TY - GEN
T1 - Fast 3D reconstruction of human shape and motion tracking by parallel fast level set method
AU - Iwashita, Yumi
AU - Kurazume, Ryo
AU - Hara, Kenji
AU - Uchida, Seiichi
AU - Morooka, Ken'ichi
AU - Hasegawa, Tsutomu
PY - 2008
Y1 - 2008
N2 - This paper presents a parallel algorithm of the Level Set Method named the Parallel Fast Level Set Method, and its application for real-time 3D reconstruction of human shape and motion. The Fast Level Set Method is an efficient implementation algorithm of the Level Set Method and has been applied to several applications such as object tracking in video images and 3D shape reconstruction using multiple stereo cameras. In this paper, we implement the Fast Level Set Method on a PC cluster and develop a real-time motion capture system for arbitrary viewpoint image synthesis. To obtain high performance on a PC cluster, efficient load-balancing and resource allocation algorithms are crucial problems. We develop a novel optimization technique of load distribution based on the estimation of moving direction of object boundaries. In this technique, the boundary motion is estimated in the framework of the Fast Level Set Method, and the optimum load distribution is predicted and performed according to the estimated boundary motion and the current load balance. Experiments of human shape reconstruction and arbitrary viewpoint image synthesis using the proposed system are successfully carried out.
AB - This paper presents a parallel algorithm of the Level Set Method named the Parallel Fast Level Set Method, and its application for real-time 3D reconstruction of human shape and motion. The Fast Level Set Method is an efficient implementation algorithm of the Level Set Method and has been applied to several applications such as object tracking in video images and 3D shape reconstruction using multiple stereo cameras. In this paper, we implement the Fast Level Set Method on a PC cluster and develop a real-time motion capture system for arbitrary viewpoint image synthesis. To obtain high performance on a PC cluster, efficient load-balancing and resource allocation algorithms are crucial problems. We develop a novel optimization technique of load distribution based on the estimation of moving direction of object boundaries. In this technique, the boundary motion is estimated in the framework of the Fast Level Set Method, and the optimum load distribution is predicted and performed according to the estimated boundary motion and the current load balance. Experiments of human shape reconstruction and arbitrary viewpoint image synthesis using the proposed system are successfully carried out.
UR - http://www.scopus.com/inward/record.url?scp=51649097986&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=51649097986&partnerID=8YFLogxK
U2 - 10.1109/ROBOT.2008.4543332
DO - 10.1109/ROBOT.2008.4543332
M3 - Conference contribution
AN - SCOPUS:51649097986
SN - 9781424416479
T3 - Proceedings - IEEE International Conference on Robotics and Automation
SP - 980
EP - 986
BT - 2008 IEEE International Conference on Robotics and Automation, ICRA 2008
T2 - 2008 IEEE International Conference on Robotics and Automation, ICRA 2008
Y2 - 19 May 2008 through 23 May 2008
ER -