Feature selection and facial recognition with sparse multiclass classification

Zhenqiu Liu, Amy Liu

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

Abstract

Facial recognition is a popular field of image analysis that has seen a lot of attention in recent years due to its many biometric and commercial applications. In this project, we propose a sparse multi-label classification approach for face identification and feature selection. Our approach is evaluated with two Yale face databases downloaded from the web site: http://www.face-rec.org/databases/. The performance of the proposed approach will be compared with the eigenface and linear discrimination analysis approaches described in contemporary literature.

Original languageEnglish (US)
Title of host publicationProceedings of the 2011 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2011
Pages970-972
Number of pages3
StatePublished - Dec 1 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

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