Face recognition and unseen subject rejection in margin enhanced space

Ju Chin Chen, Shang You Shi, Jenn Jier James Lien

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

In this paper, we develop a face recognition system with a rejection mechanism for imposter or unseen subjects. In order to boost the recognition rate and provide the promising rejection accuracy, a margin-enhanced space is derived by reweighting the LSDA space via explicitly imposing the constraint of the k-NN classification rule. In this space, not only the local discriminant structure of data can be extracted but the enhanced pairwise distance can be used to model the acceptance and rejection likelihood probability. According to the Bayes decision rule, the unseen subject can be rejected if the likelihood ratio is smaller than the estimated threshold. Note that the rejection performance based on the likelihood ratio is more tolerable than the pre-defined distance only. Experimental results show that the proposed system not only yields the higher recognition rate than other subspace learning methods but also provides the promising rejection accuracy on the challenging databases of various lighting conditions and facial expression.

Original languageEnglish
Title of host publication2010 International Conference on System Science and Engineering, ICSSE 2010
Pages631-636
Number of pages6
DOIs
Publication statusPublished - 2010 Oct 11
Event2010 International Conference on System Science and Engineering, ICSSE 2010 - Taipei, Taiwan
Duration: 2010 Jul 12010 Jul 3

Publication series

Name2010 International Conference on System Science and Engineering, ICSSE 2010

Other

Other2010 International Conference on System Science and Engineering, ICSSE 2010
CountryTaiwan
CityTaipei
Period10-07-0110-07-03

All Science Journal Classification (ASJC) codes

  • Computational Theory and Mathematics
  • Computer Science Applications
  • Information Systems
  • Control and Systems Engineering

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