Fast active appearance model search using canonical correlation analysis

被引：59

作者：

Donner, Rene

Reiter, Michael

Langs, Georg

Peloschek, Philipp

Bischof, Horst

机构：

[1] Vienna Univ Technol, Pattern Recognit & Image Proc Grp, Inst Comp Aided Automat, A-1040 Vienna, Austria

[2] Graz Univ Technol, Inst Comp Graph & Vis, Comp Vis Grp, A-8010 Graz, Austria

[3] Med Univ Vienna, Dept Radiol, A-1090 Vienna, Austria

来源：

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE | 2006年 / 28卷 / 10期

基金：

奥地利科学基金会;

关键词：

image processing and computer vision; active appearance models; statistical image models; subspace methods; medical imaging;

D O I：

10.1109/TPAMI.2006.206

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：1690 / 1694

页数：5

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