%0 Conference Proceedings
%T Human Pose Estimation through a Novel Multi-view Scheme
%A Jorge Charco
%A Angel Sappa
%A Boris X. Vintimilla
%B 17th International Conference on Computer Vision Theory and Applications (VISAPP 2022)
%D 2022
%V 5
%@ 2184-4321
%@ 978-989-758-555-5
%F Jorge Charco2022
%O MSIAU; 600.160
%O exported from refbase (http://refbase.cvc.uab.es/show.php?record=3689), last updated on Tue, 25 Apr 2023 14:47:53 +0200
%X 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 amulti-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 andcomparisons with the state-of-the-art approaches on Human3.6m dataset are presented showing improvements in the accuracy of body joints estimations.
%K Multi-view Scheme
%K Human Pose Estimation
%K Relative Camera Pose
%K Monocular Approach
%U https://www.scitepress.org/Link.aspx?doi=10.5220/0010899900003124
%U http://refbase.cvc.uab.es/files/CSV2022.pdf
%P 855-862