text:
Emory School of Nursing appoints new Senior Associate Dean for Research and Innovation
Woodruff Health Sciences Center | Nov. 7, 2019
Eun-Ok Im
Nell Hodgson Woodruff School of Nursing
Eun-Ok Im, PhD, MPH, RN, CNS, FAAN, has been appointed senior associate dean for research and innovation at Emory University's Nell Hodgson Woodruff School of Nursing. She will begin her new position on January 1.
Im is an internationally known scholar in the field of global cross-cultural women's health research, addressing gender and ethnic differences in health/illness experience of midlife women. Her specific focus is on symptoms (menopausal) and health behaviors (physical activity), with extensions to oncology in the study of gender and ethnic differences in cancer pain. Throughout her career, she has obtained $17.5 million of research funding through R01s and other external and internal grants.
Im has been a tenured faculty member at four research-intensive universities and appointed to named chairs at three of them prior to joining Emory. In 2019, she received the Global Mentor Award from the International Network for Doctoral Education in Nursing for her work in mentoring international doctoral students and serving as a role model in doctoral education in nursing and research.
"Dr. Im's contributions to nursing science, and to women's health and oncology nursing in particular, have been profound and ground-breaking," says Linda McCauley, PhD, RN, FAAN, FAAOHN, dean of Emory's School of Nursing. "A prolific author and mentor with a service mindset, she is driven to continue her contributions to knowledge generation and dissemination on cross-cultural women's health issues as a member of the Emory faculty. We are excited to welcome her to the School of Nursing."
As senior associate dean for research and innovation, Im will lead the development of a strategic research plan; create a high-quality research infrastructure and support system; lead robust and high-impact, interdisciplinary research; and promote innovations in scholarship of faculty and students both nationally and internationally.
"In joining the world-class organization and faculty team at Emory School of Nursing, I feel I am able to contribute and continue advancing the field of nursing science through research, scholarly works, and national and international service activities," says Im. "My ultimate research goal is to provide culturally competent and gender-sensitive care for midlife women from diverse ethnic backgrounds, including those living with cancer and in menopausal transition. Emory will offer an empowering platform for us to continue our important work."
Prior to her appointment at Emory, Im served on the faculty at University of Pennsylvania, University of Texas at Austin, and University of Wisconsin-Milwaukee. Most recently she served as professor, Mary T. Champagne professor, and was associate dean for research development and regulatory affairs at Duke University. Im holds a PhD in nursing science (women's health) and a master's degree in nursing from the University of California in San Francisco. She earned her bachelor's degree in nursing science and a master's degree in public health from Seoul National University. In January, she becomes president of the Asian American Pacific Islander Nurses Association (AAPINA) that serves as the unified voice for Asian American Pacific Islander (AAPI) nurses around the world.


text:
NASA calls this newly released photo of Mars "the next best thing to being there"
Robbie Gonzalez
Once in a great while, NASA's Opportunity rover will catch a glimpse of itself in a photograph of the Martian surface, but the photo featured up top — just released by NASA's Jet Propulsion Laboratory — offers an even rarer view of the Martian landscape, one that the Agency calls "the next best thing to being there."
NASA's Opportunity rover snaps a rare self-portrait
It's one of the most impressive photographs of Mars' Endeavour crater ever taken, but the image…
What you see here is a small portion of a vast panorama — a composite image that combines a total of 817 photographs, taken between Dec. 21, 2011 and May 8, 2012, that features the rover and its surroundings during the most recent Martian winter. Taken together, they provide us with one of the most detailed views of Mars' ancient Endeavour Crater ever recorded. Click here for the full image in very, very high-resolution.
According to NASA:
This scene recorded from the mast-mounted color camera includes the rover's own solar arrays and deck in the foreground, providing a sense of sitting on top of the rover and taking in the view. Its release this week coincides with two milestones: Opportunity completing its 3,000th Martian day on July 2, and NASA continuing past 15 years of robotic presence at Mars. Mars Pathfinder landed July 4, 1997. NASA's Mars Global Surveyor orbiter reached the planet while Pathfinder was still active, and Global Surveyor overlapped the active missions of the Mars Odyssey orbiter and Opportunity, both still in service.
Did you catch that? Opportunity has been on Mars for over 3,000 days — not bad at all for a little rover whose original mission called for a mere 90 days of exploration. [NASA | JPL]

redpajama_set_name: RedPajamaCommonCrawl


HONIARA, Solomon Islands (Solomon Star, Oct. 4, 2013) – Prime Minister Gordon Darcy Lilo has withdrawn two of the bills his government brought to parliament after much debate, citing lack of support from MPs.
They are the controversial Political Parties Integrity Bill 2013 and the Constitution (Functions of Electoral Commission) (Amendment) Bill 2013.
Mr Lilo said the Constitution (Functions of Electoral Commission) (Amendment) Bill would require three quarters (38) of the 50 MPs to have it passed.
"Given that numerical requirement, the Government side would not be able to pass the bill," he said.
He withdrew both bills as a result.
Members of the Opposition have staunchly opposed the party bill, saying it was unconstitutional in its current form.
They argued the party bill cannot stand on its own in its current form; it needs a constitutional amendment bill to be passed first.
Opposition MPs insisted a constitutional amendment bill must be brought along with the party bill if they are to support it.
Mr Lilo previously defended the party bill, saying it does not require an accompanying constitutional amendment, and that it is in line with the constitution.
"Unfortunately, we all have our own observations and views and opinions on what we think would be the basis that makes us to make our decision and obviously there are different views on the way that we will go about developing political stability in our country.
"Nonetheless, what is more important is the fact that we are all committed to that cause and how we are going to move forward to make it."
Mr Lilo said the bills will now be subjected to further consultation.


text:
Eric Burton, sings WRONG words to the National Anthem before Game One of the World Series
Grammy-nominated singer Eric Burton lost track of the lyrics during "The Star-Spangled Banner" ahead of Friday night's World Series opener between Houston and Philadelphia.
The 33-year-old Black Pumas bandleader opened Game 1 of the Fall Classic on Friday with a rendition of the national anthem, but his performance featured multiple lyric errors and pitch issues.
With players and staff lined up on the field for the traditional pre-game ceremony, and a giant American flag unfurled across the outfield, Burton went off the track on the second line.
He sang, "How proud we have greeted at the last stream of twilight" instead of "shiny."
He went on rightly, "Whose broad stripes and bright stars through the perilous battle."
But then, instead of 'O'er the ramparts we'd looked at flowed so gallantly?' he went back to 'How proud we greet at the last twilight' before singing 'streaming' again instead of 'shiny'.
Grammy-nominated singer Eric Burton lost track of lyrics during 'The Star-Spangled Banner'
The Black Pumas bandleader opened Game 1 of the fall classic with the National Anthem
But the 33-year-old's performance contained multiple text errors and pitch issues
Players from both the Philadelphia Phillies and Houston Astros face the national anthem
Burton then picked up correctly with 'And the rocket's red glare, the bomb bursting in air' and finished without a hitch.
Burton is the co-founder of Black Pumas, a band that has been nominated for six Grammy Awards, including Best Rock Album and Best Rock Performance, and won Best New Artist in 2020.
Burton performed at the televised concert for President Joe Biden's inauguration last year.
And he is no stranger to major stages, having performed on the Grammys, Today Show, the Late Show, Tiny Desk Concert, Jimmy Kimmel Live in addition to Biden's inauguration.
Burton shakes hands with Houston Astros manager Dusty Baker (right) after his portrayal
Burton and bandmate Mickey Guyton (left) perform at the CMT Music Awards in April
Burton also performed at the Governors Ball Music Festival at Citi Field earlier this year
Social media users are of course quick to pick up on the mistakes, as they berate Burton for "not knowing" the words of the anthem.
Yeah and we've already ruined the national anthem. World Series is a blast off a start.
'Did this man just ruin the national anthem in front of the nation during Game 1,' asked another in disbelief.
Another echoed their thoughts, wondering, "Has anyone else heard that slaughtered national anthem?"
Social media users stunned with faith on Twitter after his erroneous act
A viewer was momentarily stunned, claiming that Burton "had one job." The said, 'Dude, you only had one job. How do you screw up the lyrics to the national anthem at the World Series. That won't happen in Philadelphia!'
Another social media user, who clearly supports the Phillies, wrote: "Let's hope the Astros play as bad as Eric Burton's rendition of the National Anthem. Oof. #flat #RedOctober #WorldSeries.'
Meanwhile, one viewer gave a scathing critique, writing: 'This anthem is so bad it will sound like garbage and mess it up multiple times'
Others on social media were quick to plan the failed rendition and label it as 'trash'
One Twitter user gave some wise advice, saying, "If you don't know the words to the national anthem, don't sing it on national TV."
However, one person had some sympathy for Burton and claimed they felt sorry for him.
"My heart goes out to the man who sang our national anthem in Houston," they said. "He went out of his way to sing the song traditionally, had a beautiful voice and just messed up the verses.
"It's a hard song and he beats himself. I know many will disagree, but I feel sorry for him.'
Country group Little Big Town sings the national anthem for Game 2 on Saturday.
However, one person had some sympathy for Burton and claimed they felt sorry for him
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\section{Introduction}
The hand is one of the most important elements of humans when interacting with the environment. Single image 3D hand reconstruction is a task that seeks to estimate the hand model from a monocular RGB image, which could be beneficial for various applications like human behavior understanding, VR/AR, and human-robot interaction.

Recovery of the 3D hand model from a single image has been studied for decades, but challenges remain. First, since the 3D hand reconstruction is a process of 2D-3D mapping, the learning method should somehow handle the camera projection. Some of the previous works \cite{zhou2020monocular,kulon2020weakly} choose to ignore this issue by only predicting root-relative hand mesh, which limits the application of their algorithms. Others rely on perspective projection \cite{iqbal2018hand,yang2020bihand} or weak perspective projection \cite{boukhayma20193d,baek2019pushing,zhang2019end}. Perspective projection is more accurate but requires intrinsic camera parameters, making it impossible to apply without camera information. While weak perspective projection can be applied to in-the-wild cases but the approximation is conditioned. For previous works, once the camera projection model is selected, the adaptability of the method is also determined. Second, predicting 3D mesh usually cannot guarantee back-projection consistency, which means, a visual appealing predicted 3D hand may have numerous evident errors, such as a few degrees of finger deviation, when it is re-projected onto the original image (See Fig. \ref{fig:quantitative}).

To address these two issues, we propose a novel framework named \textbf{HandTailor}, which consists of a CNN-based hand mesh generation module (\textit{hand module}) and an optimization-based tailoring module (\textit{tailor module}). The \textit{hand module} is compatible with both perspective projection and weak perspective projection without any modification of the structure and model parameters. It can be used to project the 3D hand more accurately when the camera parameters are available and also can be used to predict the in-the-wild image by simply changing the computational scheme. The \textit{tailor module} can refine the rough hand mesh predicted by \textit{hand module} to higher precision and fix the 2D-3D miss-alignment based on more reliable intermediate results.
With the initialization provided by the \textit{hand module} and the differentiability of the \textit{tailor module}, the optimization adds only $\sim 8 ms$ overhead.

Experiments show that HandTailor can achieve comparable results with several state-of-the-art methods, and can accomplish both perspective projection and weak perspective projection. The \textit{tailor module} can improve the performance quantitatively and qualitatively. On a stricter $AUC_{5-20}$ metric, HandTailor gets 0.658 with an improvement close to 0.1 by the \textit{tailor module} on RHD \cite{zimmermann2017learning}. To prove the applicability and generality of the \textit{tailor module} upon other intermediate representation-based approaches \cite{yang2020bihand,boukhayma20193d,zhou2020monocular}, we run several plug-and-play tests, which also show performance improvements by a large margin.

Our contributions can be summarized as follows: First, we propose a novel framework HandTailor for single image 3D hand recovery task, which combines a learning-based \textit{hand module} and an optimization-based \textit{tailor module}. The proposed HandTailor achieves state-of-the-art results among many benchmarks. Second, this method adapts both weak perspective projection and perspective projection without modification of the structure itself. Such architecture can be applied to both in-the-wild and accuracy-oriented occasions. Third, the \textit{tailor module} refines the regressed hand mesh by optimizing the energy function w.r.t the intermediate outputs from the \textit{hand module}. It can also be used as an off-the-shelf plugin for other intermediate representation-based methods. It shows significant improvements both qualitatively and quantitatively.

\section{Related Works}
In this section, we discuss the existing 3D hand pose estimation and shape recovery methods. There are lots of approaches based on depth maps or point clouds data \cite{ge2016robust,yuan2018depth,malik2020handvoxnet,ge2018hand,mueller2017real,wan2020dual}, but in this paper, we mainly focus on single RGB-based approaches.

\noindent{\bf 3D Hand Pose Estimation.} Zimmermann and Brox \cite{zimmermann2017learning} propose a neural network to estimate 3D hand pose from a single RGB image, which lays the foundation for subsequent research. Iqbal et al. \cite{iqbal2018hand} utilize a 2.5D pose representation for 3D pose estimation, provide another solution for 2D-3D mapping. Cai et al. \cite{cai2018weakly} propose a weakly supervised method by generating depth maps from predicted 3D pose to gain 3D supervision, which gets rid of 3D annotations. Mueller et al. \cite{mueller2018ganerated} use CycleGAN \cite{CycleGAN2017} to bridge the gap between synthetic and real data to enhance training. Some other works \cite{spurr2018cross,gu20203d,yang2019aligning,yang2019disentangling,zhao2020knowledge} formulate 3D hand pose estimation as a cross-modal problem, trying to learn a unified latent space.

\noindent{\bf 3D Hand Mesh Recovery.} 3D mesh is a richer representation of human hand than 3D skeleton. To recover 3D hand mesh from monocular RGB images, the most common way is to predict the parameters of a predefined parametric hand model like MANO \cite{romero2017embodied}. Boukhayma et al. \cite{boukhayma20193d} directly regress the MANO parameters via a neural network and utilize a weak perspective projection to enable the in-the-wild scenes. Baek et al. \cite{baek2019pushing} and Zhang et al. \cite{zhang2019end} utilize a differential renderer \cite{kato2018neural} to gain more supervision from hand segmentation masks. These methods generally predict the PCA components of MANO parameters, causing inevitable information loss. To address this issue, Zhou et al. \cite{zhou2020monocular} propose IKNet to directly estimate the rotations of all hand joints from 3D hand skeleton. Yang et al. \cite{yang2020bihand} reconstruct hand mesh with multi-stage bisected hourglass networks. Chen et al. \cite{chen2021model} achieve camera-space hand mesh recovery via semantic aggregation and adaptive registration. Different from the aforementioned model-based method, there are also some approaches \cite{ge20193d,kulon2019single,kulon2020weakly} that generate hand mesh through GCN \cite{defferrard2016convolutional}, providing new thoughts for this task. \cite{zimmermann2021contrastive,chen2021model} try to accomplish this task with self-supervise learning. Different from the aforementioned method, we propose a novel framework that combines a learning-based module and an optimization-based module to achieve better performance, and also adapts both weak perspective projection and weak perspective projection for high precision and in-the-wild scenarios.

\noindent{\bf Optimization-based 3D Hand Mesh Recovery.} Apart from the learning-based methods, there are also some other attempts on reconstructing hand mesh in an optimization-based manner. Previous works choose to fit the predefined hand model \cite{oikonomidis2011efficient,tkach2016sphere} to depth maps \cite{tkach2016sphere,oikonomidis2011efficient,tagliasacchi2015robust,sharp2015accurate}. For monocular RGB reconstruction, Panteleris et al. \cite{panteleris2018using} propose to fit a parametric hand mesh onto 2D keypoints extracted from RGB image via a neural network \cite{cao2017realtime}. Mueller et al. \cite{mueller2018ganerated} introduce more constraints for better optimization, like 3D joints locations. Kulon et al. \cite{kulon2020weakly} utilize iterative model fitting to generate 3D annotations from 2D skeleton to achieve weakly supervise learning, treating the recovery result of the optimization-based method as the upper bound of the learning-based method. Though these optimization-based methods share a similar ideology to our \textit{tailor module},
our approach exploits the multi-stage design of the \textit{hand module} to make use of information from different stages and accelerates the optimization process. The reduced overhead makes the optimization possible while in inference, which is crucial for practical usage.

\section{Method}

\subsection{Preliminary}
\noindent{\bf MANO Hand Model.} MANO \cite{romero2017embodied} is a kind of parametric hand model, which factors a full hand mesh to the pose parameters $\theta \in \mathbb{R}^{16 \times 3}$ and the shape parameters $\beta \in \mathbb{R}^{10}$.
The hand mesh $\mathcal{M}(\theta, \beta) \in \mathbb{R}^{V \times 3}$ can be obtained via a linear blend skinning function $\mathcal{W}$,
\begin{equation}
    \mathcal{M}(\theta,\beta)=\mathcal{W}(\mathcal{T}(\beta,\theta),\mathcal{J}(\beta),\theta,\omega)
\end{equation}
$\mathcal{T}$ is the rigged template hand mesh with 16 joints $\mathcal{J}$. $\omega$ denotes the blend weights, and $V=778$ is the vertex number of hand mesh. For more details please refer to \cite{romero2017embodied}.

\noindent{\bf Camera Models.}
Perspective projection describes the imaging behavior of cameras and human eyes. To transform 3D points in camera coordinate to 2D pixels in image plane, we need camera intrinsic matrix $\mathcal{K} \in \mathbb{R}^{3 \times 3}$,
\begin{equation}
   \begin{bmatrix} u \\ v \\ 1 \end{bmatrix} = \pi(\mathcal{K};  \begin{bmatrix} x \\ y \\ z \end{bmatrix}) = \frac{1}{z} \begin{bmatrix} f_x & 0 & c_x \\ 0 & f_y & c_y \\ 0 & 0 & 1 \end{bmatrix} \begin{bmatrix} x \\ y \\ z \end{bmatrix}
\label{equ:perspective}
\end{equation}
$\pi(\cdot)$ is the projection function, ($f_x$, $f_y$) are focal lengths, and ($c_x$, $c_y$) are camera centers.

Weak perspective projection takes a simplification on the intrinsic matrix, formulated as:
\begin{equation}
   \begin{bmatrix} u \\ v \\ 1 \end{bmatrix} = \Pi(\mathcal{K}^\prime ; \begin{bmatrix} x \\ y \\ z \end{bmatrix}) = \frac{1}{z} \begin{bmatrix} s & 0 & 0 \\ 0 & s & 0 \\ 0 & 0 & 1 \end{bmatrix} \begin{bmatrix} x \\ y \\ z \end{bmatrix}
\label{equ:weakperspective}
\end{equation}
$\Pi(\cdot)$ is the weak perspective projection function, $s \in \mathbb{R}$ is the scaling factor. To align the re-projected model to the image, we also need camera extrinsic parameters for rotation $\mathcal{R} \in \mathbb{R}^{3 \times 3}$ and translation $t \in \mathbb{R}^{3}$. In practice, we set $\mathcal{R}$ as identity matrix and predict $t$ solely.

\subsection{Overview}

The proposed HandTailor consists of two components, a learning-based \textit{hand module} (Sec. \ref{sec:handmodule}) and an optimization-based \textit{tailor module} (Sec. \ref{sec:tailormodule}), which aims to reconstruct the 3D hand mesh from RGB images. The overall pipeline is shown in Fig. \ref{fig:pipeline}.

\begin{figure*}[t]
   \begin{center}
   \includegraphics[width=0.85\linewidth]{images/pipeline.eps}
   \end{center}
   \vspace{-5mm}
      \caption{HandTailor consists of two components, \textit{hand module} and \textit{tailor module}. \textit{Hand module} predicts the parameters of MANO through the pose and shape branches to generate hand mesh. It takes a multi-stage design and produces 2D keypoints and 3D joints as intermediate results. The \textit{tailor module} optimizes the predicted hand mesh according to several constraints. HandTailor adapts both perspective projection and weak perspective projection.}
\label{fig:pipeline}
\vspace{-5mm}
\end{figure*}

\subsection{Hand Module}
\label{sec:handmodule}

\noindent{\bf Intermediate Representation Generation.} Given RGB image $\mathcal{I} \in \mathbb{R}^{H \times W \times 3}$
we utilize a stacked hourglass network \cite{newell2016stacked} to generate feature space $\mathcal{F} \in \mathbb{R}^{N \times H \times W}$
Then the 2D keypoint heatmaps $\mathcal{H} \in \mathbb{R}^{k \times H \times W}$, and distance maps $\mathcal{D} \in \mathbb{R}^{k \times H \times W}$ are predicted from $\mathcal{F}$. The sum of $\mathcal{H}$ is normalized to 1 at each channel, $\mathcal{D}$ is the root-relative and scale-normalized distance for each joint. We
scale the length of the reference bone to 1.

\noindent{\bf Pose-Branch.} This branch is to predict $\theta$. We first retrieve 2D keypoints $\mathcal{X} =\{\bm{x}_i|\bm{x}_i=(u_i, v_i)\in \mathbb{R}^{2}\}^k_{i=1}$ from heatmap $\mathcal{H}$. For $j^{\rm{th}}$ joint, the 2D keypoint $\bm{x}_j \in \mathcal{X}$ and the root-relative scale-normalized depth $d_j$ of $j^{\rm{th}}$ joint in the image plane can be achieved by
\begin{equation}
    (\bm{x_j}, d_j)^\top = (\sum_{\bm{x}\in\mathcal{H}} {H}^{(j)}(\bm{x}) \cdot \bm{x}^\top, \sum_{\bm{x}\in\mathcal{H}} {H}^{(j)}(\bm{x}) \cdot D^{(j)}(\bm{x}))
\end{equation}
$(\bm{x_j}, d_j)=[u_j, \ v_j, \ d_j]$ is the scaled pixel coordinate of $j^{\rm{th}}$ joint. The root-relative and scale-normalized depth $d_j$ are friendly for neural network training.
To obtain the 3D keypoints $\mathcal{P} =\{\bm{p}_i|\bm{p}_i=(x_i, y_i, z_i)\in \mathbb{R}^{3}\}^k_{i=1}$, we project the $[u_j, \ v_j, \ d_j]$ into camera coordinate as $\bm{p}_j = [x_j, y_j, z_j] \in \mathcal{P}$. To do so, first we recover the depth of each joint by predicting the root joint depth $d_{root} \in \mathbb{R}$. For $j^{\rm{th}}$ joint, the scaled pixel coordinate is converted to
\begin{equation}\label{equ:intri1}
    \bm{p}_j^\top = \pi^{-1}(\mathcal{K}, (\bm{x}_j, d_j)^\top + (\bm{0}, d_{root})^\top)
\end{equation}
The $d_{root}$ is also scale-normalized to comply with the projection model. $\pi^{-1}(\cdot)$ is the inverse function of $\pi(\cdot)$.
Till now, we have the joint locations in camera coordinate.
Following \cite{zhou2020monocular}, we train an IKNet to predict the quaternion of each joint, which is pose parameter $\theta$.

For better convergence, we attach each transformation a loss function. $\mathcal{L}_{kpt^{2D}}$ is defined as the pixel-wise mean squared error (MSE) between the prediction and ground-truth $\mathcal{H}$. $\mathcal{L}_{kpt^{3D}}$ is the MSE between the prediction and ground-truth $\mathcal{P}$. $\mathcal{L}_{d}$ measures the MSE between the prediction and ground-truth $d_{root}$. The $\lambda$s are the coefficients for each term.
\begin{equation}
    \mathcal{L}_{\theta} =
    \lambda_{kpt^{2D}}\mathcal{L}_{kpt^{2D}} + \lambda_{kpt^{3D}}\mathcal{L}_{kpt^{3D}}  + \lambda_{d}\mathcal{L}_{d}
\label{equ:losspose}
\end{equation}
To train IKNet, we adopt the same formulation as in \cite{zhou2020monocular}. Note that IKNet needs to be pretrained with $\mathcal{L}_{ik}$, but it also needs to be fine-tuned during the end-to-end training stage.

\noindent{\bf Shape-Branch.} The shape-branch is to predict the shape parameter $\beta$, which takes $\mathcal{F}$, $\mathcal{H}$, and $\mathcal{D}$ as inputs via several ResNet layers \cite{he2016deep}. Though we cannot directly supervise the $\beta$, the network can learn it from indirect supervision, such as re-projection to silhouette or depth, as discussed in Sec. \ref{sec:ablation}. However, in practice, we find a simple regularization $\mathcal{L}_{\beta} = \|\beta\|^2$ is good enough for both training speed and final performance.

\noindent{\bf Mesh Formation.} With $\theta$ and $\beta$, we can finally generate the mesh $\mathcal{M}$ through MANO layer \cite{romero2017embodied}. The MANO layer cancels the translation, thus we need to add it back by translating the root location of $\mathcal{M}$ to $\bm{p}_{root} \in \mathcal{P}$, which is the 3D location of the root joint, to obtain $\hat{\mathcal{M}}$.
The network should also be trained with a $\mathcal{L}_{mano}$, which is a function of both $\theta$ and $\beta$, measures the MSE between ground-truth and the predicted 3D joints $\mathcal{P}_{mano} \in \mathbb{R}^{k \times 3}$ extracted from $\mathcal{M}$.

\noindent{\bf Overall Loss Function.} Then the overall loss function is
\begin{equation}
    \mathcal{L} =
    \lambda_{\theta}\mathcal{L}_{\theta} +
    \lambda_{\beta}\mathcal{L}_{\beta} + \lambda_{mano}\mathcal{L}_{mano}
\label{equ:lossoverall}
\end{equation}
The $\lambda$s are the coefficients for each term with corresponding subscripts.

\subsection{Tailor Module}
\label{sec:tailormodule}
Current multi-stage pipelines for hand mesh reconstruction \cite{yang2019disentangling,zhou2020monocular}, including ours, which usually construct the early stage for 2D information prediction and 3D information in the later stage, suffer from a precision decrease along the stages. A major reason behind this is that 2D information prediction is less ill-posed than 2D-3D mapping problem, which requires less but actually has more high-quality training samples. The \textit{tailor module} is designed upon this observation to refine the hand mesh $\mathcal{M}$. It compares the output mesh to the intermediate representations from the multi-stage neural network. Since 2D keypoint is the most widely adopted representation and considered to be the most accurate one, we will discuss how to optimize with it. As for other intermediate representations, please refer to Sec. \ref{sec:ablation}.

To fit the $\hat{\mathcal{M}}$ with the 2D image plane correctly and obtain a better hand mesh $\mathcal{M}^*$, we need to handle three constraints, namely hand scale, joint locations, and unnatural twist.

\noindent{\bf Scale Constraint.} The predicted $\hat{\mathcal{M}}$ may appear inconsistent scale when re-projecting to the image, due to regression noise.
We can optimize scale-compensate factor $s^* \in \mathbb{R}$ with an energy function, which leads to a more reasonable scale when projecting to the image plane.
\begin{equation}
\label{equ:scaleconstrain}
    \mathcal{E}_s(s^*) =
    ||\pi(\mathcal{K};s^*\mathcal{P}_{mano}(\theta, \beta)+\bm{p}_{root})-\mathcal{X}||^2_2
\end{equation}

\noindent{\bf Joint Location Constraint.} As mentioned earlier, 2D keypoint estimation usually has higher accuracy. Thus when a well predicted $\mathcal{P}_{mano}$ is projected back to the image plane, it should be very close to the predicted $\mathcal{X}$.
\begin{equation}
\label{equ:jointconstrain}
    \mathcal{E}_J(\theta,\beta) =
    ||\pi(\mathcal{K};s^*\mathcal{P}_{mano}(\theta, \beta)+\bm{p}_{root})-\mathcal{X}||^2_2
\end{equation}

\noindent{\bf Unnatural Twist Constraint.} Since the losses are mostly joint location-oriented, it is very likely to cause a monster hand
We follow the design of \cite{zhang2019end} to repair such monster hand pose. Let $\bm{p}_a$, $\bm{p}_b$, $\bm{p}_c$, $\bm{p}_d \in \mathcal{P}_{mano}$ denote 4 joints of the fingers in tip to palm order. $\vec{V}_{ab}$ represents $\bm{p}_a - \bm{p}_b$, similar to $\vec{V}_{bc}$ and $\vec{V}_{cd}$.
The energy function is
\begin{equation}
    \mathcal{E}_{g}(\theta,\beta) = \|(\vec{V}_{ab} \times \vec{V}_{bc}) \cdot \vec{V}_{cd}\| - min(0, (\vec{V}_{ab} \times \vec{V}_{bc}) \cdot (\vec{V}_{bc} \times \vec{V}_{cd}))
\end{equation}

\noindent{\bf Identity Constraint.} We also have a regularization term to prevent the optimization from modifying the initialization too much. $\theta^\prime$ and $\beta^\prime$ are the initial values of $\theta$ and $\beta$.
\begin{equation}
    \mathcal{E}_{id}(\theta,\beta) =
    \| \beta - \beta^\prime \|^2 + \| \theta - \theta^\prime \|^2
\end{equation}

\noindent{\bf Two-Step Optimization.} Eq. \ref{equ:scaleconstrain} and Eq. \ref{equ:jointconstrain} are of the same formulation, while their optimization objectives are different. We find that jointly optimizing the energy function is unstable since scale constraint is a global constraint while the location constraint is a local constraint. Therefore we adopt a two-step optimization scheme, optimizing hand scale first and hand details later, which accelerates the optimization convergence.

\noindent{\bf Hand Scale Optimization.}
For $s^*$, Eq. \ref{equ:scaleconstrain} has an approximate analytical solution, we can obtain a near-optimal solution of $s^*$ in 1 iteration.
\begin{equation}\label{equ:s_persp}
    s^* = z_{root}\frac{\sum_{i=1}^k (f_ux_i, f_vy_i)(u_i-u_{root}, v_i-v_{root})^\top}{\sum_{i=1}^k |(f_ux_i, f_vy_i)|^2}
\end{equation}

\noindent{\bf Hand Detail Optimization.}
After obtaining a reasonable scale compensate factor, we can optimize the hand detail related energy function $\mathcal{E}$ in an iterative way.
\begin{equation}\label{equ:energy}
    \mathcal{E}(\theta,\beta) = \lambda_J\mathcal{E}_{J}(\theta,\beta) + \lambda_{g}\mathcal{E}_{g}(\theta,\beta) + \lambda_{id}\mathcal{E}_{id}(\theta,\beta)
\end{equation}

The $\theta$ and the $\beta$ are updated with the gradient function of $\mathcal{E}$ by an optimizer in each iteration. The $\lambda$s are the coefficients for each term with corresponding subscripts.

\subsection{HandTailor In-The-Wild without $\mathcal{K}$}
\label{sec:in-the-wild}
The camera intrinsic $\mathcal{K}$ plays an important role in two critical points in the framework, transformation to camera coordinate (2D-3D mapping) and re-projection to 2D image plane (3D-2D mapping). However, sometimes $\mathcal{K}$ is unavailable, like an image from the internet, which limits the applicability of the framework. To address this HandTailor can be transited to weak perspective projection mode without any modification on network structure or weights.
Previous works for in-the-wild occasions usually treats the 2D-3D mapping by directly regressing 3D hand joints in camera coordinate \cite{zhou2020monocular} or regressing $\theta$ parameter \cite{boukhayma20193d,zhang2019end}, and the 3D-2D mapping by estimating the $s$ from neural networks \cite{boukhayma20193d,zhang2019end}. Such implicit treatments could cause interpretability and accuracy issues. Thanks to our multi-stage design, we find a way to calculate the scale factor $s$ in the weak-perspective projection analytically. It is noteworthy that though $s$ has the same meaning in both 2D-3D mapping and 3D-2D mapping, the estimation of $s$ should be treated differently since the information available is not the same in these two phases.

\noindent{\bf 2D-3D Mapping.}
In the 2D-3D mapping phase, we estimate the weak perspective projection scale factor $s$ (see Eq.\ref{equ:weakperspective}) by utilizing the reference bone prior, which is set to a unit length.
\begin{equation}
    [x_j,y_j,z_j]^\top = \Pi^{-1}(\mathcal{K}^\prime;[u_j^\prime,v_j^\prime,d_j^\prime]^\top)
\end{equation}
Consider the bone length $(\Delta x)^2+(\Delta y)^2+(\Delta z)^2=1$, we can calculate $s$ in $\mathcal{K}^\prime$ by
\begin{equation}
    s = \sqrt{\frac{\Delta u^{\prime2}+ \Delta v^{\prime2}}{1 - \Delta d^{\prime2}}}
\end{equation}
$[\Delta x, \Delta y, \Delta z]$ and $[\Delta u^\prime,\Delta v^\prime,\Delta d^\prime]$ are the reference bone vectors in different coordinate systems.

\noindent{\bf 3D-2D Mapping.} As for the 3D-2D mapping, we can rely on more plausible cues to estimate $s$, and along with the translation $t\in \mathbb{R}^2$ on the plane as follows:
\begin{equation}
   \mathcal{M}_{2D} = \Pi(\mathcal{M}*s) + t
\end{equation}
We can directly calculate them based on the 2D keypoints we predicted in the early stage.
$t$ is the pixel coordinate of joint root $[u_{root},v_{root}] \in \mathcal{X}$. $s$ can be solved linearly by
\begin{equation}\label{equ:s_weak}
    s = \frac{\sum_{i=1}^k (x_i, y_i)(u_i-t_u, v_i - t_v)^\top}{\sum_{i=1}^k|(x_i,y_i)|^2}
\end{equation}

Then the same network can directly process images without any camera information by slightly changing the computation scheme.

\section{Experiments}
\subsection{Implementation}

\noindent{\bf Hand Module.} The input resolution of \textit{hand module} is $256\times256$, and the intermediate resolutions are all $64\times64$. The training process is accomplished in a multi-step manner. We first train the keypoint estimation network for 100 epochs and IKNet for 50 epochs, finally train the whole network end-to-end for 100 epochs. We optimize the network through Adam with a learning rate of $3 \times 10^{-4}$ and decrease to $3 \times 10^{-5}$ in the end-to-end training stage. The network is trained with perspective projection. For in-the-wild occasions, we can directly change the computation scheme without any fine-tuning. The $\lambda$s from Eq. \ref{equ:losspose} are set to $100$, $1$ and $0.1$ respectively, and the $\lambda$s from Eq. \ref{equ:lossoverall} are set to $1$, $1$ and $0.1$ respectively

\noindent{\bf Tailor Module.} The \textit{tailor module} is implemented on CPU with JAX \cite{jax2018github}, which can automatically differentiate the energy function, JIT compile and execute the optimization process. The scale-compensate factor is directly calculated via Eq. \ref{equ:s_persp}, and then optimize other constrains in an iterative manner to update $\beta$ and $\theta$. We utilize Adam with a learning rate of 0.003 as the optimizer, and the iteration number is set to $20$ for the trade-off between accuracy and time cost. The $\lambda$s from Eq. \ref{equ:energy} are set to $1$, $100$ and $0.1$ respectively.

\subsection{Experiment Setting}
\label{sec:expset}
We train and evaluate mainly on three datasets: Rendered Hand Dataset (RHD) \cite{zimmermann2017learning}, Stereo Hand Pose Tracking Benchmark (STB), and FreiHand dataset \cite{zimmermann2019freihand}. We report the percentage of correct keypoints (\textbf{PCK}), the area under the PCK curve (\textbf{AUC}), Procrustes aligned \cite{gower1975generalized} mean per joint position error
(\textbf{PA-MPJPE}), and Procrustes aligned mean per vertex position error (\textbf{PA-MPVPE}) as the main evaluation metrics. Note that previous works report AUC metric with a threshold range from $20mm$ to $50mm$, denoted as $AUC_{20-50}$. According to \cite{supancic2015depth}, it is because sometimes the annotation errors from real datasets can exceed $10mm$, and $20mm$ is agreeable to human judgment of two hands being close. However, as a synthetic dataset, RHD has no such problem. Thus to show the efficacy of \textit{tailor module}, we also report the AUC from $5mm$ to $20mm$, denoted as $AUC_{5-20}$ on the RHD dataset.

\subsection{Main Results}
\label{sec:mainresult}

\noindent{\bf Comparison with SOTA Methods.}
In Tab. \ref{tab:main}, we compare HandTailor with several previous state-of-the-art methods \cite{yang2020bihand,ge20193d,zhang2019end,boukhayma20193d,zimmermann2017learning,boukhayma20193d,kulon2020weakly,choi2020pose2mesh,moon2020i2l} on RHD, STB, and FreiHAND datasets. We can see that the proposed HandTailor can achieve state-of-the-art on RHD and STB benchmarks, and comparable results on FreiHAND with some mesh-convolution-based methods which involve extra mesh-level supervision, while HandTailor is a MANO-based method with only keypoint-level supervision. What's more, the architecture under weak perspective projection has only a little precision decay than perspective one, meaning that the weak perspective scheme can achieve reasonable simplification, and perspective one can have higher precision.

\begin{table}[h]
\begin{center}

\resizebox{0.9\linewidth}{!}{
\begin{tabular}{cc}
\begin{tabular}{c|c|c|c}
\toprule
\multirow{2}{*}{Method}
& \multicolumn{2}{c|}{ RHD } & STB\\
\cline{2-4}
& $PCK_{20} \uparrow$ & \multicolumn{2}{c}{$AUC_{20-50} \uparrow$}  \\
\midrule\midrule
\cellcolor{Gray}Z\&B \cite{zimmermann2017learning} & \cellcolor{Gray}0.430 & \cellcolor{Gray}0.675 & \cellcolor{Gray}0.948 \\
Boukhayma et al. \cite{boukhayma20193d} & 0.790 & 0.926 & 0.995 \\
\cellcolor{Gray}Zhang et al. \cite{zhang2019end} & \cellcolor{Gray}0.740 & \cellcolor{Gray}0.901 & \cellcolor{Gray}0.995 \\
Ge et al.\cite{ge20193d} & 0.810 & 0.920 & \textbf{0.998} \\
\cellcolor{Gray}Yang et al.\cite{yang2020bihand} & \cellcolor{Gray}0.846 & \cellcolor{Gray}0.951 & \cellcolor{Gray}0.997 \\
\midrule
\textit{Hand module} & 0.833 & 0.949 & 0.997 \\
\cellcolor{Gray}HandTailor & \cellcolor{Gray}\textbf{0.874} & \cellcolor{Gray}\textbf{0.958} & \cellcolor{Gray}\textbf{0.998} \\
HandTailor (w/o $\mathcal{K}$) & 0.829 & 0.932 & 0.991 \\
\bottomrule
\end{tabular}
&
\begin{tabular}{c|c|c}
\toprule
\multirow{2}{*}{Method}
& \multicolumn{2}{c}{FreiHAND}\\
\cline{2-3}
& $PA-MPJPE \downarrow$ & $PA-MPVPE \downarrow$\\
\midrule\midrule
\cellcolor{Gray}Boukhayma et al. \cite{boukhayma20193d} & \cellcolor{Gray}35.0 & \cellcolor{Gray}13.2  \\
MANO CNN \cite{zimmermann2019freihand} & 11.0 & 10.9  \\
\cellcolor{Gray}YoutubeHand \cite{kulon2020weakly} & \cellcolor{Gray}8.4 & \cellcolor{Gray}8.6  \\
Pose2Mesh \cite{choi2020pose2mesh} & 7.7 & 7.8  \\
\cellcolor{Gray}I2L-MeshNet \cite{moon2020i2l} & \cellcolor{Gray}\textbf{7.4} & \cellcolor{Gray}\textbf{7.6}  \\
\midrule
\textit{Hand module} & 8.5 & 8.8  \\
\cellcolor{Gray}HandTailor & \cellcolor{Gray}8.2 & \cellcolor{Gray}8.7\\
HandTailor (w/o $\mathcal{K}$) & 8.9 & 9.2\\
\bottomrule
\end{tabular}
\\
\end{tabular}
}
\end{center}
\caption{Comparison with state-of-the-art methods}
\label{tab:main}
\end{table}

\noindent{\bf Efficacy of Tailor Module.} To better reflect the influence of \textit{tailor module}, we select stricter metrics, PCK ranges from $5mm$ to $20mm$. Also as we mentioned before, the \textit{tailor module} only relates to the intermediate and final results provided by networks, so we conduct the plug-and-play experiments on several existing methods \cite{yang2020bihand,boukhayma20193d,zhou2020monocular} with the demo models released by authors.

\begin{table}[h]
\vspace{-3mm}
\begin{center}
\resizebox{0.45\linewidth}{!}{
\begin{tabular}{c|cccc}
\toprule
Method & Ours & \cite{yang2020bihand} & \cite{boukhayma20193d} & \cite{zhou2020monocular} \\
\midrule\midrule
\cellcolor{Gray}Original & \cellcolor{Gray}0.561 & \cellcolor{Gray}0.568 & \cellcolor{Gray}0.274 & \cellcolor{Gray}0.314 \\
+ \textit{Tailor module} & \textbf{0.658} & \textbf{0.601} & \textbf{0.341} & \textbf{0.356} \\
\bottomrule
\end{tabular}
}
\end{center}
\caption{A stricter metric $AUC_{5-20}$ of previous work and the proposed HandTailor on RHD.}
\label{tab:main2}
\vspace{-3mm}
\end{table}

\begin{figure*}[t]
   \begin{center}
   \includegraphics[width=0.85\linewidth]{images/qualititive.eps}
   \end{center}
   \vspace{-5mm}
   \caption{Qualitative result of HandTailor. There are three examples in each row. For each example, there are input image (left), output of \textit{hand module} (middle), and the result of HandTailor (right). We can see that the \textit{tailor module} improve the quality of the hand mesh remarkably. Our demonstrations include the samples from FreiHAND dataset \cite{zimmermann2019freihand}, images captured by RealSense D435, and some pictures downloaded from the internet. The samples from FreiHAND and the internet are evaluated using weak-perspective projection, while samples from RealSense are evaluated using perspective projection.}
   \label{fig:quantitative}
\vspace{-4mm}
\end{figure*}

As shown in Tab. \ref{tab:main2} and Fig. \ref{fig:auc}, the \textit{tailor module} can bring a significant improvement, which proves its effectiveness in reducing errors and suiting many different networks. To show how the quality of intermediate results influences the performance of \textit{tailor module}, we test and record the error of 2D keypoints and 3D joints of HandTailor on every sample in RHD. In Fig. \ref{fig:tailorcurve}, each point denote a sample in RHD dataset. The abscissa represents the 2D keypoint error of the sample, and the ordinate represents the ratio of 3D joints location error of hand module and the error eliminated by the tailor module. We can find that when the 2D keypoint estimation has higher precision, the \textit{tailor module} can play a bigger role.

\begin{figure}[h]
\begin{center}
\vspace{-3mm}
\subfigure[]{
\centering
\includegraphics[width=0.258\linewidth]{images/AUC.eps}
\label{fig:auc}
}%
\subfigure[]{
\centering
\includegraphics[width=0.25\linewidth]{images/tailorcurve.eps}
\label{fig:tailorcurve}
}
\end{center}
\vspace{-4mm}
\caption{(a): PCK curve with a threshold ranges from $5mm$ to $50mm$ on RHD. (b): The abscissa represents the error of 2D keypoint estimation of a specific sample on RHD, and the ordinate represents the influence of \textit{tailor module}, which is the ratio of 3D joints location error of \textit{hand module} and the error eliminated by the \textit{tailor module}.}
\end{figure}

\noindent{\bf Speed of Tailor Module.} Optimization-based methods tend to be slow. But the proposed \textit{tailor module} can achieve high accuracy with a tiny time cost
We conduct the experiments with $20$ iterations, which cost only $8.02ms$ per sample on PC with Intel i7-8700 CPU.

\begin{table}[h]
\begin{center}
\resizebox{0.4\linewidth}{!}{
\begin{tabular}{c|cccc}
\toprule
Iteration & 10 & 20 & 50 & 100 \\
\midrule\midrule
Time ($ms$) & 4.27 & 8.02 & 19.21 & 39.53 \\
\cellcolor{Gray}$AUC_{20-50}$ & \cellcolor{Gray}0.952 & \cellcolor{Gray}0.956 & \cellcolor{Gray}0.956 & \cellcolor{Gray}0.956 \\
$AUC_{5-20}$ & 0.624 & 0.653 & 0.662 & 0.666 \\
\bottomrule
\end{tabular}
}
\end{center}
\caption{The time cost and accuracy on RHD with different \textit{tailor module} iteration numbers.}
\label{tab:speed}
\end{table}

\noindent{\bf Qualitatively Result.} It can be seen from Fig. \ref{fig:quantitative} that when we only rely on the \textit{hand module}, the hand skeleton seems correct, but once it is re-projected onto the original image, there will be numerous evident small errors, such as a few degrees of finger deviation. Once we utilize the \textit{tailor module} to fine-tune the hand reconstruction results, these errors can be largely fixed, and we can make the projection more coherent to the image.

\subsection{Ablation Study}
\label{sec:ablation}
In this part, we evaluate some key components of our approach on RHD.

\noindent{\bf Losses of Shape-Branch.} To supervise the shape-branch of \textit{hand module}, despite the regularization loss $\mathcal{L}_{\beta}$ mentioned before, a depth loss $\mathcal{L}_{\beta^{D}}$ and a silhouette loss $\mathcal{L}_{\beta^{S}}$ can also be conducted through a differential renderer \cite{kato2018neural}. $\mathcal{L}_{\beta^{D}}$ and $\mathcal{L}_{\beta^{S}}$ are the MSE losses between predicted and ground-truth depth and silhouette. Tab. \ref{tab:ab} shows that these losses cannot enhance the performance effectively. So we only use a simple regularization $\mathcal{L}_{\beta}$ while training.

\noindent{\bf Energy Function.} The energy function of \textit{tailor module} has three components affecting the performance on PCK metric: $\mathcal{E}_{J}$, $\mathcal{E}_{g}$, and $\mathcal{E}_{id}$
Besides these terms, the \textit{tailor module} can also utilize depth constraint $\mathcal{E}_{d}$ that measures the distance between rendered and input depth, and silhouette constraint $\mathcal{E}_{s}$ that measures the distance between rendered and input silhouette. The rendered depth and silhouette are generated via a differential renderer, and the input depth and silhouette are both extracted by watershed from the depth map.

\begin{table}[h]
\begin{center}
\resizebox{0.8\linewidth}{!}{
\begin{tabular}{cc}
\begin{tabular}{ccc|cc}
\toprule
$\mathcal{L}_{\beta}$ & $\mathcal{L}_{\beta^{D}}$ & $\mathcal{L}_{\beta^{S}}$ & $AUC_{20-50}$ & $AUC_{5-20}$ \\
\midrule\midrule

 \checkmark &  &   & 0.958& 0.658\\
 \cellcolor{Gray}\checkmark & \cellcolor{Gray}\checkmark & \cellcolor{Gray}  & \cellcolor{Gray}0.956 & \cellcolor{Gray}0.653\\
 \checkmark &  & \checkmark  & 0.955& 0.651\\

\bottomrule
\end{tabular} &
\begin{tabular}{cccc|ccc}
\toprule
$\mathcal{E}_{g}$ & $\mathcal{E}_{id}$ & $\mathcal{E}_{d}$ & $\mathcal{E}_{s}$ & $AUC_{20-50}$ & $AUC_{5-20}$ & Time($ms$)\\
\midrule
\midrule
 \checkmark & \checkmark &  &  & 0.958 & 0.658 & 8.02\\
 \cellcolor{Gray}\checkmark & \cellcolor{Gray} & \cellcolor{Gray} & \cellcolor{Gray} & \cellcolor{Gray}0.958 & \cellcolor{Gray}0.657 & \cellcolor{Gray}8.01\\
   & \checkmark &  &  & 0.958 & 0.658 & 7.98\\
 \cellcolor{Gray}\checkmark & \cellcolor{Gray}\checkmark & \cellcolor{Gray}\checkmark & \cellcolor{Gray} & \cellcolor{Gray}0.950 & \cellcolor{Gray}0.644 & \cellcolor{Gray}42.11\\
 \checkmark & \checkmark &  & \checkmark & 0.948 & 0.640 & 42.08\\
\bottomrule
\end{tabular} \\
\end{tabular}
}
\end{center}
\caption{Ablation study on the loss functions of shape-branch (left), and how different constraints of \textit{tailor module}. influence the precision and speed (right).}
\label{tab:ab}
\end{table}

We can see from Tab. \ref{tab:ab} that
$\mathcal{E}_{g}$ and $\mathcal{E}_{id}$ do not improve the precision, but they do affect the hand mesh quality as shown in Fig. \ref{fig:energy}. Also, depth and silhouette constraints cannot improve \textit{tailor module}. This is because they make the energy function more complex and hard to converge. These constraints also bring a heavy overhead to \textit{tailor module}.

\begin{figure}[h]
\begin{center}
\includegraphics[width=0.4\linewidth]{images/energy.eps}
\end{center}
\vspace{-5mm}
  \caption{From left to right are the output of the full \textit{tailor module}, the output of the \textit{tailor module} without unnatural twist constraint, and the output without identity constraint.}
\label{fig:energy}
\vspace{-5mm}
\end{figure}

\section{Conclusion}

In this paper, we propose a novel framework HandTailor for monocular RGB 3D hand recovery, combining a learning-based \textit{hand module} and an optimization-based \textit{tailor module}. We can adapt both perspective projection and weak perspective projection for high precision and in-the-wild scenarios. And the \textit{tailor module} can bring significant improvement for the whole pipeline both qualitatively and quantitatively. In the future, we will try to solve the hand reconstruction task when the hand is holding objects or two hands are interacting.

redpajama_set_name: RedPajamaArXiv


text:
Home | Life & Culture
The Waldheim Scandal |
When Austrians Stopped Calling Themselves Hitler's First Victims
New documentary provides rare look at months leading up to the presidential election of Kurt Waldheim, the former UN secretary-general who conveniently forgot his Nazi past
Judy Maltz
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Kurt Waldheim being prepared for an interview in footage from "The Waldheim Waltz."Credit: Ruth Beckermann filmproduktion
It was the spring of 1986, and many angry people had taken to the streets of Vienna. Some were outraged that a man accused of complicity in Nazi war crimes could become their next president. Others were incensed that anyone would dare try to stop him.
"Who rules the world – the Germans or the Jews?" a supporter of Kurt Waldheim, the former UN secretary-general and leader of the front-running Austrian People's Party, called out at the rally.
"Maybe the Jews?" he taunted the counterdemonstrators and proceeded to answer his own question. "Damn right," he said. "Still. Still."
An elderly man trying to strike up a conversation with another Waldheim supporter in the crowd was ordered to shut up and called a "Jewish swine."
Ruth Beckermann caught it all on camera.
Documentary filmmaker Ruth Beckermann.Credit: Ruth Beckermann filmproduktion
U.S. bans Austrian president for suspected WWII war crimes
In Austria's elections, the fight against anti-Semitism has turned nasty
Rise of Austria's far right seen as proof of failure to confront Nazi past
The Austrian-Jewish filmmaker had been an active member of the small but growing opposition to Waldheim back then, witnessing many ugly street scenes like these. In those days, she recounts, protesters didn't walk around with video cameras, and so she was an oddity. But the demonstrations provided her with a great opportunity to gather footage for a documentary she was working on at the time about Jewish identity in the first generation after the Holocaust.
It never crossed her mind that this footage would ultimately serve as the basis for a film about a presidential campaign that would become a turning point in postwar Austrian history.
"I guess because I lived through it, the idea of making a movie didn't interest me back then," she told Haaretz this week in Tel Aviv.
About five years ago, Beckermann discovered the old black-and-white video footage stashed away in a box in her office. Having not looked at it for so many years, she found the contents shocking.
"All this shouting in the streets and all this anti-Semitism," she says. "I cannot imagine this happening today. Maybe on social media, but definitely not in the main square of the city."
Altogether, she had gathered about two hours of footage, and some of it was used in her film about postwar Jewish identity. It was mainly scenes of rallies and protests in the months leading up to Waldheim's election (including some close-ups of the candidate himself), but also some behind-the-scenes footage of the opposition strategizing their moves. This group of anti-Waldheim activists included, as Beckermann puts it, "socialists, communists, Trotskyites, Jews – and anyone else who didn't agree."
Upon discovering the videos, Beckermann showed them to some young people she knew – Austrians born after Waldheim's presidency who knew little about the era. She was surprised by their response.
"They may not be that familiar with Waldheim, but they are very familiar with populism and politicians who lie about their past – as well as the whole idea of 'us against the others,' which today applies more to migrants than to Jews," she says. "These young people were the ones who encouraged me to make the film."
They had good instincts.
"The Waldheim Waltz," which played this week at the DocAviv film festival in Tel Aviv, won the best original documentary award at this year's Berlin International Film Festival and is scheduled for wide release in Austria and Germany this fall.
Footage of Austria's then-presidential candidate Kurt Waldheim speaking at a rally, from "The Waldheim Waltz."Credit: Ruth Beckermann filmproduktion
The 90-minute film interweaves the video shot by Beckermann with other archival footage, creating a dramatic account of the buildup to the 1986 election – a brief period in history when the eyes of the world were focused on Austria.
It opens with footage from Waldheim's last campaign rally in May 1986, shot by Beckermann herself. In the voice-over, the filmmaker reflects on the scene playing out on screen from the perspective of more than 30 years. "Suddenly I was right in the middle of it all, when Austria's grand delusion of having been the first victim of the Nazis began to crumble," she says. "In the middle of it all – half as protester, half as documentarist."
Waldheim, a former Austrian foreign secretary, served as UN secretary-general for two terms from 1972 to 1981. He had long claimed he fought on the Russian front during World War II until he was injured in 1941 and was then retired from military duty.
Nazi youth organization
A few months before the presidential election, though, an Austrian news magazine published an exposé charging that Waldheim had lied about his past and had, in fact, served with German forces throughout the war and previously belonged to a Nazi youth organization. Further investigations initiated by other media outlets and the World Jewish Congress revealed even more incriminating information: During the years he was supposed to have been out of commission, Waldheim had served as an interpreter and intelligence officer for a German army unit in the Balkans that had brutally murdered Yugoslavian partisans and civilians, and organized the deportation of the Jewish community of Salonika.
Most Austrians were either not convinced or could care less.
Waldheim ultimately won the election in a second round of voting in June 1986 and served as Austria's president for the next six years. An international commission of historians appointed to investigate the allegations against him found no proof that he had personally engaged in war crimes, but ruled that he was indirectly complicit because he had to have known about the atrocities taking place around him and clearly did nothing to stop them. He was snubbed by most of the Western world during the years of his presidency.
The documentary incorporates a BBC interview with Waldheim, in which he angrily bangs his fist on a table when questioned about the newly revealed evidence against him and demands that the journalist sitting across the table "be a little bit more objective" and take note that "there were casualties on both sides."
In an Austrian television interview also used in the film, Waldheim insists he was "very moved" by the tragedy of the Jews during World War II, but reminds his interlocutor that there were also 6 million non-Jews killed in countries under Nazi rule and that the Austrians suffered too.
The contentious presidential race set off a wave of anti-Semitism in Austria, likely further fueled by the aggressive international campaign waged against Waldheim by the World Jewish Congress.
In a televised clip incorporated into the film, Waldheim makes clear he has little fondness for "the Mr. Singers or whatever their names are" trying to dig up information on him – a reference to Israel Singer, the former secretary-general of the WJC.
A scene from "The Waldheim Waltz."Credit: Ruth Beckermann filmproduktion
Waldheim's supporters accused the international Jewish community of targeting the Austrian candidate because he had presided over the United Nations at a time when numerous anti-Israel measures had been adopted – most famously the "Zionism is a form of racism" resolution of 1975.
Among the film's most dramatic scenes is an exchange between the late Tom Lantos – a Democrat from California and the only Holocaust survivor to serve in the U.S. Congress – and Gerhard Waldheim, the candidate's son who was working as a banker in New York at the time.
The exchange took place during a special congressional hearing to investigate Waldheim's past and determine whether he should be barred entry from the United States. The archival footage depicts Lantos mercilessly grilling Waldheim Jr. about his father's World War II memory lapse. "It is not about whether he lied, but about the denial by the highest official in the UN of a central fact of a whole epoch in history," said Lantos, his voice barely able to contain his emotions.
"My father wasn't a man of many words," his son replied, hardly blinking an eye.
The film also captures Beckermann on the other side of the camera for a few seconds. In the countdown to the election, several Austrian officials held a televised briefing defending Waldheim. Beckermann was among seven protesters to infiltrate the live broadcast, carrying with them embarrassing signs raised above the heads of the speakers.
Beckermann was born in 1952 to Jewish parents who settled in Austria after the war. Her mother came from what was then British Mandatory Palestine and her father from the then-Soviet Union. She has more than 15 films to her credit. "The Waldheim Waltz" has already been sold to Channel 8, the Israeli cable station dedicated to broadcasting documentaries.
When she discovered the lost footage five years ago and began toying with the idea of making a film, the world was in a very different place, Beckermann notes. "There was no Donald Trump, and we didn't have the government we have today in Austria," she says. "So even if there are parallels with what is happening today, it wasn't intended."
The timing may be good for the release of the film, she concedes, "but not so much for the world."
Europe Jews


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text:
Q: Combining to tables and sorting by latest latest date I am real beginner to php-mysql and am trying to figure this out.
I have two tables, as shown: a topic table and a conversation table.
I'm trying to merge the tables to:
1) display the titles that belong to a specific category (for example, if category=color, display the titles: 'Color of orange' and 'Color of banana'.)
2) display the date of the last comment made associated with each title (for, example, the latest date for 'Color of orange' is 2009
3) Sort the titles by the latest date - descending
I can manage doing part I, but I'm lost with part 2 and 3. Any help is appreciated.

A: If anyone is interested, this code seems to work for me.
SELECT title, dateM FROM topic JOIN
(SELECT topic_id, MAX(date) as dateM FROM conversation GROUP BY topic_id
) AS c
ON c.topic_id=topic.id
WHERE category=color ORDER by dateM DESC

A: All you need is a join:
SELECT `topic`.`title`, `conversation`.`year`
FROM `conversation`
INNER JOIN `topic` on `topic`.`ID` = `conversation`.`topic_id`

A: You'll use SELECT CASE, JOIN and subquery to achieve that.
EDIT
Lets start from begining. As I don't know your table's names I'll write some fake names. You said you have two tables: one for topics and other for replies. You also mentioned some categories but you didn't specified how it works, so I'll write it as a column of topic's table.
Table T = Topic's table + Table R = Reply's table
Also consider registry_date a TIMESTAMP column where we save the registration date of our rows.
To achieve your order by last change you need to get some info like:

*

*Is there an answer (reply)?

*If so, what's the registration date of
the latest reply?

You can answer both questions by searching for the last reply.
SELECT R.topicID, R.registry_date FROM R GROUP BY R.topicID ORDER BY R.registry_date DESC
That will be your subquery. But as you need it in your ORDER BY query you should JOIN that result with your topic's table.
SELECT T.title, T.category FROM T LEFT JOIN {subquery} AS Rs ON T.ID=Rs.topicID GROUP BY T.ID
It's not ordering yet. Please note that I called our subquery result "Rs".
Now we'll use our CASE. Different from what I wrote earlier, instead of doing SELECt CASE I'll try ORDER BY CASE, alright? That's simple.
First lets mount our CASE query.
CASE
    WHEN Rs.registry_date IS NULL THEN T.registry_date
    ELSE Rs.registry_date
END

Our first conditional checks if there's any answer. If it's empty, we will use the topic's registration date. If it's populated, we will use the reply's registration date. Now we apply that CASE query on our ORDER BY like this:
ORDER BY {CASE} DESC

As you probably want the last change date info we'll need to get it on our SELECT. You can use your CASE query here too.
SELECT T.title, T.category, {CASE} AS `last_change` (...)

Then our query ends up like this:
SELECT
    T.title,
    T.category,
    CASE
        WHEN Rs.registry_date IS NULL THEN T.registry_date
        ELSE Rs.registry_date
    END AS `last_change`
FROM T
LEFT JOIN (
    SELECT
        R.topicID,
        R.registry_date
    FROM R
    GROUP BY R.topicID
    ORDER BY R.registry_date DESC
) AS Rs ON Rs.topicID=T.ID
GROUP BY T.ID
ORDER BY
    CASE
        WHEN Rs.registry_date IS NULL THEN T.registry_date
        ELSE Rs.registry_date
    END DESC

PS: you can improve your own "WHERE" statements here.
Just as you asked, for example, WHERE T.category='color'
SELECT
    T.title,
    T.category,
    CASE
        WHEN Rs.registry_date IS NULL THEN T.registry_date
        ELSE Rs.registry_date
    END AS `last_change`
FROM T
LEFT JOIN (
    SELECT
        R.topicID,
        R.registry_date
    FROM R
    GROUP BY R.topicID
    ORDER BY R.registry_date DESC
) AS Rs ON Rs.topicID=T.ID
WHERE T.category='color'
GROUP BY T.ID
ORDER BY
    CASE
        WHEN Rs.registry_date IS NULL THEN T.registry_date
        ELSE Rs.registry_date
    END DESC

Please let me know if something's missing.

redpajama_set_name: RedPajamaStackExchange


text:
Geac flies with Peregrine
Richard Noone (ARN) 28 November, 2001 10:27
Geac Computer Corporation and Peregrine Systems have signed a global agreement, which will see Geac's Enterprise Solutions division resell Peregrine's employee relationship management applications.
Although it is still "early days" for the partnership in Australia, Geac will offer Peregrine's Get2Connect global trading network to its own customer base, according to Geac spokeswoman Carol Bath. The alliance also includes Peregrine's e-procurement and employee self-service applications, and business relationship management software for collaborative commerce.
Bath said the deal originated out of the US and will take some time before its effects are felt in the Australian market. For the time being, it remains "business as usual", she said.
One sticking point that will receive strong attention is the fact that Geac already has a human resources software package, which Bath said has undergone extensive localisation for the Australian market.
However, Steve Gardner, Peregrine's chairman and CEO, said in a statement: "The combination of our e-procurement solution and our Get2Connect network will be tightly integrated with Geac's proven business management software.
"This is a good opportunity for customers to realise return on investment through improved operational efficiencies in the procurement process, better visibility and cost controls over procured goods, and the competitive advantage of building tighter and more productive relationships between buyers and suppliers."
Peregrine's e-procurement software extends traditional procurement processes by allowing organisations to evaluate the overall cost of owning and managing an asset -- described as the total cost of ownership not simply its initial purchase price.


HUMAN life depends on availability of clean and safe water. United Nations (UN), water requirements per person range from 20 to 50 decent litres per day. Water data indicates almost 50 percent of Tanzania population access safe water.
With that number on the table, it strikes hard observing water sources pollution continuation over time and space across Tanzania.
Hence, World Health Organization (WHO), accounts for 80 percent of developing nations diseases to be water related, it is no brainer that water availability is an imperative factor to work-upon and collective efforts in combating water pollution are to be forged.
National Environmental Statistics Report of 2017 indicates that, our annual rainfall has been lying around 550- 2500mm, while the urban water supply reaching 86 percent of the population, with more than 22 million people served with water in rural areas (2016).
With all those numbers, it takes band of efforts and measures to safeguard the longevity of water provision to all people over space and time.
However, water pollution has been occurring for decades and evidently rivers, lakes, swamps, marshes and other wetlands have been polluted by human economic activities.
Such as chronic mineral processing activities, domestic sewage and industrial, commercial, institutional waste water, but also solid waste materials are being introduced into water sources every day.
United Nations-data on marine pollution show that land-based sources account for 80 percent of marine pollution of which almost 60 to 95 percent of it is of plastic.
Nipe Fagio, a local-environmental NGO based in Dar es Salaam, conducts beachcleaning waste audit assessment after every activity.
Thus plastic materials were among the high quantity of waste elements found on the beach areas during the cleaning campaigns, this sends a very loud signal that is not heeded.
Tanzania has been endowed with an extensive array of fresh water sources, rivers and lakes which cover 7 percent, but the rate of pollution has been higher compared to the sustainability measures.
Evidently, crucial power holders have been raising stakes high on combating water pollution. In September, 2018 President John Pombe Magufuli, intervened a chilling water crisis conflict in Nyamongo, Mara Region where community members and their livestock were affected by water consumed, His excellency, addressed his concern on the toll of dead cattle, people and skin complications, urging National Environmental Management Council to conduct another water quality assessment after the first report was found with flaws.
Thus, His excellency urged transparency to be a factor in addressing the issues, on the other side of the coin, seriousness of conserving is inadequate within responsible bodies.
The Nyamongo waterstrife, rose after prolonged pollution of communities' water sources from mining processes of which contain harmful chemical substance, seeping through the ground affecting the water tables and leaking through open ground other associated water sources.
Deforestation has been an associating shadow culprit behind water source pollution, where Prime Minister, Kassim Majaliwa in 2016 gave strict precautions to water polluters and urged Namanyere residents-Rukwa on preserving Nkasi forest which caters for the entire Nkasi district water demands.
Due to the intensity of the matter, stakes were raised high of which, Prime Minister directed 70 million TSH to be fined and 7 years jail time to the polluters.
Climate change has been a grim-challenge towards rural-dwellers livelihood supply especially water, for irrigation and human use. As rainfall patterns have changed tremendously affecting the regular water supply, forcing women to fetch water far away risking their lives and economies.
Industrial and population water demand over time and space, have multiplied the efforts to provide water and sate both entities demand, hence the operations have not mutually beneficial to the UN Sustainability Goal Number 6 (Clean Water and Sanitation), industries and human activities are polluting water sources like there is another vital substance to access apart from water that can sustain human life.
Due to the fact that fresh water availability is dwindling over time and space, the urgency of protecting fresh water sources is incredibly required.
Disappointingly, still as communities, experts and power holders we have not exercised water sources conservation adequately. Most cities in Tanzania, lack sewage treatment facilities and consequence which catapults discharge of sewage waste into the environment.
Such as Mirongo river-Mwanza channeling human-foulness and other solid waste materials into Lake Victoria. Msimbazi river-Dar es Salaam doing the same and valley-dwellers intensifying pollution during rainy days.
To validate the latter, a study done by Salim Mohammed, University of Dar es Salaam, Institute of Marine on Assessment of water quality and pollution in Tanzania, found out that major cities fail to establish sustainable operational sewer networks to avert water-borne health risks. Mohammed went along and cited that "pollution in Tanzania has no yet reached alarming levels.
However, given the continuing population pressure and industrialization in the country as well as the presence of some hotspots along the coast, necessary steps need to be taken to preclude further deterioration of water quality in the country".
A cross sectoral collective effort approach will be of impeccable tool towards combating water pollution. In realizing industrialised Tanzania, water demands will be higher.
Thus relevant ministries and agencies ought to harness their resources and skills to wage war on water pollution at any cost, placing technology and human-centered-designs in at the fore front. Ministries: Environment, water, health, industry, trade and investment, mining, energy and education to mention the winning team, ought to preclude all water bodies pollution by incorporating the local people within water bodies location, harness their indigenous knowledge to make the conservation sustainable.
Moreover, it is vital to cast efforts in developing water treatment technologies to diminish waste water overload and downplay gray water draining in domestic environments.
Civil Society Organization, have a crucial role to play in addressing water challenges to communities especially by championing youth to be ambassadors of water sources protection.


text:
getreading
How to watch and join the Royal Wedding celebrations in Windsor and on TV
Thousands of people are expected to travel to Windsor for the May wedding
By Khadija Taboada
Prince Harry and Meghan Markle's official engagement photos. Credit: Alexi Lubomirski via Getty
Prince Harry and Meghan Markle's wedding may be low key in comparison to another Royal wedding back in April 2011, but getting involved is still an option.
The bride and groom have handed out an open invitation to members of the public who want to feel part of their big day.
As well as extra trains running to Windsor, visitors will be able to watch their nuptials live on screens being set up around the town.
Food stalls, live entertainment and viewing areas for the carriage procession will also be set up, encouraging participation in the event.
Extra trains will run to Windsor for the Royal wedding
With so much excitement surrounding the nuptials, it's expected that thousands will travel to Windsor, Berkshire on Saturday, May 19.
Cllr Phill Bicknell, cabinet member for highways, transport and Windsor, said: "As a Windsorian I am hugely proud we have the opportunity to welcome the royal wedding of Prince Harry and Ms Meghan Markle to our town.
"We expect large crowds of well-wishers and visitors will line the procession route, eager to catch a glimpse of the newlyweds.
"As a royal town it is part of who we are to play host to international events just like the royal wedding and I look forward to the world's eyes once again turning to Windsor"
The happy couple at The Sunken Gardens in Kensington Palace. Credit: Getty
The town centre will be decorated with bunting and ceremonial banners welcoming the couple who will be making their vows at St George's Chapel, Windsor Castle.
Large screens in Long Walk and Alexandra Gardens will be showing live footage of the wedding and procession.
Visitors who want to catch a glimpse of the couple after they say 'I Do' can place themselves up at viewing areas along the precession route.
Roads including Castle Hill, High Street, Sheet Street, Kings Road, Albert Road and the Long Walk will be open to visitors.
The most popular baby names in Berkshire revealed
The Royal Borough of Windsor and Maidenhead expect the wedding will inspire even more visitors to come to the area, but also warn those planning to attend wedding celebrations to think ahead.
Although no tents are allowed, fans of the royals joining the party should think about arriving early, booking transport and bringing folding chairs if necessary.
How to watch on TV
The ceremony will take place inside St George's Chapel. Credit: PA
Phillip Schofield and ITV News at Ten's Julie Etchingham will present a live broadcast from The Long Walk in Windsor, which is among the roads closed during the royal wedding.
The Royal Wedding will be on air from 9.25am until 3pm, with the presenters joined by a range of guests including friends of Prince Harry and Meghan, as well as friends of the Royal family.
Windsor road closures announced for the Royal wedding
Royal Editor Chris Ship will also be on hand to provide his expertise throughout the day, with guests interview and more specialist segments during the broadcast.
In the evening there will also be a special hour-long Royal Wedding highlights show on ITV3 for those unable to tune in during the day.
Audiences from across the UK will be able to enjoy BBC coverage across radio, TV and online, full details of which are yet to be announced.
Information that has been released includes Claire Balding hosting a live commentary from Windsor Castle on BBC Radio 4.
Coverage of the wedding procession making its way through the town will then continue on 5 live until 2pm.
Sky News is kicking off bright and early with coverage starting at 6am with its Sunrise show being streamed from the castle grounds.
The newest member of the Royal family finally gets a name
Coverage will then continue from 9am, from a make-shift studio in Long Walk, Windsor.
Correspondents will be placed along the procession route, on the castle grounds and at street parties in the couples honour across the country.
The route the carriage procession will take
The #RoyalWedding carriage procession route has been announced by @KensingtonRoyal! Here's what the newly married couple will see in Windsor 🏰💒🍾#HarryandMeghan #MondayMotivation pic.twitter.com/FgQ9sMixeo
— Visit Windsor (@visitwindsor) February 12, 2018
Whether travelling from Wokingham, Bracknell, Reading, Berkshire or further afield there are plenty of options to get to Windsor.
Those driving are able to book parking for £30, there are 6,000 spaces reserved for well wishers.
Click Here for getreading.co.uk news
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HomeServicesIs It Time to Replace Your Storage Tanks?
Storage tanks can store any kind of liquid. It can be the storage container for oil and fuel, chemicals, and even fertilizer. With the sensitivity of these materials, it's no wonder there are rigorous safety guidelines in place. But these storage tanks are not prone to leaks and other signs of wear. At which point do you decide to replace them?
Some chemicals stored in a tank can be corrosive. And while tank fabrication and design often takes this into account, over time rust may still form on the liner or joints of the tank. These signs mean that the storage tank is not able to keep its integrity or that of its contents. Rather than compounding the problem, it's best to replace the tank right away.
The last thing you want is to see signs of leaks in your tank. Above ground tanks will show signs of leaks first on welded joints, which are their weakest spots. A leaking underground storage tank may contaminate soil or ground water. Anywhere there is a break in the tank's construction, a potential leak may occur. You may have the tank repaired by a licensed storage tank repair specialist, but make sure they also reinforce the entire tank. You do not want to fix a leak only to deal with another leak in a different location.
Sometimes it's less expensive and safer to replace a tank right away, even if the damage is minimal. Remember, lives are at risk if the storage tank cannot do its job properly. Have an inspector assess the extent of the damage and ask them if it's wiser to just get a new tank.
When dealing with storage tanks, there is no room for error. Lives may be lost if you do not follow an inspector's recommendations. No amount of money you can save from repairs can bring those lives back.


text:
Among the Witnesses
BBC Radio 3, 17 April 1978 22.25
' Even when I was a child, I knew I could not have a level fight as a girl; hut what was important for all of us was. after all, the same - the tasks that lay ahead of us as human beings '- RIMMA, KAZAKOVA. Secretary of the Moscow Writers' Union
Last year, the poet and novelist Elaine Feinstcin visited Russia. In the second of three programmes on women and poetry in the Soviet Union, she looks at the work of Margarita Aliger. Yunna Morils and Rimma Kazakova with the help of recordings collected during her visit.
Reader FRANCES HOROVITZ Producer FRASER STEEL BBC Manchester
Unknown: Elaine Feinstcin
Unknown: Margarita Aliger.
Unknown: Yunna Morils
Unknown: Rimma Kazakova
Reader: Frances Horovitz
Producer: Fraser Steel
Feedback about Among the Witnesses, BBC Radio 3, 22.25, 17 April 1978
Please leave this link here so we can find the programme you're referring to: http://genome.ch.bbc.co.uk/0b91e6ce384a44f383fb9a9b5ae7aeb6


You'll love this charming 2-story historical home in sought after Irvington neighborhood! Step inside to your spectacular living room with 12 ft vaulted ceilings and wood burning fireplace. Space galore with 4 bedrooms 2 full baths, large fenced-in backyard that leads to a 2 car detached garage. Relax on your three seasons porch or cozy up to the wood burning stove fireplace in the basement with full bath, laundry/utility room and tons of extra storage space!
MLS/BLC # 21612435 is a 4 -bedroom, 2-bath property located at 929 North Bolton Avenue, Indianapolis, IN 46219, in Marion County. This Residential/Condo was built in 1931 and offers 3521 square feet of total space. The current listing status of 929 North Bolton Avenue Indianapolis IN 46219 is "Sold." This property is conveniently located in Irvington, a popular Indianapolis-area neighborhood. 929 North Bolton Avenue Indianapolis IN 46219 is in the Irvington Subdivision. See More Indianapolis homes for sale.
929 North Bolton Avenue, Indianapolis, IN 46219 Property displayed on MSWOODS.COM and listed by CENTURY 21 Scheetz. The BLC® listing information is provided by the Metropolitan Indianapolis Board of REALTORS® from a copyrighted compilation of listings. The compilation of listings and each individual listing are © 2019 Metropolitan Indianapolis Board of REALTORS® All Rights Reserved. The information provided is for consumers' personal, non-commercial use and may not be used for any purpose other than to identify prospective properties consumers may be interested in purchasing. All properties are subject to prior sale or withdrawal. All information provided on 929 North Bolton Avenue, Indianapolis, IN 46219 (and all other homes for sale in Indianapolis) is deemed reliable but is not guaranteed accurate, and should be independently verified.
I would like to see the house at 929 North Bolton Avenue, Indianapolis, IN 46219 at the following date and time.


Buddha began his meditation practice applying what existed at the time Veda (Hindu) meditation practice. He did the concentration breathing meditation ( known as anapanasati at Goenka retreat ) and attained the 8 jhanas but found out that the purity of mind was fleeting as soon as he came out of the meditation.
Then, he remembered how he meditated as a child and easily attained jhana. He decided to meditate like that again and became enlightened. His breathing meditation is described in the anapanasati sutra, which makes NO REFERENCE to rising and falling of stomach or noticing air at the nostril. Simply, be mindful of breathing and breath in a way that it relaxes and calms your body and mind. Be aware of your field of awareness. This method contains introspection awareness, so it is samatha and vipassana in tandem.
There is no meditation method used by Buddha for his enlightenment that is samatha first, vipassana second or vipassana first, samatha second or vipassana only.
1000 years later, Buddhaghosa, who didn't have knowledge of Buddha's meditation practice, wrote commentaries called Visuddhimagga or Path of Purification, heavily relied on my Theraveda teachers. He inserted the vary meditation practice that Buddha abandoned and called it anapanasati. He inserted samatha and vipassana as separate meditation practices.
Visuddhimagga emphasizes strenuous meditation practice and pain tolerance. The jhanas have 8 levels.
Buddha emphasizes relaxed meditation practice and middle effort. The jhanas have 4 levels.
Even when you are talking about jhanas, you have to say absorption (Visuddhimagga) jhana or sutta (Buddha) jhana.
Unfortunately, the commentary not only did not elaborate Buddha's teaching but distorting it making meditation strenuous and difficult.
Goenka and Mahasi retreats are all based on Visuddhimagga. They are not the original teaching of Buddha.
You can follow either track. My personal direct experience is that Buddha's meditation practice is far superior. It releases hindrance while absorption method suppresses hindrance such that they are released when you are not meditating. Buddha's path reaches jhana so much easier. Relaxing is letting go of hindrance. One can reach enlightenment faster.
I hope this clarifies a lot of confusion surrounding Theraveda Buddhism. You don't have to believe in me. You can research on your own. You can ask yourself do you get he aches and tightness of heads which many have complained about the anapanasati taught at Theraveda school of Buddhism.
Buddha's teaching is neither Theraveda, Zen, Tibetan. It simply is the original sutta established by the first council.
Then, he remembered how he meditated as a child and easily attained jhana. He decided to meditate like that again and became enlightened.
There is really no relationship between jhana & the Buddha's enlightenment. Therefore, when the Buddha remembered how he attained jhana as a child, it was probably about 'how' he attained jhana rather than jhana itself.
His breathing meditation is described in the anapanasati sutra, which makes NO REFERENCE to rising and falling of stomach or noticing air at the nostril. Simply, be mindful of breathing and breath in a way that it relaxes and calms your body and mind. Be aware of your field of awareness. This method contains introspection awareness, so it is samatha and vipassana in tandem.
The sutta does not state to "be mindful of breathing". It states the meditator 'observes' ('anupassi') the breathing by using mindfulness ('sati') to abandon covetousness & distress.
This is not true. The Anapanasati Sutta uses the word 'calming' in the 4th and 8th step, which means 'calming' is a predominant quality at the beginning stages (even though there is also vipassana at the beginning stages). The later stages are 100% vipassana.
Sure. Buddhists have been criticising Buddhaghosa for a long time. This is not anything new.
Visuddhimagga emphasizes strenuous meditation practice and pain tolerance. The jhanas have 8 levels. Buddha emphasizes relaxed meditation practice and middle effort. The jhanas have 4 levels.
Buddha also refers to 8 jhanas. The word the Buddha used for the method to attain jhana is 'letting go' ('vossagga') rather than 'relaxation'. Refer to SN 48.10 and the last paragraphs of the Anapanasati Sutta, often translated as "relinquishment'.
For example, if the idea exists that "I am relaxing", this is not complete 'letting go' or 'relinquishment'.
Really? Please quote specific teachings to prove this.
Absorption (jhana) develop from 'letting go' does not suppress hindrances. In fact, using suppression probably cannot reach true jhana.
OK... thanks for clarifying that (even though I worked this out about 30 years ago after about six weeks of meditation).
Indeed. It is Buddha's teaching of letting go (vossagga) rather than Vimalaramsi's teaching about 'relaxtion'. Well spoken.


text:
KASABIAN interview – Evening Standard, 31 March 2017
Posted in Interviews, Kasabian
Having previously written music inspired by velociraptors, internet surveillance and Vlad the Impaler, and named their band after a member of the Manson Family, Kasabian have done something really unexpected as they prepare to release their sixth album: they've come up with what they say is their first ever love song.
Put Your Life On It closes the Leicester quartet's new album, released next month, which is called For Crying Out Loud. It's a strumming, slow-building singalong, a bit glam rock, a bit Hey Jude, with a chorus that gets bigger and bigger. "I wanna say I love you/Won't let you down," sings Tom Meighan, over and over. If previously you have thought Kasabian's music was a bit ridiculous, a bit messy, songs for footie fans to spill their pints to, just try and resist this one.
"The Sex Pistols never had a love song, so I suppose I always thought I wanted to stay away from that," explains guitarist and songwriter Serge Pizzorno, 36, who married his long-term girlfriend Amy White last July. "Then I just wrote this song about my wife. And rather than hold back and think: 'I can't say that!' I said it exactly how it is. I can already see people react to it when we play it live."
Frontman Meighan, 36, who often comes across less as Pizzorno's bandmate and more his biggest fan, is characteristically effusive about it. "It's a massive anthem, isn't it? It makes your hair stand up. I'm on the edge of crying, basically, it's that powerful," he tells me. "It's so simple, but sometimes simple songs are the best, aren't they?"
"Simple" has been the buzzword throughout the process this time around. Pizzorno has been the sole writer since forming the band with his schoolfriends in the late Nineties (bassist Chris Edwards and drummer Ian Matthews, a later addition, complete the line-up) and these days makes the music in the home studio he calls The Sergery on the outskirts of Leicester. He took a year to write the songs on Kasabian's last album, 48:13, so this time set himself the challenge of writing everything in six weeks.
"You might think: 'I'm an artist. You can't tell me when and where I can be creative,' but I got really excited about trying to do it so quickly," he says. "I also put restrictions on other things. I took this sort of Motown approach: the first eight bars have to draw you in, the chorus has to come in the right place, everything has to be beautifully crafted. I didn't allow my psychedelic section, where the song goes off on a completely different tangent to freak people out. I wasn't allowed to use my usual tricks so there was no production, no loops, no electronics. I just wrote on piano and acoustic guitar."
The result is more of a classic rock and roll sound compared to 48:13's oddball romping. The danceable grooves of songs such as the new single, You're in Love With a Psycho, and the eight-minute centrepiece, Are You Looking for Action?, were inspired by Blondie, ESG and Talking Heads rather than the Nineties rave and Britpop on which the band were raised. Meighan is particularly thrilled by the end result: "Screw the interludes and all the breakdowns. It's Sergio at his best, just writing great songs with great melodies. I love that he's gone back to our roots: massive rock and roll pop songs. The songs are joyous, do you know what I mean? They're like a celebration."
Kasabian had good reason to celebrate when the work on this album began. In June 2014, just after 48:13 was released, they joined the exclusive club of Glastonbury Pyramid Stage headliners. "That was like completing Mario World, or getting to the end boss on Double Dragon," says Pizzorno. "Coming off stage after that, rather than feeling, 'Ah, we've done it now,' I sort of felt, 'We've done it, and now I can do anything.' Nothing's daunting any more."
They toured the world in 2015, then Pizzorno had his six week writing rush at the beginning of 2016 and came up with 10 of the new album's 12 songs. There was no resting on laurels. "You wake up in the morning, no matter how many great songs you've written, and you go: 'Today's the day I'm gonna write that tune.' You always need one more," he says.
The summer months were triumphant: a surprise appearance playing four songs at the champions' parade of their soaring hometown football club, Leicester City, followed a fortnight later by two giant gigs in Leicester's King Power Stadium. "That was off the scale. We will never, ever, see that again in our lifetime," says Meighan. Then Pizzorno got married and spent three months "being human for a bit" with his wife and their two sons, aged six and three. After that, the last two songs came to him and the band started recording the music that's almost with us.
For Meighan, however, 2016 was far less celebratory. In his first magazine cover interview for the new campaign, he broke down in tears, alluded to a lifestyle of damaging excess and revealed that he is no longer living with his girlfriend and their young daughter. The revelation was all over the tabloids. He fails to show up to our scheduled face-to-face chat, leaving quiet, affable Pizzorno to talk to me alone in posh central London members' club Home House. But a few days later he comes to the phone on time and sounding chipper. "I don't want to go into detail about it. Of course I didn't have a great year, of course it was difficult, but I found myself, and found a way to love myself again and be happy," he says, talking as usual at 100 miles an hour, narrating his turning over of sausages on the grill while he's speaking.
"I had to look at my demons and kill them off otherwise it could have led down a very dark path. But I had good support around me, friends and family who care about me. So I'm back now, mate. It's one of those things in life, you just have to get on with it, don't you? ANYWAY," he says, loudly emphasising the word to enforce a change of subject, "I'm alive now, and feeling very good basically."
I know from past experience that Meighan is a tricky interviewee at the best of times, with probably the shortest attention span of any adult I've ever met. "Ask him about crisps," is Pizzorno's suggestion for ensuring a longer conversation. "He's an afficionado." The singer is clearly anxious that his personal problems don't become the story when Kasabian are back with their best music in some time.
"We've gone through bad times, gone through everything, and we're a proper family, our band," he says. "We've been through so much together and nothing's cracked. We've grown up together, we're all parents now, and everyone's in a good place. It's a lovely thing."
April 18-20, O2 Forum Kentish Town, NW5 (0844 847 2405, o2forumkentishtown.co.uk)
For Crying Out Loud is released on April 28 on Columbia.
MAVERICK SABRE – Evening Standard 27 Jan 2012
STEFFLON DON interview – Evening Standard, 23 Feb 2018
EDWARD SHARPE AND THE MAGNETIC ZEROS interview – Evening Standard, 12 JUly 2013
CARO EMERALD interview – Evening Standard, 5 July 2013
Tagged 2017, Evening Standard, Kasabian
JAMIROQUAI, Roundhouse – Evening Standard, 3 April 2017
BRUNO MARS interview – Evening Standard, 21 April 2017


text:
Home Tags Owen Hart
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WWE Timeline To Look At Bret vs. Owen Hart Feud, Top 25 WWE Instagram...
News Ryan Clark - August 9, 2020
The Mahoning Drive-In in Lehighton, Pennsylvania will be running some wrestling-themed movies next Friday and Saturday. They'll be airing Bodyslam: The Movie and Ready...
New Owen Hart Documentary Announced, Never Before Seen Footage
News Brandon Ewing - June 19, 2020
Kaleidoscope Film Distribution announced that they are working on a new Owen Hart documentary called Owen, which will feature never-before-seen footage, according to a...
Chris Jericho Talks Owen Hart, Owen Not Going Into The WWE Hall of Fame,...
News Brandon Ewing - June 9, 2020
Chris Jericho was interviewed by Sportskeeda ahead of the UK Premiere for "Dark Side of the Ring". Jericho discusses Owen Hart and why Owen...
Edge Looks Back at 1998 Match With Owen Hart
News Jon Fuentes - May 27, 2020
WWE Hall Of Famer Edge was recently interviewed by Inside The Ropes to talk about several professional wrestling topics. Here are the highlights: His match with...
Arn Anderson Says Loss of Owen Hart Was One of the 'Darkest Days in...
Professional wrestling legend Arn Anderson took to his podcast, "The Arn Show," to talk about several professional wrestling topics. Here are the highlights: Learning what happened...
Edge Shares a Memory of Wrestling Owen Hart, Talks the Night Owen Died
News Ryan Clark - May 24, 2020
During a recent interview with Inside the Ropes, WWE Hall of Famer Edge commented on working with Owen Hart, his passing at the Over...
Bonus Clip From Dark Side of the Ring Shows Owen Hart's Infamous Ribs
News Brandon Ewing - May 21, 2020
VICE TV has released a special bonus clip from Owen Hart's documentary, which aired as the latest episode of "Dark Side of the Ring"...
Report – Max Mini Was Originally Set to Be Attached to Owen Hart
An investigative file into the death of Owen Hart has surfaced and it says Max Mini was supposed to be attached to Owen Hart...
CM Punk Praises Owen Hart's Wife & Children Following "Dark Side of the Ring"...
CM Punk took to Twitter to comment on "The Final Days of Owen Hart," the Season 2 finale for the Dark Side of the...
Owen Hart's Son Won't Let WWE Induct his Father Into Hall of Fame
News Andrew Ravens - May 20, 2020
Owen Hart's son Oje said on last night's episode of Dark Side of the Ring (transcript via Fightful) that he won't allow the WWE...
Martha Hart Comments On Why She Doesn't Want Owen In The Hall of Fame
Martha Hart, the widow of the late "King of Harts" Owen Hart spoke with Forbes magazine, as she explained to them why she doesn't...
Martha Hart Reveals How Owen Hart Was Affected By the Montreal Screwjob, More
During the latest edition of "Talk is Jericho", Owen Hart's widow, Martha Hart, commented on Owen being upset by the Montreal Screwjob, and more....
Owen Hart's Widow Martha Filmed for 'Dark Side Of The Ring' Season 2
News Kyle Dunning - January 18, 2020
The Facebook account for the Owen Hart Foundation revealed that Dr. Martha Hart, the widow of late former WWE Superstar Owen Hart, was filmed...
The Best & Worst WWE King of the Ring Winners in History
Articles Kyle Dunning - August 21, 2019
Hello folks! With its return already underway, I believe it's the right time to take us on a journey. However, instead of ranking every...
EXCLUSIVE: Davey Boy Smith Jr Comments on His Father and Uncle Owen Not Being...
News Robert DeFelice - May 24, 2019
During my exclusive interview with Davey Boy Smith Jr., we discuss why there are so many key members of the Hart family legacy that...
Several Wrestlers Remember Owen Hart
Today (May 23, 2019) marks the 20th anniversary of Owen Hart passing away after falling from the ceiling of the Kemper Arena in Kansas...
Starrcast Adds Owen Hart Remembrance Panel
Due to having to pull The Roast of Ric Flair from the Starrcast convention, Conrad Thompson and the Starrcast team have announced a special...
Owen Hart Audio Documentary To Be Released
News Vincent Dipietro - May 16, 2019
John Pollock of Post Wrestling has been working on a audio documentary covering Owen Hart and his tragic accident. The documentary is scheduled to be released...
Bruce Prichard Claims Bret Hart Wanted to Beat Owen at WrestleMania 10
News Ryan Clark - March 23, 2019
During the latest edition of his "Something to Wrestle" podcast with Conrad Thompson, WWE creative team writer Bruce Prichard commented on Bret Hart vs....
He is a professional wrestling personality perhaps best known as a manager and producer for World Wrestling Entertainment (WWE, formerly the World Wrestling Federation). As ...