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A Novel Approach for Human Action Recognition from Silhouette Images
Published in Taylor and Francis Ltd
Volume: 63
Issue: 2
Pages: 160 - 171
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. © 2017 IETE.
About the journal
JournalData powered by TypesetIETE Journal of Research
PublisherData powered by TypesetTaylor and Francis Ltd
Open AccessYes