Recognizing Rotated Faces From Frontal and Side Views: An Approach Toward Effective Use of Mugshot Databases

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Title Recognizing Rotated Faces From Frontal and Side Views: An Approach Toward Effective Use of Mugshot Databases
Author Zhang, Paul; Gao, Yongsheng; Leung, Maylor K. H.
Journal Name IEEE Transactions on Information Forensics and Security
Editor Pierre Moulin (Editor-in-Chief)
Year Published 2008
Place of publication United States
Publisher IEEE
Abstract Mug shot photography has been used to identify criminals by the police for more than a century. However, the common scenario of face recognition using frontal and side-view mug shots as gallery remains largely uninvestigated in computerized face recognition across pose. This paper presents a novel appearance-based approach using frontal and sideface images to handle pose variations in face recognition, which has great potential in forensic and security applications involving police mugshot databases. Virtual views in different poses are generated in two steps: 1) shape modelling and 2) texture synthesis. In the shape modelling step, a multilevel variation minimization approach is applied to generate personalized 3-D face shapes. In the texture synthesis step, face surface properties are analyzed and virtual views in arbitrary viewing conditions are rendered, taking diffuse and specular reflections into account. Appearance-based face recognition is performed with the augmentation of synthesized virtual views covering possible viewing angles to recognize probe views in arbitrary conditions. The encouraging experimental results demonstrated that the proposed approach by using frontal and side-view images is a feasible and effective solution to recognizing rotated faces, which can lead to a better and practical use of existing forensic databases in computerized human face-recognition applications.
Peer Reviewed Yes
Published Yes
Publisher URI http://ieeexplore.ieee.org/servlet/opac?punumber=10206
Alternative URI http://dx.doi.org/10.1109/TIFS.2008.2004286
Copyright Statement Copyright 2008 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Volume 3
Issue Number 4
Page from 684
Page to 697
ISSN 1556-6013
Date Accessioned 2008-11-26
Date Available 2009-05-12T06:39:02Z
Language en_AU
Research Centre Institute for Integrated and Intelligent Systems
Faculty Faculty of Science, Environment, Engineering and Technology
Subject PRE2009-Computer Vision; PRE2009-Image Processing; PRE2009-Pattern Recognition
URI http://hdl.handle.net/10072/22882
Publication Type Journal Articles (Refereed Article)
Publication Type Code c1

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