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Action Recognition Based on Hierarchical Model

In: The 19th International Conference on Industrial Engineering and Engineering Management

Author

Listed:
  • Yang-yang Wang

    (Shenyang Aerospace University)

  • Yang Liu

    (Shenyang Aerospace University)

  • Jin Xu

    (Shenyang Aerospace University)

Abstract

The feature representation of human actions is one of the important factors which influence the recognition accuracy of actions. Usually the recognition accuracy is higher, when the feature simultaneously includes both appearance and motion information. However the dimensions of the feature space is high, and this leads to high computational cost. To overcome this problem, we propose a hierarchical model for action recognition. In the first hierarchy, we adopt box features to divide the actions into two classes, according to whether or not legs are all almost stayed in a static place. In the second hierarchy, we construct different structure of motion feature descriptors to represent different kinds of actions, and use nearest neighbor classifier to obtain the final classification results. Experiments on the Weizmann dataset demonstrate the effectiveness of the proposed method.

Suggested Citation

  • Yang-yang Wang & Yang Liu & Jin Xu, 2013. "Action Recognition Based on Hierarchical Model," Springer Books, in: Ershi Qi & Jiang Shen & Runliang Dou (ed.), The 19th International Conference on Industrial Engineering and Engineering Management, edition 127, chapter 0, pages 93-100, Springer.
    • Handle: RePEc:spr:sprchp:978-3-642-38391-5_10
    DOI: 10.1007/978-3-642-38391-5_10
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