Human action recognition via skeletal and depth based feature fusion

@inproceedings{Li2016HumanAR,
  title={Human action recognition via skeletal and depth based feature fusion},
  author={Meng Li and Howard Leung and Hubert P. H. Shum},
  booktitle={MIG},
  year={2016}
}
This paper addresses the problem of recognizing human actions captured with depth cameras. Human action recognition is a challenging task as the articulated action data is high dimensional in both spatial and temporal domains. An effective approach to handle this complexity is to divide human body into different body parts according to human skeletal joint positions, and performs recognition based on these part-based feature descriptors. Since different types of features could share some… CONTINUE READING