Authors:
Jorge L. Charco
1
;
2
;
Angel D. Sappa
3
;
1
and
Boris X. Vintimilla
1
Affiliations:
1
ESPOL Polytechnic University, Escuela Superior Politécnica del Litoral, ESPOL, Campus Gustavo Galindo Km. 30.5 Vía Perimetral, P.O. Box 09-01-5863, Guayaquil, Ecuador
;
2
Universidad de Guayaquil, Delta and Kennedy Av., P.B. EC090514, Guayaquil, Ecuador
;
3
Computer Vision Center, Edifici O, Campus UAB, 08193 Bellaterra, Barcelona, Spain
Keyword(s):
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.