A New Approach for 2D-3D Heterogeneous Face Recognition

被引：8

作者：

Wang, Xiaolong ^{[1
]}

Ly, Vincent ^{[1
]}

Guo, Guodong ^{[2
]}

Kambhamettu, Chandra ^{[1
]}

机构：

[1] Univ Delaware, Newark, DE 19716 USA

[2] W Virginia Univ, Morgantown, WV 26506 USA

来源：

2013 IEEE INTERNATIONAL SYMPOSIUM ON MULTIMEDIA (ISM) | 2013年

关键词：

Partial least square; canonical correlation analysis; heterogeneous face recognition; fusion; 3D;

D O I：

10.1109/ISM.2013.58

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper proposes a novel scheme for face recognition from visible images to depth images. In our proposed technique, we adopt Partial Least Square (PLS) to handle correlation mapping between 2D to 3D. A considerable performance improvement is observed compared to using Canonical Correlation Analysis (CCA). To further improve the performance, a fusion scheme based on PLS and CCA is advocated. We evaluate the advocated approach on a popular face dataset-FRGCV2.0. Experimental results demonstrate that the proposed scheme is an effective approach to perform 2D-3D face recognition.

引用

页码：301 / 304

页数：4

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