Programs
- M. Tech. in Automotive Engineering -
- Clinical Fellowship in Laboratory Genetics & Genomics - Fellowship
Blendshape models are used in various computer vision applications, such as expression transfer, 3D reconstruction, expression analysis and so on. Blendshape models have received lot of attention in last decades, and extensive research is carried out in the 3D face modeling. Computer-based animations use blendshape models for the transfer of target facial expression to animated character. The major challenge in such animation is developing blendshape models that can represent various facial expressions. To create such large data set of expression, one requires a dedicated expert team and it is a time-consuming process. In this paper, we propose a framework for automatic facial landmark detection and blendshape generation through expression transfer. The proposed work is in two main folds: Initially, facial landmarks are extracted based on geometric information of the given facial mesh. Further, the extracted landmark points and the estimated correspondence between source and target facial models are used to perform deformation transfer. Experiment results show that our method is able to transfer expression by using automatic landmarks and also the smoothness of deformation around facial landmark areas proves that our proposed landmark-based deformation method is as good as the state-of-the-art methods. Our proposed method for automatic facial landmark detection based on geometric information of 3D face model has the ability to detect reliable correspondences, and it is faster and simpler compared with the state-of-the-art automatic deformation transfer method on the facial models.
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