Human Behavior Recognition Based On CNN

Qing YE, Jun DENG, Yong-mei ZHANG, Wen-bo HUANG

Abstract


The technology of human behavior recognition is a cutting-edge topic which covers many areas-including computer vision, pattern recognition and artificial intelligence, and it have been widely used in areas such as commercial products, medical testing and military fields. According to the principle of Convolution Neural Networks (CNN), this paper presents a CNN human behavior recognition method based on small sample, which can identify a variety of human behaviors and human interaction behaviors respectively. The experimental result shows that the method can accurately identify the behavior of single-person and double-person interaction, and the recognition rate is above 92%, which proves the effectiveness of the method.

Keywords


Convolution Neural Networks, Small sample, Single-person behaviors, Double-person interaction.


DOI
10.12783/dtcse/smce2017/12438

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