Face recognition using 2-D, 3-D, and infrared: Is multimodal better than multisample?

被引：16

作者：

Bowyer, Kevin W. ^{[1
]}

Chang, Kyong I.

Flynn, Patrick J.

Chen, Xin

机构：

[1] Univ Notre Dame, Dept Comp Sci & Engn, Notre Dame, IN 46556 USA

[2] Philips Med Syst Ultrasound, Bothell, WA 98041 USA

[3] Navteq, Chicago, IL 60654 USA

来源：

PROCEEDINGS OF THE IEEE | 2006年 / 94卷 / 11期

基金：

美国国家科学基金会;

关键词：

biometrics; face recognition; information fusion; infrared; multimodal; three-dimensional;

D O I：

10.1109/JPROC.2006.885134

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

This work examines face recognition using normal intensity images, infrared images, three-dimensional shape, and combinations of these. We compare the performance improvement obtained by combining three-dimensional or infrared with normal intensity images (a "multimodal" approach) to the performance improvement obtained by using multiple intensity images (a "multisample" approach). Combining results from different types of imagery gives significantly higher recognition rates than are obtained by using a single intensity image. However, significantly higher recognition rates are also obtained by combining results from multiple intensity images. overall, initial results indicate that, using an "eigen-face" recognition algorithm and weighted score fusion, multisample techniques can result in a performance increase comparable to that of multimodal techniques.

引用

页码：2000 / 2012

页数：13

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