|Table of Contents|

[1] Yu Weiwei, Teng Xiaolong, Liu Chongqing,. Feature fusing in face recognition [J]. Journal of Southeast University (English Edition), 2005, 21 (4): 427-431. [doi:10.3969/j.issn.1003-7985.2005.04.010]
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Feature fusing in face recognition()
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Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

Volumn:
21
Issue:
2005 4
Page:
427-431
Research Field:
Computer Science and Engineering
Publishing date:
2005-12-30

Info

Title:
Feature fusing in face recognition
Author(s):
Yu Weiwei Teng Xiaolong Liu Chongqing
School of Electronic Information and Electrical Engineering, Shanghai Jiaotong University, Shanghai 200030, China
Keywords:
face recognition feature fusion global features local features
PACS:
TP391
DOI:
10.3969/j.issn.1003-7985.2005.04.010
Abstract:
With the aim of extracting the features of face images in face recognition, a new method of face recognition by fusing global features and local features is presented.The global features are extracted using principal component analysis(PCA).Active appearance model(AAM)locates 58 facial fiducial points, from which 17 points are characterized as local features using the Gabor wavelet transform(GWT).Normalized global match degree(local match degree)can be obtained by global features(local features)of the probe image and each gallery image.After the fusion of normalized global match degree and normalized local match degree, the recognition result is the class that included the gallery image corresponding to the largest fused match degree.The method is evaluated by the recognition rates over two face image databases(AR and SJTU-IPPR). The experimental results show that the method outperforms PCA and elastic bunch graph matching(EBGM).Moreover, it is effective and robust to expression, illumination and pose variation in some degree.

References:

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Memo

Memo:
Biographies: Yu Weiwei(1978—), female, graduate;Liu Chongqing(corresponding author), male, professor, liuchqing@263.net.
Last Update: 2005-12-20