Human Motion Sequence Recognition Based on Feature Selection and Support Vector Machine

Aiming at the problem of human motion sequence recognition, algorithm based on feature selection and support vector machine is proposed. Firstly, the feature extraction of human motion sequences is obtained by key frame and human joint angle calculation. Then, based on the Pearson correlation coefficient and CFS evaluation function, the algorithm of relevance feature selection is used to search the optimal feature subset from the original feature set. By reducing the dimension of the feature set, the difficulty of classification recognition is reduced. In the classification process, the support vector machine is used as the classifier to complete the recognition task of the human motion sequence. Through the recognition experiment and the contrast experiment, the effectiveness of the recognition algorithm based on feature selection and support vector machine is proved.