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Proceedings Paper

3D face identification: experiments towards a large gallery
Author(s): Dirk Colbry; Folarin Oki; George Stockman
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Paper Abstract

3D face recognition technologies, with a computation time of a few seconds, perform well for person verification. However, current 3D face recognition approaches are too slow for person identification, even for a watch list of only a few hundred face models. By transforming scanned 3D faces into a canonical face format, storage size is greatly compressed and standard feature extraction is enabled: combining these advantages allows a probe scan to be matched to hundreds or thousands of gallery scans in a few seconds on a commodity computer. We report several experiments that extract a sparse feature representation from the canonical 3D face surface and then perform recognition of a probe face based on the sparse features. We expect to have a trade off between algorithm speed and recognition performance. The best results achieved so far are a rank-1 recognition rate of 98.2% and a speed of 1900 face matches per second. Extrapolating these results suggests that multistage systems could achieve comparable or better recognition rates over large galleries within 5 seconds of compute time.

Paper Details

Date Published: 17 March 2008
PDF: 9 pages
Proc. SPIE 6944, Biometric Technology for Human Identification V, 694403 (17 March 2008); doi: 10.1117/12.778683
Show Author Affiliations
Dirk Colbry, Arizona State Univ. (United States)
Folarin Oki, Michigan State Univ. (United States)
George Stockman, Michigan State Univ. (United States)

Published in SPIE Proceedings Vol. 6944:
Biometric Technology for Human Identification V
B.V.K. Vijaya Kumar; Salil Prabhakar; Arun A. Ross, Editor(s)

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