基于典型相关分析的快速主动外观模型搜索
Fast active appearance model search using canonical correlation analysis.
作者信息
Donner René, Reiter Michael, Langs Georg, Peloschek Philipp, Bischof Horst
机构信息
Pattern Recognition and Image Processing Group, Institute of Computer Aided Automation, Vienna University of Technology, Favoritenstr. 9/183/2, A-1040 Vienna, Austria.
出版信息
IEEE Trans Pattern Anal Mach Intell. 2006 Oct;28(10):1690-4. doi: 10.1109/TPAMI.2006.206.
A fast AAM search algorithm based on canonical correlation analysis (CCA-AAM) is introduced. It efficiently models the dependency between texture residuals and model parameters during search. Experiments show that CCA-AAMs, while requiring similar implementation effort, consistently outperform standard search with regard to convergence speed by a factor of four.
介绍了一种基于典型相关分析的快速主动形状模型搜索算法（CCA-AAM）。它在搜索过程中有效地对纹理残差和模型参数之间的相关性进行建模。实验表明，CCA-AAM虽然实现成本相近，但在收敛速度方面始终比标准搜索快四倍。
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