Discriminant analysis of haar features for accurate eye detection

Shuo Chen, Chengjun Liu

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

6 Scopus citations

Abstract

The efficient and discriminating feature extraction is a significant problem in pattern recognition and computer vision. This paper presents a novel Discriminating Haar (D-Haar) features for eye detection. The D-Haar feature extraction starts with a Principal Component Analysis (PCA) followed by a whitening transformation on the Haar feature space. A discriminant analysis is then performed on the reduced feature space. A set of basis vectors, based on the novel definition of the within-class and between-class scatter vectors and a new criterion vector, is defined through this analysis. The D-Haar features are derived in the subspace spanned by these basis vectors. We then present an accurate eye detection approach using the D-Haar features. Experiments on Face Recognition Grand Challenge (FRGC) show the promising discriminating power of D-Haar features and the improved detection performance over existing methods.

Original languageEnglish (US)
Title of host publicationProceedings of the 2011 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2011
Pages917-923
Number of pages7
StatePublished - 2011
Event2011 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2011 - Las Vegas, NV, United States
Duration: Jul 18 2011Jul 21 2011

Publication series

NameProceedings of the 2011 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2011
Volume2

Other

Other2011 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2011
CountryUnited States
CityLas Vegas, NV
Period7/18/117/21/11

All Science Journal Classification (ASJC) codes

  • Computer Graphics and Computer-Aided Design
  • Computer Vision and Pattern Recognition

Keywords

  • Discriminant analysis
  • Eye detection
  • Face recognition grand challenge
  • Haar wavelet

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