关键词: 动作识别, 光流特征, 剪影特征, HOG特征

Abstract: The choice of motion features affects the result of human interaction recognition algorithm directly. Because of different adaptive scopes, many factors often influence the single features, such as the appearance of human body, environment and camera setting. So it can’t achieve satisfactory accuracy of action recognition. On the basis of studying the representation and recognition of human interaction action, and giving full consideration to the advan-tages and disadvantages of different features, this paper proposes a mixed feature which combines local optical flow feature, local silhouette feature and HOG (histogram of oriented gradient) feature. The nearest neighbor classifier is used to obtain the recognition probability of three features. Finally, the recognition result is achieved by weighted fusing those recognition probabilities. The experimental results demonstrate that this algorithm achieve better recognition results in the UT-interaction database, and compared with the single features, the mixed feature can improve the recognition rate to 91.7%．

Key words: action recognition, optical flow feature, silhouette feature, HOG feature