You are provided with a research question, keyphrases about the question, a description of candidate datasets and dataset options. Read the description of popular datasets provided below and select the ones that can be used to validate the following research question. Use your knowledge of machine learning datasets to make the best judgement.
Your response should be formatted as a `json` array. For instance, for the query "Semi supervised image classification", a sample response might be: ["CIFAR-10", "CIFAR-100"]. Do not include any extra text in the response other than the answer array.

Query: A Siamese network with online weight updating and a Bayesian verification model for visual object tracking.

Keyphrases: visual object tracking video

Dataset description:
MOT17: The Multiple Object Tracking 17 (MOT17) dataset is a dataset for multiple object tracking. Similar to its previous version MOT16, this challenge contains seven different indoor and outdoor scenes of public places with pedestrians as the objects of interest.
TrackingNet: TrackingNet is a large-scale tracking dataset consisting of videos in the wild. It has a total of 30,643 videos split into 30,132 training videos and 511 testing videos, with an average of 470,9 frames.
MOT15: MOT2015 is a dataset for multiple object tracking. It contains 11 different indoor and outdoor scenes of public places with pedestrians as the objects of interest, where camera motion, camera angle and imaging condition vary greatly.
Syn2Real: Syn2Real, a synthetic-to-real visual domain adaptation benchmark meant to encourage further development of robust domain transfer methods. The goal is to train a model on a synthetic "source" domain and then update it so that its performance improves on a real "target" domain, without using any target annotations.
VOT2016: VOT2016 is a video dataset for visual object tracking. It contains 60 video clips and 21,646 corresponding ground truth maps with pixel-wise annotation of salient objects.
OTB: Object Tracking Benchmark (OTB) is a visual tracking benchmark that is widely used to evaluate the performance of a visual tracking algorithm. The dataset contains a total of 100 sequences and each is annotated frame-by-frame with bounding boxes and 11 challenge attributes.

Options:- A: MOT17  B: TrackingNet  C: MOT15  D: Syn2Real  E: VOT2016  F: OTB
["VOT2016", "OTB"]