Viewpoint-invariant face recognition based on view-based representation

被引：0
|
作者：
Chung, Jinyun [1 ]
Lee, Juho [1 ]
Park, Hyun Jin [1 ]
Yang, Hyun Seung [1 ]
机构：
[1] Korea Adv Inst Sci & Technol, Taejon 305701, South Korea
来源：
COMPUTATIONAL INTELLIGENCE, PT 2, PROCEEDINGS | 2006年 / 4114卷
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, we suggest a viewpoint-invariant face recognition model based on view-based representation. The suggested model has four stages: view-based representation, viewpoint classification, frontal face estimation and face recognition. For view-based representation, we obtained the feature space by using independent subspace analysis, the bases of which are grouped like the neurons in the brain's visual area. The viewpoint of a facial image can be easily classified by a single-layer perceptron due to view-dependent activation characteristic of the feature space. To estimate the independent subspace analysis representation of frontal face, a radial basis neural network learns to generalize the relation of the bases between two viewpoints. Face recognition relies on a normalized correlation for selecting the most similar frontal faces in a gallery. Through our face recognition experiment on XM2VTS [9], we obtained a face recognition rate of 89.33%.
引用
收藏
页码：872 / 878
页数：7
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