The performance of human motion classification and recognition systems is highly dependent on the distinctiveness and robustness of the feature descriptor. In this paper, a new descriptor containing motion, shape and spatial layout information is proposed, therefore it is more effective for action modeling and is suitable for detecting and recognizing a variety of actions. Experiments show that the proposed descriptor outperforms other existing methods, such as Moment Invariants and Histogram of Oriented Gradients, on recognizing human motions in an indoor environment with a stationary camera.
|Publication status||Published - Jul 2010|
|Event||CIVR 2010 - ACM International Conference on Image and Video Retrieval - Xi'an, China|
Duration: 1 Jul 2010 → …
|Conference||CIVR 2010 - ACM International Conference on Image and Video Retrieval|
|Period||1/07/10 → …|