Mixed features based improved human action recognition algorithm
基于混合特征的人体动作识别改进算法

The choice of the motion features affects the result of the human action recognition method directly. Many factors often influence the single feature differently, such as appearance of human body, environment and video camera. So the accuracy of action recognition is limited. On the basis of studying the representation and recognition of human actions, and giving full consideration to the advantages and disadvantages of different features, this paper proposed a mixed feature which combined global silhouette feature and local optical flow feature. This combined representation was used for human action recognition. The experimental results demonstrate that this algorithm can recognize human actions and achieve high recognition rates. This algorithm achieves 100% correct recognition rate for the human actions in the Weizmann database.