Human pose estimation combined with depth information

Human pose estimation is an important research topic in the field of computer vision. Pose recognition is widely used in human-computer interaction, games, security, telepresence, medical and other fields. There has been some scholars put forward many new methods on this issue. But due to the quality differences between imaging devices, complicated appearance of characters, changeable body posture, a lot of uncertain factors such as interference of environmental background, human pose estimation is always one of the difficult problem in this area. In this paper, according to the existing problem of the traditional pose estimation method based on color image: manual intervention will bring the uncertainty leading to inaccurate foreground / background segmentation, and have a negative impact on the subsequent parsing process. We put forward a method which combined with the depth information captured by the Kinect, with the pre-processing of depth image, to improve pose estimation process in static images, so that the subsequent processing can be more convenient, and meanwhile the accuracy can be improved.