TY - GEN
T1 - Real-time human pose estimation from body-scanned point clouds
AU - Barros, Jilliam María Díaz
AU - Garcia, Frederic
AU - Sidibé, Désiré
N1 - Publisher Copyright:
Copyright © 2015 SCITEPRESS - Science and Technology Publications All rights reserved.
PY - 2015
Y1 - 2015
N2 - This paper presents a novel approach to estimate the human pose from a body-scanned point cloud. To do so, a predefined skeleton model is first initialized according to both the skeleton base point and its torso limb obtained by Principal Component Analysis (PCA). Then, the body parts are iteratively clustered and the skeleton limb fitting is performed, based on Expectation Maximization (EM). The human pose is given by the location of each skeletal node in the fitted skeleton model. Experimental results show the ability of the method to estimate the human pose from multiple point cloud video sequences representing the external surface of a scanned human body; being robust, precise and handling large portions of missing data due to occlusions, acquisition hindrances or registration inaccuracies.
AB - This paper presents a novel approach to estimate the human pose from a body-scanned point cloud. To do so, a predefined skeleton model is first initialized according to both the skeleton base point and its torso limb obtained by Principal Component Analysis (PCA). Then, the body parts are iteratively clustered and the skeleton limb fitting is performed, based on Expectation Maximization (EM). The human pose is given by the location of each skeletal node in the fitted skeleton model. Experimental results show the ability of the method to estimate the human pose from multiple point cloud video sequences representing the external surface of a scanned human body; being robust, precise and handling large portions of missing data due to occlusions, acquisition hindrances or registration inaccuracies.
KW - Human pose estimation
KW - Point cloud
KW - Skeleton model
UR - http://www.scopus.com/inward/record.url?scp=84939515090&partnerID=8YFLogxK
U2 - 10.5220/0005309005530560
DO - 10.5220/0005309005530560
M3 - Conference contribution
AN - SCOPUS:84939515090
T3 - VISAPP 2015 - 10th International Conference on Computer Vision Theory and Applications; VISIGRAPP, Proceedings
SP - 553
EP - 560
BT - VISAPP 2015 - 10th International Conference on Computer Vision Theory and Applications; VISIGRAPP, Proceedings
A2 - Braz, Jose
A2 - Battiato, Sebastiano
A2 - Imai, Francisco
PB - SciTePress
T2 - 10th International Conference on Computer Vision Theory and Applications, VISAPP 2015
Y2 - 11 March 2015 through 14 March 2015
ER -