Automatically Determining Dominant Motions in Crowded Scenes by Clustering Partial Feature Trajectories

@article{Cheriyadat2007AutomaticallyDD,
  title={Automatically Determining Dominant Motions in Crowded Scenes by Clustering Partial Feature Trajectories},
  author={Anil M. Cheriyadat and Richard J. Radke},
  journal={2007 First ACM/IEEE International Conference on Distributed Smart Cameras},
  year={2007},
  pages={52-58}
}
We present a system for automatically identifying dominant motions in a crowded scene. Accurately tracking individual objects in such scenes is difficult due to inter-and intra-object occlusions that cannot be easily resolved. Our approach begins by independently tracking low-level features using optical flow. While many of the feature point tracks are unreliable, we show that they can be clustered into dominant motions using a distance measure for feature trajectories based on longest common… CONTINUE READING
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