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

The Journal of Engineering

Xueping Liu¹  Xiaoming Li²  Yueqi Yang³  Can Tian⁴  Yibo Li⁵ 

[1] College of Automation Engineering , Nanjing University of Aeronautics and Astronautics , Nanjing , People'College of Automation Engineering , Shenyang Aerospace University , Shenyang , People'Faculty of Aerospace Engineering , Shenyang Aerospace University , Shenyang , People'Institute of Information Systems Engineering , Concordia University , Montreal , Canada;s Republic of China

关键词: human action recognition;    classification problem in-depth video sequence;    acquired fusion features;    temporal depth video sequence;    3D human action space;    three coordinate planes;    spatial depth video sequence;    action sequence feature data;    computer vision research;    multifeature consultation model;   

DOI  :  10.1049/joe.2018.8301

学科分类：工程和技术（综合）

来源: IET

【 摘 要 】

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.

【 授权许可】

CC BY