Abstract
Facial expression hallucination is an important approach to facial expression synthesis. Existing works mainly focused on synthesizing a static facial expression image given one face image with neutral expression. In this paper, we propose a novel two-level hierarchical fusion approach to hallucinate dynamic expression video sequences when given only one neutral expression face image. By fusion of local linear and global nonlinear subspace learning, the two-level approach provides a sound solution to organizing the complex video sample space. Experiments show that our approach generates reasonable facial expression sequences both in temporal domain and spatial domain with less artifact compared with existing works.
This work is supported by the key program of National Natural Science Foundation of China (No.60533090), National Science Fund for Distinguished Young Scholars (No.60525108), 973 Program (No.2002CB312101), Science and Technology Project of Zhejiang Province (2005C13032, 2005C11001-05).
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Zhang, J., Zhuang, Y., Wu, F. (2006). Video-Based Facial Expression Hallucination: A Two- Level Hierarchical Fusion Approach. In: Blanc-Talon, J., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2006. Lecture Notes in Computer Science, vol 4179. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11864349_47
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DOI: https://doi.org/10.1007/11864349_47
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