Human Behavior Recognition Based on Motion Decomposition

Shao Ping Zhu; Yu Hua Chen

doi:10.4028/www.scientific.net/AMR.945-949.1780

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 945-949Human Behavior Recognition Based on Motion...

Human Behavior Recognition Based on Motion Decomposition

Abstract:

Human behavior recognition is an active research field in computer vision and image processing. A novel method is proposed for human behavior recognition in video image sequences. First of all, a video sequence is represented by extracting space-time interest points. Then Human behavior is represented by activities through Motion Decomposition. The activity comprises labeled bags that are composed of unlabeled instances comprising to action. Final labeled activities are used to train a strong classifier which is used to predict the labels of unseen behavior bags. Experimental results show the effectiveness of the proposed method in comparison with other related works in the literature and can also tolerate noise and interference conditions.

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Periodical:

Advanced Materials Research (Volumes 945-949)

Pages:

1780-1783

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.945-949.1780

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Online since:

June 2014

Authors:

Shao Ping Zhu, Yu Hua Chen

Keywords:

BAG, Behavior Recognition, Multiple Instance Learning

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