期刊
IETE JOURNAL OF RESEARCH
卷 63, 期 2, 页码 160-171出版社
TAYLOR & FRANCIS LTD
DOI: 10.1080/03772063.2016.1242383
关键词
Action-code classifier (AAC); Action units (AU); Human action recognition (HAR); Spatio-temporal body parts movement (STBPM); Trajectory analysis (TA); Video analysis
资金
- DST, Ministry of Science and Technology, Government of India through INSPIRE project [IF10163]
- Science and Engineering Research Board
In this work, we propose a novel human action recognition (HAR) technique for human silhouette sequence based on spatio-temporal body parts movement (STBPM) and action-code classification (ACC). STBPM feature is designed to accumulate the signature of the activity of several body parts to accomplish any action. ACC is a code-based classifier for HAR, which needs no training and the codes of any action is created by analyzing the STBPM features. The proposed approach is view independent except the top view and scale invariant. The experimental results on publicly available Weizmann, MuHVAi, and IXMAS datasets clearly show that our proposed technique outperforms the related research works in terms of accuracy in the human action detection.
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