Charco J., Sappa A., Vintimilla B. and Velesaca O., “Human Pose Estimation through a Novel Multi-view Scheme”, 17th Int. Conf. on Computer Vision Theory and Applications, Online, February 6-8, 2022, pp 855-862.
This paper presents a multi-view scheme to tackle the challenging problem of the self-occlusion in human pose estimation problem. The proposed approach first obtains the human body joints of a set of images, which are captured from different views at the same time. Then, it enhances the obtained joints by using a multi-view scheme. Basically, the joints from a given view are used to enhance poorly estimated joints from another view, especially intended to tackle the self occlusions cases. A network architecture initially proposed for the monocular case is adapted to be used in the proposed multi-view scheme. Experimental results and comparisons with the state-of-the-art approaches on Human3. 6m dataset are presented showing improvements in the accuracy of body joints estimations.