Multi-cues eye detection on gray intensity image

Guo Can Feng, Pong Chi YUEN*

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

151 Citations (Scopus)


This paper presents a novel eye detection method for gray intensity image. The precise eye position can be located if the eye windows are accurately detected. The proposed method uses multi-cues for detecting eye windows from a face image. Three cues from the face image are used. Each cue indicates the positions of the potential eye windows. The first cue is the face intensity because the intensity of eye regions is relatively low. The second cue is based on the estimated direction of the line joining the centers of the eyes. The third cue is from the response of convolving the proposed eye variance filter with the face image. Based on the three cues, a cross-validation process is performed. This process generates a list of possible eye window pairs. For each possible case, variance projection function is used for eye detection and verification. A face database from MIT Al laboratory, which contains 930 face images with different orientations and hairstyles captured from different people, is used to evaluate the proposed system. The detection accuracy is 92.5%.

Original languageEnglish
Pages (from-to)1033-1046
Number of pages14
JournalPattern Recognition
Issue number5
Publication statusPublished - May 2001

Scopus Subject Areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence

User-Defined Keywords

  • Eye detection
  • Eye variance filter
  • Face detection
  • Face recognition


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