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Comparative Study Of Human Pose Estimation Models

Human Pose Estimation is one of the main research areas in computer vision because of its profusion of applications that can benefit from such a technology. Several works have been done constantly to improve this technology and is still the most debatable and challenging topics in the present. So, we present a novel comparison using existing articulated human pose estimation techniques and tried to propose a better model among them which then help in estimating better appearance models on novel images. In this paper, we have compared four different techniques used widely in computer vision field on certain metrices like pros and cons of each techniques and the best areas where they can work commendable along with their computational efficiency and numerical accuracy.