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Extraction of Human Activities as Action Sequences using pLSA and Prefix Span
Takuya TONARU,Tetsuya TAKIGUCHI,Yasuo ARIKI 보안공학연구지원센터 2009 International Journal of Hybrid Information Techno Vol.2 No.1
In this paper, we propose a framework for recognizing human activities in our daily life. Since a human activity is represented as a sequence of actions, the actions are recognized from videos and then the frequently-occurring human activities can be extracted from them. We show the experimental results applied to the data taken in a deskwork environment to demonstrate the performance of the proposed framework. The experimental results were as follows: 86.0% averaged recall rate and 78.3% averaged precision rate were obtained in extracting human activities.