earticle

영어

Pose estimation which is regard as the cross-technology of computer vision and pattern recognition, and an important prerequisite for human behavior understanding. Human pose estimation which use the probability theory, machine learning, pattern recognition, graph theory and other theories to get the position, the deflection angle of the various parts of the body. Then make the detection and estimation parameters for the human body pose. When the image has interference in the background, color and scale changed, human pose complex, self-occlusion and interpersonal interaction occlusion may make the precision and accuracy of pose estimation face great challenge. Thus, according to the above problems, this paper use the advanced model of the human body as contour model to descript the complex pose, in order to make the model more accurate and suitable for various human pose, we pre-clustering the human body pose of the training samples before we trained the model and in order to ensure the accuracy of the pose we use robust segmentation of multi-view with a novel shape prior. The experiment shows that the algorithm performs better than the classic algorithm on the public datasets.