RT Journal Article
T1 3D human pose estimation from depth maps using a deep combination of poses
A1 Marin-Jimenez, Manuel J.
A1 Romero-Ramirez, Francisco J.
A1 Munoz-Salinas, Rafael
A1 Medina-Carnicer, Rafael
K1 3D human pose
K1 Body limbs
K1 Depth maps
K1 ConvNets
AB Many real-world applications require the estimation of human body joints for higher-level tasks as, for example, human behaviour understanding. In recent years, depth sensors have become a popular approach to obtain three-dimensional information. The depth maps generated by these sensors provide information that can be employed to disambiguate the poses observed in two-dimensional images. This work addresses the problem of 3D human pose estimation from depth maps employing a Deep Learning approach. We propose a model, named Deep Depth Pose (DDP), which receives a depth map containing a person and a set of predefined 3D prototype poses and returns the 3D position of the body joints of the person. In particular, DDP is defined as a ConvNet that computes the specific weights needed to linearly combine the prototypes for the given input. We have thoroughly evaluated DDP on the challenging 'ITOP' and 'UBC3V' datasets, which respectively depict realistic and synthetic samples, defining a new state-of-the-art on them.
PB Academic Press
SN 1047-3203
YR 2018
FD 2018-07-17
LK http://hdl.handle.net/10668/18831
UL http://hdl.handle.net/10668/18831
LA en
NO Marín-Jiménez MJ, Romero-Ramirez FJ, Muñoz-Salinas R, Medina-Carnicer R. 3D human pose estimation from depth maps using a deep combination of poses. Journal Of Visual Communication And Image Representation [Internet]. 1 de agosto de 2018;55:627-39.
NO This project has been funded under projects TIN2016-75279-P and IFI16/00033 (ISCIII) of Spain Ministry of Economy, Industry and Competitiveness, and FEDER. Thanks to NVidia for donating the GPU Titan Xp used for the experiments presented in this work. We also thank Shafaei and Little for providing their error and precision results used in ourcomparative plots.
DS RISalud
RD Apr 12, 2025