Adaptive appearance based face recognition

Qi Li, Jieping Ye, Min Li, Chandra Kambhamettu

Research output: Contribution to journalArticlepeer-review


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
Issue number1
StatePublished - Feb 1 2008


  • Contour extraction
  • Eye location
  • Face recognition

ASJC Scopus subject areas

  • Artificial Intelligence


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