Face recognition with visible and thermal infrared imagery

Authors:
Diego A. Socolinsky;Andrea Selinger;Joshua D. Neuheisel
Affiliations:
Equinox Corporation, 207 East Redwood Street, Suite 1005, Baltimore, MD;Equinox Corporation, 9 West 57th Street, New York, NY;Equinox Corporation, 207 East Redwood Street, Suite 1005, Baltimore, MD
Venue:
Computer Vision and Image Understanding - Special issue on Face recognition
Year:
2003

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Abstract

We present a comprehensive performance study of multiple appearance-based face recognition methodologies, on visible and thermal infrared imagery. We compare algorithms within the same imaging modality as well as between them. Both identification and verification scenarios are considered, and appropriate performance statistics reported for each case. Our experimental design is aimed at gaining full understanding of algorithm performance under varying conditions, and is based on Monte Carlo analysis of performance measures. This analysis reveals that under many circumstances, using thermal infrared imagery yields higher performance, while in other cases performance in both modalities is equivalent. Performance increases further when algorithms on visible and thermal infrared imagery are fused. Our study also provides a partial explanation for the multiple contradictory claims in the literature regarding performance of various algorithms on visible data sets.