Adaptive appearance based face recognition

Qi Li, Jieping Ye, Min Li, Chandra Kambhamettu

Research output: Contribution to journalArticle

Abstract

In this paper, we present an adaptive appearance based face recognition framework that combines the efficiency of global approaches and the robustness of local approaches together. The framework uses a novel eye locator to select an appropriate scheme for appearance based recognition. The eye locator first locates eye candidates via a new strength assignment, determined by the dissimilarity between the local appearance of an image point and the appearance of its neighboring points. Then the eye locator applies a simple but flexible model (half-circle snake) to the local context of the eye candidates in order to either refine the location of an eye candidate or discard non-eye candidates. We show the performance of our framework by testing on challenging face datasets containing extreme expressions, severe occlusions, and varied lighting conditions.

Original languageEnglish (US)
Pages (from-to)175-193
Number of pages19
JournalInternational Journal on Artificial Intelligence Tools
Volume17
Issue number1
DOIs
StatePublished - Feb 1 2008

Keywords

  • Contour extraction
  • Eye location
  • Face recognition

ASJC Scopus subject areas

  • Artificial Intelligence

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