Robust Face Recognition through Local Graph Matching (2007)
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| Venue: | JOURNAL OF COMPUTERS |
| Citations: | 4 - 1 self |
BibTeX
@ARTICLE{Fazl-ersi07robustface,
author = {Ehsan Fazl-ersi and John S. Zelek and John K. Tsotsos},
title = { Robust Face Recognition through Local Graph Matching},
journal = {JOURNAL OF COMPUTERS},
year = {2007},
pages = {31--37}
}
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Abstract
A novel face recognition method is proposed, in which face images are represented by a set of local labeled graphs, each containing information about the appearance and geometry of a 3-tuple of face feature points, extracted using Local Feature Analysis (LFA) technique. Our method automatically learns a model set and builds a graph space for each individual. A two-stage method for optimal matching between the graphs extracted from a probe image and the trained model graphs is proposed. The recognition of each probe face image is performed by assigning it to the trained individual with the maximum number of references. Our approach achieves perfect result on the ORL face set and an accuracy rate of 98.4 % on the FERET face set, which shows the superiority of our method over all considered state-of-the-art methods.
Keyphrases
robust face recognition local graph matching face image trained model graph model set perfect result two-stage method optimal matching orl face set face feature point novel face recognition method graph space state-of-the-art method accuracy rate feret face set local feature analysis probe image probe face image maximum number
