Human Action Recognition Using RGB-D Image Features
TANG Chao1, WANG Wenjian2, ZHANG Chen1, PENG Hua3, LI Wei4
1.School of Artificial Intelligence and Big Data, Hefei University, Hefei 230601; 2.School of Computer and Information Technology, Shanxi University, Taiyuan 030006; 3.Department of Computer Science and Engineering, Shaoxing University, Shaoxing 312000; 4.School of Computer and Information Engineering, Xiamen University of Technology, Xiamen 361024
Abstract：Since the existing multi-modal feature fusion methods cannot measure the contribution of different features effectively, a human action recognition method based on RGB-depth image features is proposed. Firstly, the histogram of oriented gradient feature based on RGB modal information, the space-time interest points feature based on depth modal information, and the joints relative position feature based on joints modal information are acquired to express human actions, respectively. Then, nearest neighbor classifiers with different distance measurement formulas are utilized to classify prediction samples expressed by the three modal features. The experimental results on public datasets show that the proposed method is simple, fast and efficient.
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2019, Vol. 32 
