Journal
IETE JOURNAL OF RESEARCH
Volume 63, Issue 2, Pages 160-171Publisher
TAYLOR & FRANCIS LTD
DOI: 10.1080/03772063.2016.1242383
Keywords
Action-code classifier (AAC); Action units (AU); Human action recognition (HAR); Spatio-temporal body parts movement (STBPM); Trajectory analysis (TA); Video analysis
Funding
- DST, Ministry of Science and Technology, Government of India through INSPIRE project [IF10163]
- Science and Engineering Research Board
Ask authors/readers for more resources
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.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available