PT Unknown
AU Bhaskar Chakraborty
   Andrew Bagdanov
   Jordi Gonzalez
TI Towards Real-Time Human Action Recognition
BT 4th Iberian Conference on Pattern Recognition and Image Analysis
PY 2009
VL 5524
DI 10.1007/978-3-642-02172-5_55
AB This work presents a novel approach to human detection based action-recognition in real-time. To realize this goal our method first detects humans in different poses using a correlation-based approach. Recognition of actions is done afterward based on the change of the angular values subtended by various body parts. Real-time human detection and action recognition are very challenging, and most state-of-the-art approaches employ complex feature extraction and classification techniques, which ultimately becomes a handicap for real-time recognition. Our correlation-based method, on the other hand, is computationally efficient and uses very simple gradient-based features. For action recognition angular features of body parts are extracted using a skeleton technique. Results for action recognition are comparable with the present state-of-the-art.
ER