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Proceedings Paper

Face recognition: database acquisition, hybrid algorithms, and human studies
Author(s): Srinivas Gutta; Jeffrey R.-J. Huang; Dig Singh; Harry Wechsler
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Paper Abstract

One of the most important technologies absent in traditional and emerging frontiers of computing is the management of visual information. Faces are accessible `windows' into the mechanisms that govern our emotional and social lives. The corresponding face recognition tasks considered herein include: (1) Surveillance, (2) CBIR, and (3) CBIR subject to correct ID (`match') displaying specific facial landmarks such as wearing glasses. We developed robust matching (`classification') and retrieval schemes based on hybrid classifiers and showed their feasibility using the FERET database. The hybrid classifier architecture consist of an ensemble of connectionist networks--radial basis functions-- and decision trees. The specific characteristics of our hybrid architecture include (a) query by consensus as provided by ensembles of networks for coping with the inherent variability of the image formation and data acquisition process, and (b) flexible and adaptive thresholds as opposed to ad hoc and hard thresholds. Experimental results, proving the feasibility of our approach, yield (i) 96% accuracy, using cross validation (CV), for surveillance on a data base consisting of 904 images (ii) 97% accuracy for CBIR tasks, on a database of 1084 images, and (iii) 93% accuracy, using CV, for CBIR subject to correct ID match tasks on a data base of 200 images.

Paper Details

Date Published: 14 February 1997
PDF: 12 pages
Proc. SPIE 2935, Surveillance and Assessment Technologies for Law Enforcement, (14 February 1997); doi: 10.1117/12.266795
Show Author Affiliations
Srinivas Gutta, George Mason Univ. (United States)
Jeffrey R.-J. Huang, George Mason Univ. (United States)
Dig Singh, George Mason Univ. (United States)
Harry Wechsler, George Mason Univ. (United States)

Published in SPIE Proceedings Vol. 2935:
Surveillance and Assessment Technologies for Law Enforcement
A. Trent DePersia; Suzan Yeager; Steve M. Ortiz, Editor(s)

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