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Author Jorge Charco; Angel Sappa; Boris X. Vintimilla
Title Human Pose Estimation through a Novel Multi-view Scheme Type Conference Article
Year 2022 Publication 17th International Conference on Computer Vision Theory and Applications (VISAPP 2022) Abbreviated Journal
Volume 5 Issue Pages (down) 855-862
Keywords Multi-view Scheme; Human Pose Estimation; Relative Camera Pose; Monocular Approach
Abstract 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.
Address On line; Feb 6, 2022 – Feb 8, 2022
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2184-4321 ISBN 978-989-758-555-5 Medium
Area Expedition Conference VISAPP
Notes MSIAU; 600.160 Approved no
Call Number Admin @ si @ CSV2022 Serial 3689
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