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Author Jorge L. Charco, Angel D. 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), febrero 6-8 Abbreviated Journal
Volume 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.
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Notes Approved yes
Call Number cidis @ cidis @ Serial 169
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