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Proceedings Paper

Multi-stream face recognition for crime-fighting
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Paper Abstract

Automatic face recognition (AFR) is a challenging task that is increasingly becoming the preferred biometric trait for identification and has the potential of becoming an essential tool in the fight against crime and terrorism. Closed-circuit television (CCTV) cameras have increasingly been used over the last few years for surveillance in public places such as airports, train stations and shopping centers. They are used to detect and prevent crime, shoplifting, public disorder and terrorism. The work of law-enforcing and intelligence agencies is becoming more reliant on the use of databases of biometric data for large section of the population. Face is one of the most natural biometric traits that can be used for identification and surveillance. However, variations in lighting conditions, facial expressions, face size and pose are a great obstacle to AFR. This paper is concerned with using waveletbased face recognition schemes in the presence of variations of expressions and illumination. In particular, we will investigate the use of a combination of wavelet frequency channels for a multi-stream face recognition using various wavelet subbands as different face signal streams. The proposed schemes extend our recently developed face veri.cation scheme for implementation on mobile devices. We shall present experimental results on the performance of our proposed schemes for a number of face databases including a new AV database recorded on a PDA. By analyzing the various experimental data, we shall demonstrate that the multi-stream approach is robust against variations in illumination and facial expressions than the previous single-stream approach.

Paper Details

Date Published: 12 April 2007
PDF: 12 pages
Proc. SPIE 6539, Biometric Technology for Human Identification IV, 65390J (12 April 2007); doi: 10.1117/12.719775
Show Author Affiliations
Sabah A. Jassim, Univ. of Buckingham (United Kingdom)
Harin Sellahewa, Univ. of Buckingham (United Kingdom)
Gray Cancer Institute (United Kingdom)

Published in SPIE Proceedings Vol. 6539:
Biometric Technology for Human Identification IV
Salil Prabhakar; Arun A. Ross, Editor(s)

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