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Proceedings Paper

Multiscale representations for face recognition
Author(s): S. Chandu Ravela
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Paper Abstract

Automatic face recognition algorithms have the potential to impact several applications including surveillance, human augmentation, multimedia indexing and retrieval, and authentication. In this paper, a technique to retrieve images by visual appearance similarity is applied to the problem of face recognition. The framework for representing and computing similarity is based on the design and use of multi-scale Gaussian differential features (MGDFs) as appearance features. In the first part of this paper, the relevance of MGDFs as appearance features and an algorithm to deduce global similarity is developed. In the second part of this paper, multi-scale representations are applied to face recognition. Results from experiments on standard test collections tested in this paper indicate that at least 96% recognition accuracy is obtained, and when compared with other techniques, the MGDF based representation yields comparable or better results. The MGDF based technique is very general; it was originally developed for global appearance similarity retrieval in heterogeneous images, and has been applied to retrieve similar textures, trademarks, binary shapes and heterogeneous gray-level collections.

Paper Details

Date Published: 21 February 2001
PDF: 10 pages
Proc. SPIE 4232, Enabling Technologies for Law Enforcement and Security, (21 February 2001); doi: 10.1117/12.417562
Show Author Affiliations
S. Chandu Ravela, Univ. of Massachusetts/Amherst (United States)


Published in SPIE Proceedings Vol. 4232:
Enabling Technologies for Law Enforcement and Security
Simon K. Bramble; Lenny I. Rudin; Simon K. Bramble; Edward M. Carapezza; Lenny I. Rudin, Editor(s)

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