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Proceedings Paper

Scalable illumination robust face identification using harmonic representation
Author(s): Cong Xia; Jiansheng Chen; Chang Yang; Jing Wang; Jing Liu; Guangda Su; Gang Zhang
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Paper Abstract

Evaluations of both academic face recognition algorithms and commercial systems have shown that the recognition performance degrades significantly due to the variation of illumination. Previous methods for illumination robust face recognition usually involve computationally expensive 3D model transformations or optimization base reconstruction using multiple gallery face images, making them infeasible in practical large scale face identification applications. In this paper, we propose an alternative face identification framework, in which one image per person is used for enrollment as is commonly practiced in real life applications. Several probe images captured under different illumination conditions are synthesized to imitate the illumination condition of the enrolled gallery face image. We assume Lambertian reflectance of human faces and use the harmonic representations of lighting. We demonstrate satisfactory performance on the Yale B database, both visually and quantitatively. The proposed method is of very low complexity when linear facial feature are used, and is therefore scalable for large scale applications.

Paper Details

Date Published: 19 July 2013
PDF: 6 pages
Proc. SPIE 8878, Fifth International Conference on Digital Image Processing (ICDIP 2013), 88780Y (19 July 2013); doi: 10.1117/12.2030553
Show Author Affiliations
Cong Xia, Tsinghua Univ. (China)
Jiansheng Chen, Tsinghua Univ. (China)
Chang Yang, Tsinghua Univ. (China)
Jing Wang, Tsinghua Univ. (China)
Jing Liu, Tsinghua Univ. (China)
Guangda Su, Tsinghua Univ. (China)
Gang Zhang, Tsinghua Univ. (China)


Published in SPIE Proceedings Vol. 8878:
Fifth International Conference on Digital Image Processing (ICDIP 2013)
Yulin Wang; Xie Yi, Editor(s)

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