Optimized 4D Dpm For Pose Estimation On Rgbd Channels Using Polisphere Models
Keywords
DPM; Human pose estimation; Inverse kinematics; RGBD images
Abstract
The Deformable Parts Model (DPM) is a standard method to perform human pose estimation on RGB images, 3 channels. Although there has been much work to improve such method, little work has been done on utilizing DPM on other types of imagery such as RGBD data. In this paper, we describe a formulation of the DPM model that makes use of depth information channels in order to improve joint detection and pose estimation using 4 channels. In order to offset the time complexity and overhead added to the model due to extra channels to process, we propose an optimization for the proposed algorithm based on solving direct and inverse kinematic equations, that form we can reduce the interested points reducing, at the same time, the time complexity. Our results show a significant improvement on pose estimation over the standard DPM model on our own RGBD dataset and on the public CAD60 dataset.
Publication Date
1-1-2017
Publication Title
VISIGRAPP 2017 - Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications
Volume
5
Number of Pages
281-288
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.5220/0006133702810288
Copyright Status
Unknown
Socpus ID
85028060176 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/85028060176
STARS Citation
Martinez, Enrique; Nina, Oliver; Sanchez, Antonio J.; and Ricolfe, Carlos, "Optimized 4D Dpm For Pose Estimation On Rgbd Channels Using Polisphere Models" (2017). Scopus Export 2015-2019. 7124.
https://stars.library.ucf.edu/scopus2015/7124