We present a method that combines performance-driven method with segmented 3D blendshape models to animate a face. First we prepare key sample examples and corresponding key target examples. Next we segment the whole ...We present a method that combines performance-driven method with segmented 3D blendshape models to animate a face. First we prepare key sample examples and corresponding key target examples. Next we segment the whole face into two regions, for each region we reduce dimensionality of source examples using PAC into abstract space which is defined by truncated PCA eigen- vectors. Then for each example we fix the cardinal base function, which can determine the weight of the target example. Finally, in the animation stage we compute the weight of each example for each frame and add the weighted displacement vectors of each re- gion on the general face model.展开更多
We propose a novel method that automatically analyzes stroke-related artistic styles of paintings. A set of adaptive interfaces are also developed to connect the style analysis with existing painterly rendering system...We propose a novel method that automatically analyzes stroke-related artistic styles of paintings. A set of adaptive interfaces are also developed to connect the style analysis with existing painterly rendering systems, so that the specific artistic style of a template painting can be effectively transferred to the input photo with minimal effort. Different from conventional texture-synthesis based rendering techniques that focus mainly on texture features, this work extracts, analyzes and simulates high-level style features expressed by artists' brush stroke techniques. Through experiments, user studies and comparisons with ground truth, we demonstrate that the proposed style-orientated painting framework can significantly reduce tedious parameter adjustment, and it allows amateur users to efficiently create desired artistic styles simply by specifying a template painting.展开更多
基金supported by the National Natural Science Foundation of China (No.60875046)the Program for Changjiang Scholars and Innovative Research Team in University(No.IRT1109)+5 种基金the Key Project of Chinese Ministry of Education (No.209029)the Program for Liaoning Excellent Talents in University(No.LR201003)the Program for Liaoning Science and Technology Research in University (No.LS2010008,2009S008,2009S009,LS2010179)the Program for Liaoning Innovative Research Team in University(Nos.2009T005,LT2010005,LT2011018)Natural Science Foundation of Liaoning Province (201102008)by "Liaoning BaiQianWan Talents Program(2010921010,2011921009)"
文摘We present a method that combines performance-driven method with segmented 3D blendshape models to animate a face. First we prepare key sample examples and corresponding key target examples. Next we segment the whole face into two regions, for each region we reduce dimensionality of source examples using PAC into abstract space which is defined by truncated PCA eigen- vectors. Then for each example we fix the cardinal base function, which can determine the weight of the target example. Finally, in the animation stage we compute the weight of each example for each frame and add the weighted displacement vectors of each re- gion on the general face model.
基金supported by Fok Ying-Tong Education Foundation of China under Grant No. 131065the International Joint Project from the Royal Society of UK under Grant No. JP100987
文摘We propose a novel method that automatically analyzes stroke-related artistic styles of paintings. A set of adaptive interfaces are also developed to connect the style analysis with existing painterly rendering systems, so that the specific artistic style of a template painting can be effectively transferred to the input photo with minimal effort. Different from conventional texture-synthesis based rendering techniques that focus mainly on texture features, this work extracts, analyzes and simulates high-level style features expressed by artists' brush stroke techniques. Through experiments, user studies and comparisons with ground truth, we demonstrate that the proposed style-orientated painting framework can significantly reduce tedious parameter adjustment, and it allows amateur users to efficiently create desired artistic styles simply by specifying a template painting.