Human Pose Estimation in Video via MCMC Sampling

摘要

We describe a method for the human pose estimation in a video sequence. We propose a new mathematical model of a human pose in a video sequence, which incorporates motion and pose parameters. We show that the model of (Park and Ramanan, 2011) is a particular case of our model. We introduce a framework to infer an approximation of the optimal value in the proposed model. We use an exact algorithm of motion parameters estimation to reduce complexity of inference. Our approach outperforms results of (Park and Ramanan, 2011) in the most complicated video sequences.