Abstract
In view of the low efficiency and angle problem of human action recognition, a algorithm with Kinect-3D skeleton and MCRF model was proposed. Its 3D skeleton data has less and key information, and MCRF model was able to fusion many features and advantage of context information. First, human action was divided into global action, arm action, and leg action, extracted features through several feature subsets. Then, CRF model was used for every subset to generate, each CRF sets was merged together into MRCF model which was utilized to recognize human action. The experimental results show that the method has higher detection rate.
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