Performance-driven facial animation
SIGGRAPH '90 Proceedings of the 17th annual conference on Computer graphics and interactive techniques
A Method for Registration of 3-D Shapes
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part II
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CA '96 Proceedings of the Computer Animation
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ACM SIGGRAPH 2011 papers
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ACM SIGGRAPH 2011 papers
Realtime performance-based facial animation
ACM SIGGRAPH 2011 papers
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SCA '11 Proceedings of the 2011 ACM SIGGRAPH/Eurographics Symposium on Computer Animation
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CVPR '12 Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
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ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part II
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ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part VII
Reconstructing detailed dynamic face geometry from monocular video
ACM Transactions on Graphics (TOG)
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We present a real-time performance-driven facial animation system based on 3D shape regression. In this system, the 3D positions of facial landmark points are inferred by a regressor from 2D video frames of an ordinary web camera. From these 3D points, the pose and expressions of the face are recovered by fitting a user-specific blendshape model to them. The main technical contribution of this work is the 3D regression algorithm that learns an accurate, user-specific face alignment model from an easily acquired set of training data, generated from images of the user performing a sequence of predefined facial poses and expressions. Experiments show that our system can accurately recover 3D face shapes even for fast motions, non-frontal faces, and exaggerated expressions. In addition, some capacity to handle partial occlusions and changing lighting conditions is demonstrated.