Face recognition and verification with pose and illumination variations and imposter rejection

Chao Yuan; David P. Casasent

doi:10.1117/12.593419

28 March 2005 Face recognition and verification with pose and illumination variations and imposter rejection

Chao Yuan, David P. Casasent

Proceedings Volume 5779, Biometric Technology for Human Identification II; (2005) https://doi.org/10.1117/12.593419
Event: Defense and Security, 2005, Orlando, Florida, United States

Abstract

We address rejection-classification problems, which have been ignored in most prior work. For such a system, a high classification rate and a low false alarm rate are simultaneously desired. We first propose a one-class support vector representation machine (SVRM). The SVRM achieves a high test set detection rate by requiring a high training set detection rate; the SVRM reduces the false alarm rate by minimizing the upper bound of the decision region. The SVRM is then extended to a new support vector representation and discrimination machine (SVRDM) classifier to address multiple-class cases. The theoretical basis for our new SVRDM as best at rejection of non-objects (imposters in face recognition) is provided, as are new σ parameter selection methods. Test results on face recognition and verification with both pose and illumination variations are presented.

Citation Download Citation

Chao Yuan and David P. Casasent "Face recognition and verification with pose and illumination variations and imposter rejection", Proc. SPIE 5779, Biometric Technology for Human Identification II, (28 March 2005); https://doi.org/10.1117/12.593419

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