A New Algorithm of Posture Modeling and Recognition Based on Gaussian Mixture Model and EM Estimation
نویسندگان
چکیده
In this paper, we proposed a new posture modeling method based on Gaussian Mixture Model (GMM). First, spatial-temporal interest points (STIPs) were extracted according to the properties of human movement, and then, histogram of gradient (HOG) was built to describe the distribution of STIPs in each frame. In addition, the training samples were clustered by non-supervised classification method. Moreover, the postures were modeled with GMM according to Expectation Maximization (EM) estimation. The experiment results proved that our method can effectively and accurately recognize human’s action postures.
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