Realistic modeling for facial animation
SIGGRAPH '95 Proceedings of the 22nd annual conference on Computer graphics and interactive techniques
Proceedings of the 25th annual conference on Computer graphics and interactive techniques
Proceedings of the 28th annual conference on Computer graphics and interactive techniques
Animated deformations with radial basis functions
VRST '00 Proceedings of the ACM symposium on Virtual reality software and technology
Head shop: generating animated head models with anatomical structure
Proceedings of the 2002 ACM SIGGRAPH/Eurographics symposium on Computer animation
An example-based approach for facial expression cloning
Proceedings of the 2003 ACM SIGGRAPH/Eurographics symposium on Computer animation
Graphical Models
Rapid modeling of 3D faces for animation using an efficient adaptation algorithm
Proceedings of the 2nd international conference on Computer graphics and interactive techniques in Australasia and South East Asia
Spacetime faces: high resolution capture for modeling and animation
ACM SIGGRAPH 2004 Papers
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Modeling the human face and producing realistic facial animation are the challenging tasks for computer animators. On the other hand, with the development of advanced laser-scanning service, it is capable of capturing face with millions of triangles. In the situations where the real-time animation is expected, the problem of how to reduce the size of the dense laser-scanned face data for the animation purpose has been addressed. In this paper, firstly we present an approach that is capable of producing the low polygon approximation model for the dense laser-scanned face while accurately conveying the distinguished features in the original data. We modify the predefined generic model based on the feature points to produce the approximation model. The modification of the generic model involves three steps: Radial Basis Function (RBF) morphing; then loop subdivision step followed by mesh refinement. Secondly, instead of creating new facial animation from scratch, we take advantage of the existing source animation data and use the face motion retargeting method to resample the source motion vectors onto our approximation model. The resulting facial animation is fast and efficient.