Motion segment decomposition of RGB-D sequences for human behavior understanding

@article{Devanne2017MotionSD,
  title={Motion segment decomposition of RGB-D sequences for human behavior understanding},
  author={Maxime Devanne and Stefano Berretti and Pietro Pala and Hazem Wannous and Mohamed Daoudi and Alberto Del Bimbo},
  journal={Pattern Recognition},
  year={2017},
  volume={61},
  pages={222-233}
}
In this paper, we propose a framework for analyzing and understanding human behavior from depth videos. The proposed solution first employs shape analysis of the human pose across time to decompose the full motion into short temporal segments representing elementary motions. Then, each segment is characterized by human motion and depth appearance around hand joints to describe the change in pose of the body and the interaction with objects. Finally, the sequence of temporal segments is modeled… CONTINUE READING
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