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Title

Human Action Recognition Using Deep Data: A Fine-Grained Study

Author

D. Surendra Rao,Sudharsana Rao Potturua, Bhagyaraju. V

Citation

Vol. 22  No. 6  pp. 97-108

Abstract

The video-assisted human action recognition [1] field is one of the most active ones in computer vision research. Since the depth data [2] obtained by Kinect cameras has more benefits than traditional RGB data, research on human action detection has recently increased because of the Kinect camera. We conducted a systematic study of strategies for recognizing human activity based on deep data in this article. All methods are grouped into deep map tactics and skeleton tactics. A comparison of some of the more traditional strategies is also covered. We then examined the specifics of different depth behavior databases and provided a straightforward distinction between them. We address the advantages and disadvantages of depth and skeleton-based techniques in this discussion.

Keywords

Depth, action recognition, depth maps, skeleton, feature extraction, and classification.

URL

http://paper.ijcsns.org/07_book/202206/20220616.pdf