Fourier principles for emotion-based human figure animation
SIGGRAPH '95 Proceedings of the 22nd annual conference on Computer graphics and interactive techniques
SIGGRAPH '95 Proceedings of the 22nd annual conference on Computer graphics and interactive techniques
SIGGRAPH '95 Proceedings of the 22nd 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
System identification (2nd ed.): theory for the user
System identification (2nd ed.): theory for the user
A hierarchical approach to interactive motion editing for human-like figures
Proceedings of the 26th annual conference on Computer graphics and interactive techniques
Proceedings of the 27th annual conference on Computer graphics and interactive techniques
I3D '01 Proceedings of the 2001 symposium on Interactive 3D graphics
SIGGRAPH '88 Proceedings of the 15th annual conference on Computer graphics and interactive techniques
Comparing constraint-based motion editing methods
Graphical Models
Footskate cleanup for motion capture editing
Proceedings of the 2002 ACM SIGGRAPH/Eurographics symposium on Computer animation
Motion texture: a two-level statistical model for character motion synthesis
Proceedings of the 29th annual conference on Computer graphics and interactive techniques
Motion capture assisted animation: texturing and synthesis
Proceedings of the 29th annual conference on Computer graphics and interactive techniques
Practical parameterization of rotations using the exponential map
Journal of Graphics Tools
Realistic synthesis of novel human movements from a database of motion capture examples
HUMO '00 Proceedings of the Workshop on Human Motion (HUMO'00)
PCA-Based Walking Engine Using Motion Capture Data
CGI '04 Proceedings of the Computer Graphics International
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Recently, motion capture is widely used in the human animation. But it is still difficult to create new-style animations from the existing motion capture data. In this paper, we propose a novel technique to create the style animations from an existing motion sequence. Firstly, we use linear time-invariant system (LTI) to derive an explicit mapping between the high-dimensional motion capture data and the low-dimensional state variables. Secondly, new style animations are created within the state space. Only a few important keyframes need be modified through adjusting the low-dimensional style variables. The remaining frames of the original motion can be generated automatically. Finally, we design an effective algorithm to calculate the model parameters. Experimental results show that the generated style animations are natural and smooth.