Abstract
We consider the problem of automatically recognizing a human face from its multi-view images with unconstrained poses. We formulate the multi-view face recognition task as a joint sparse representation model and take advantage of the correlations among the multiple views for face recognition using a novel joint dynamic sparsity prior. The proposed joint dynamic sparsity prior promotes shared joint sparsity patterns among the multiple sparse representation vectors at class-level, while allowing distinct sparsity patterns at atom-level within each class to facilitate a flexible representation. Extensive experiments on the CMU Multi-PIE face database are conducted to verify the efficacy of the proposed method.
Original language | English (US) |
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Pages (from-to) | 1290-1298 |
Number of pages | 9 |
Journal | Pattern Recognition |
Volume | 45 |
Issue number | 4 |
DOIs | |
State | Published - Apr 2012 |
Keywords
- Joint dynamic sparse representation based classification
- Joint dynamic sparsity
- Multi-view face recognition
ASJC Scopus subject areas
- Software
- Signal Processing
- Computer Vision and Pattern Recognition
- Artificial Intelligence