Please use this identifier to cite or link to this item: https://doi.org/10.1109/FGR.2006.40
Title: Face alignment with unified subspace optimization of active statistical models
Authors: Zhao, M. 
Chua, T.-S. 
Issue Date: 2006
Source: Zhao, M.,Chua, T.-S. (2006). Face alignment with unified subspace optimization of active statistical models. FGR 2006: Proceedings of the 7th International Conference on Automatic Face and Gesture Recognition 2006 : 67-72. ScholarBank@NUS Repository. https://doi.org/10.1109/FGR.2006.40
Abstract: Active statistical models including active shape models and active appearance models are very powerful for face alignment. They are composed of two parts: The subspace model(s) and the search process. While these two parts are closely correlated, existing efforts treated them separately and had not considered how to optimize them overall. Another problem with the subspace model(s) is that the two kinds of parameters of subspaces (the number of components and the constraints on the components) are also treated separately. So they are not jointly optimized. To tackle these two problems, an unified subspace optimization method is proposed. This method is composed of two unification aspects: (1) unification of the statistical model and the search process: The subspace models are optimized according to the search procedure; (2) unification of the number of components and the constraints: The two kinds of parameters are modelled in an unified way, such that they can be optimized jointly. Experimental results demonstrate that our method can effectively find the optimal subspace model and significantly improve the performance. © 2006 IEEE.
Source Title: FGR 2006: Proceedings of the 7th International Conference on Automatic Face and Gesture Recognition
URI: http://scholarbank.nus.edu.sg/handle/10635/41687
ISBN: 0769525032
DOI: 10.1109/FGR.2006.40
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