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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.

Optimized 4D DPM for Pose Estimation on RGBD Channels using Polisphere Models