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Erschienen in:
2009 | OriginalPaper | Buchkapitel
Towards Real-Time Human Action Recognition
verfasst von : Bhaskar Chakraborty, Andrew D. Bagdanov, Jordi Gonzàlez
Erschienen in: Pattern Recognition and Image Analysis
Verlag: Springer Berlin Heidelberg
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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.