Inverse kinematics positioning using nonlinear programming for highly articulated figures
ACM Transactions on Graphics (TOG)
Efficient generation of motion transitions using spacetime constraints
SIGGRAPH '96 Proceedings of the 23rd annual conference on Computer graphics and interactive techniques
Retargetting motion to new characters
Proceedings of the 25th annual conference on Computer graphics and interactive techniques
Physically based motion transformation
Proceedings of the 26th annual conference on Computer graphics and interactive techniques
Local and Global Skeleton Fitting Techniques for Optical Motion Capture
CAPTECH '98 Proceedings of the International Workshop on Modelling and Motion Capture Techniques for Virtual Environments
Flexible automatic motion blending with registration curves
Proceedings of the 2003 ACM SIGGRAPH/Eurographics symposium on Computer animation
Mapping optical motion capture data to skeletal motion using a physical model
Proceedings of the 2003 ACM SIGGRAPH/Eurographics symposium on Computer animation
PCA-Based Walking Engine Using Motion Capture Data
CGI '04 Proceedings of the Computer Graphics International
Synthesizing physically realistic human motion in low-dimensional, behavior-specific spaces
ACM SIGGRAPH 2004 Papers
Momentum-based parameterization of dynamic character motion
SCA '04 Proceedings of the 2004 ACM SIGGRAPH/Eurographics symposium on Computer animation
Skeletal Parameter Estimation from Optical Motion Capture Data
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Efficient content-based retrieval of motion capture data
ACM SIGGRAPH 2005 Papers
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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.