Automatic estimation of skeletal motion from optical motion capture data
Authors: Xiao, Z., Nait-Charif, H. and Zhang, J.J.
Volume: 5277 LNCS
Pages: 144-153
ISBN: 9783540892199
DOI: 10.1007/978-3-540-89220-5_15
Abstract:Utilization of motion capture techniques is becoming more popular in the pipeline of articulated character animation. Based upon captured motion data, defining accurate joint positions and joint orientations for the movement of a hierarchical human-like character without using a pre-defined skeleton is still a potential concern for motion capture studios. In this paper, we present a method for automatically estimating and determining the topology of hierarchical human skeleton from optical motion capture data based on the human biomechanical information. Through the use of a novel per-frame based recursive method with joint angle minimization, human skeleton mapping from optical marker and joint angle rotations are achieved in real time. The output of motion data from a hierarchical skeleton can be applied for further character motion editing and retargeting. © 2008 Springer Berlin Heidelberg.
Source: Scopus
Automatic Estimation of Skeletal Motion from Optical Motion Capture Data
Authors: Xiao, Z., Nait-Charif, H. and Zhang, J.J.
Volume: 5277
Pages: 144-153
ISBN: 978-3-540-89219-9
Source: Web of Science (Lite)
Automatic Estimation of Skeletal Motion from Optical Motion Capture Data
Authors: Xiao, Z., Nait-Charif, H. and Zhang, J.J.
Pages: 144-153
Publisher: Springer
ISBN: 978-3-540-89219-9
DOI: 10.1007/978-3-540-89220-5
Abstract:Utilization of motion capture techniques is becoming more popular in the pipeline of articulated character animation. Based upon captured motion data, defining accurate joint positions and joint orientations for the movement of a hierarchical human-like character without using a pre-defined skeleton is still a potential concern for motion capture studios. In this paper, we present a method for automatically estimating and determining the topology of hierarchical human skeleton from optical motion capture data based on the human biomechanical information. Through the use of a novel per-frame based recursive method with joint angle minimization, human skeleton mapping from optical marker and joint angle rotations are achieved in real time. The output of motion data from a hierarchical skeleton can be applied for further character motion editing and retargeting.
http://www.springerlink.com/content/17135637750h568g/
Source: Manual
Preferred by: Zhidong Xiao, Jian Jun Zhang and Hammadi Nait-Charif