Abstract: In order to solve the problems in multi-person behavior recognition,for example,it is difficult to distinguish many characters,it is difficult to express and learn increased feature dimension of image,the behavior background is complex and it is easy to cause interference,this paper proposed a method of multiplayer behavior recognition based on convolutional neural network.At first,considering the complexity of multi-person behavior recognition,the simple two-person interactive behavior is choosen as the research object and the picture database is collected.Then,because multiplayer behavior recognition has complicated background and many features in the recognition progress,a method using the Dense-sift algorithm for feature pretreatment mode is proposed.Against the complexity of the multiplayer behavior recognition,this network makes various modifications,such as input dimensions which is expanded to include layer convolution,convolution kernel increasing,output reduction,etc.Experimental results show that the proposed method can recognize simple multi-person behavior recognition,such as boxing,hug and kissing effectively.

Key words: Multi-person behavior recognition,Convolutional neural network,Dense-sift feature extraction