Abstract:Aiming at the requirement of transfer service robots for high precision of human pose recognition and the problem of low recognition accuracy of existing human pose recognition methods under joint occlusion, this paper proposes a model constraintbased human pose recognition algorithm to solve the precise extraction of human body joint space coordinates of the robot system before the transfer operation. Firstly, the OpenPose algorithm is used to identify the pixel coordinates of the unoccluded joints in color image. Through aligning the color image and depth image of the RGBD camera, the joint pixel coordinates are converted into 3D coordinates. Then, the spatial coordinates of the occluded joint connected with the unoccluded joint are calculated according to the relevant parameters of the human model and the unoccluded joint coordinates, which are used to improve the recognition accuracy of the occluded joints. The experiment results show that the recognition accuracy of the proposed algorithm is 92% when the joint is unoccluded, and reaches 90% when the joint is occluded. The average time for a single frame calculation is about 190 ms, which meets the realtime requirements of transfer service robot operation.