NDLI: Multi-feature consultation model for human action recognition in depth video sequence

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Multi-feature consultation model for human action recognition in depth video sequence

Content Provider	IET Digital Library
Author	Liu, Xueping Li, Yibo Li, Xiaoming Tian, Can Yang, Yueqi
Abstract	In the field of computer vision research, the research on human action recognition of depth video sequence is an important research direction. Herein, considering the characteristics of temporal and spatial depth video sequence, the authors propose a framework of the consultation model of several action sequence features to solve the classification problem in-depth video sequence. According to the characteristics of the 3D human action space, a variety of action sequence feature data is obtained, and then these data is projected to three coordinate planes, the acquired fusion features are used to train the consultation model, and finally the model is validated through the data. The authors have achieved good results by comparing the two publicly available datasets with the other methods. Experimental results demonstrate that the model performs well in existing identification methods.
Starting Page	1498
Ending Page	1502
Page Count	5
Volume Number	2018
e-ISSN	20513305
Issue Number	Issue 16, Nov (2018)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/joe/2018/16
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/joe.2018.8301
Journal	The Journal of Engineering
Publisher	The Institution of Engineering and Technology
Publisher Date	2018-08-16
Access Restriction	Open
Rights License	Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/)
Subject Keyword	3D Human Action Space Acquired Fusion Features Action Sequence Feature Data Classification Problem In-depth Video Sequence Computer Vision Computer Vision And Image Processing Technique Computer Vision Research Feature Extraction Human Action Recognition Human Computer Interaction Image Motion Analysis Image Sequence Multifeature Consultation Model Optical, Image And Video Signal Processing Spatial Depth Video Sequence Temporal Depth Video Sequence Three Coordinate Plane User InterFace Video Signal Processing
Content Type	Text
Resource Type	Article

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