Active shape models—their training and application
Computer Vision and Image Understanding
Simulating facial surgery using finite element models
SIGGRAPH '96 Proceedings of the 23rd annual conference on Computer graphics and interactive techniques
Warping and morphing of graphical objects
Warping and morphing of graphical objects
Animated deformations with radial basis functions
VRST '00 Proceedings of the ACM symposium on Virtual reality software and technology
A framework for geometric warps and deformations
ACM Transactions on Graphics (TOG)
Image Metamorphosis with Scattered Feature Constraints
IEEE Transactions on Visualization and Computer Graphics
Image Warping with Scattered Data Interpolation
IEEE Computer Graphics and Applications
Linear Time Euclidean Distance Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume II - Volume II
Skin Aging Estimation by Facial Simulation
CA '99 Proceedings of the Computer Animation
Facial Expression Morphing and Animation with Local Warping Methods
ICIAP '99 Proceedings of the 10th International Conference on Image Analysis and Processing
Video object tracking with a sequential hierarchy of template deformations
IEEE Transactions on Circuits and Systems for Video Technology
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In this paper, we propose a virtual aesthetic surgery (VAS) system using a deformation technique based on a radial basis function (RBF) and blending technique that combines the deformed facial component with the original face. The proposed VAS system is composed of three main steps. First, various deformation templates are matched to facial components by a multi-resolution active appearance model (MAAM), which is trained by 2D color face images. Next, the VAS system computes the degree of deformation for lattice cells on the free-form deformation (FFD) using the proposed RBF. The deformation error is compensated for by the coefficients of the mapping function, which is recursively solved by the singular value decomposition (SVD) technique using the sum of squared error (SSE) between the deformed control points and target control points on the base curves. Finally, the deformed facial component is blended with the original face using a blending ratio that is computed by the modified Euclidean distance transform. Experimental results show that the proposed deformation and blending techniques are very efficient in terms of smoothness, accuracy, and distortion.