Multi-view face recognition via joint dynamic sparse representation

Haichao Zhang, Nasser M. Nasrabadi, Thomas S. Huang, Yanning Zhang

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

Abstract

We consider the problem of automatically recognizing a human face from its multi-view images with unconstrained poses and illuminations. We formulate the multi-view face recognition problem as that of classifying among several multi-input (views) regression models by using a novel joint dynamic sparse representation method which exploits jointly the inter-correlation among all the multi-view images in order to make a decision. Extensive experiments on CMU Multi-PIE face database are conducted to verify the efficacy of the proposed method.

Original languageEnglish (US)
Title of host publicationICIP 2011
Subtitle of host publication2011 18th IEEE International Conference on Image Processing
Pages3025-3028
Number of pages4
DOIs
StatePublished - 2011
Event2011 18th IEEE International Conference on Image Processing, ICIP 2011 - Brussels, Belgium
Duration: Sep 11 2011Sep 14 2011

Publication series

NameProceedings - International Conference on Image Processing, ICIP
ISSN (Print)1522-4880

Other

Other2011 18th IEEE International Conference on Image Processing, ICIP 2011
CountryBelgium
CityBrussels
Period9/11/119/14/11

Keywords

  • joint dynamic sparsity
  • multi-view face recognition
  • sparse representation based classification

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

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