An Efficient Face and Eye Detector Modeling in External Environment

  • Mi Young Nam
  • Eun Jin Koh
  • Phill Kyu Rhee
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4029)


In this paper, we propose multi-class classifier and knowledge based face detection. Eye region and face location is used illuminant based Bayesian detector. We propose the efficient face and eye detection system using varying illuminant context modeling and multi–classifier. The face detection system architecture use cascade method by illuminant face model. Also, we detect eye region after face detection. Proposed eye detection frame is multiple illuminant Bayesian classifiers. Because face images have varying illuminant and this is vary difficult problem in face detection. Therefore, we made in context model using face illuminant. The multiple classifiers consist of face illuminant information. Multiple Bayesian classifiers are employed for selection of face and eye detection windows on illuminant face group. Finally, face and eye regions of the detected candidates are selected by context awareness.


False Alarm Face Recognition Face Image Object Detection Face Detection 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Mi Young Nam
    • 1
  • Eun Jin Koh
    • 1
  • Phill Kyu Rhee
    • 1
  1. 1.Dept. of Computer Science & EngineeringInha University 253IncheonKorea

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