You are provided with the abstract of a scientific paper and the abstracts of the papers it references. Your task is to write a Related Work section for the main paper. This section should concisely summarize and integrate the key points from the cited abstracts, reflecting how they relate to the main paper's contributions and context. In your summary, use numerical citation markers like [1], [2], etc., to refer to the corresponding papers.

Main Abstract:
We present a practical approach to capturing ear-to-ear face models comprising both 3D meshes and intrinsic textures (i.e. diffuse and specular albedo). Our approach is a hybrid of geometric and photometric methods and requires no geometric calibration. Photometric measurements made in a lightstage are used to estimate view dependent high resolution normal maps. We overcome the problem of having a single photometric viewpoint by capturing in multiple poses. We use uncalibrated multiview stereo to estimate a coarse base mesh to which the photometric views are registered. We propose a novel approach to robustly stitching surface normal and intrinsic texture data into a seamless, complete and highly detailed face model. The resulting relightable models provide photorealistic renderings in any view.

Cited Abstract(s):
[1]: This paper proposes a novel approach to non-rigid, markerless motion capture from synchronized video streams acquired by calibrated cameras. The instantaneous geometry of the observed scene is represented by a polyhedral mesh with fixed topology. The initial mesh is constructed in the first frame using the publicly available PMVS software for multi-view stereo [7]. Its deformation is captured by tracking its vertices over time, using two optimization processes at each frame: a local one using a rigid motion model in the neighborhood of each vertex, and a global one using a regularized nonrigid model for the whole mesh. Qualitative and quantitative experiments using seven real datasets show that our algorithm effectively handles complex nonrigid motions and severe occlusions.

[2]: The Viewport immersive teleconferencing system reconstructs sparse 3D representations for each user and applies virtual seating to maintain the same seating geometry as face-to-face meetings. In this article, we propose a fully distributed immersive teleconferencing system that assumes there is only one user at each station during the conference. Such a system would allow users to conduct meetings in their own offices for greatest convenience. Compared with group conferencing systems, fully distributed systems let us render the light and sound fields from a single user's viewpoint at each site, which demands less of the system hardware.

[3]:
Geometric methods. Multiview shape estimation methods such as binocular stereo, structure-from-motion and multiview stereo have been applied quite successfully to the problem of face shape estimation. The key problem in this context is establishing correspondence between views over apparently-featureless regions of the face such as the cheeks and forehead. One solution to this problem is to either paint [1] or project [2] a pattern onto the face that provides matchable features. An alternative passive approach is to use very high resolution images in which fine scale features such as freckles, wrinkles and skin pores are resolved. These provide ideal features for robust matching. Finally, methods such as shape-from-silhouette do not rely on feature matching and can hence be applied to faces [3] even when small features are not visible.