Robust unsupervised motion pattern inference from video and applications

@article{Zhao2011RobustUM,
  title={Robust unsupervised motion pattern inference from video and applications},
  author={Xuemei Zhao and G{\'e}rard G. Medioni},
  journal={2011 International Conference on Computer Vision},
  year={2011},
  pages={715-722}
}
We propose an unsupervised learning framework to infer motion patterns in videos and in turn use them to improve tracking of moving objects in sequences from static cameras. Based on tracklets, we use a manifold learning method Tensor Voting to infer the local geometric structures in (x, y) space, and embed tracklet points into (x, y, θ) space, where θ represents motion direction. In this space, points automatically form intrinsic manifold structures, each of which corresponds to a motion… CONTINUE READING

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