Facial Recognition Technology A Survey of Policy and Implementation Issues

Facial recognition technology (FRT) has emerged as an attractive solution to address many contemporary needs for identification and the verification of identity claims. It brings together the promise of other biometric systems, which attempt to tie identity to individually distinctive features of the body, and the more familiar functionality of visual surveillance systems. This report develops a socio-political analysis that bridges the technical and social-scientific literatures on FRT and addresses the unique challenges and concerns that attend its development, evaluation, and specific operational uses, contexts, and goals. It highlights the potential and limitations of the technology, noting those tasks for which it seems ready for deployment, those areas where performance obstacles may be overcome by future technological developments or sound operating procedures, and still other issues which appear intractable. Its concern with efficacy extends to ethical considerations. For the purposes of this summary, the main findings and recommendations of the report are broken down into five broad categories: performance, evaluation, operation, policy concerns, and moral and political considerations. These findings and recommendations employ certain technical concepts and language that are explained and explored in the body of the report and glossary, to which you should turn for further elaboration.

[1]  Patrick J. Flynn,et al.  A survey of approaches and challenges in 3D and multi-modal 3D + 2D face recognition , 2006, Comput. Vis. Image Underst..

[2]  M. Turk,et al.  Eigenfaces for Recognition , 1991, Journal of Cognitive Neuroscience.

[3]  Irma van der Ploeg,et al.  The illegal body: `Eurodac' and the politics of biometric identification , 1999, Ethics and Information Technology.

[4]  Christoph von der Malsburg,et al.  Strategies and Benefits of Fusion of 2D and 3D Face Recognition , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops.

[5]  Rama Chellappa,et al.  Discriminant Analysis for Recognition of Human Face Images (Invited Paper) , 1997, AVBPA.

[6]  P. Jonathon Phillips,et al.  An Introduction to Evaluating Biometric Systems , 2000, Computer.

[7]  P.A.E. Breij Ethical Aspects of Facial Recognition Systems in Public Places , 2004 .

[8]  Ray Bingham,et al.  The face-off. , 2008, Health affairs.

[9]  A. M. Burton,et al.  100% Accuracy in Automatic Face Recognition , 2008, Science.

[10]  Shimon Ullman,et al.  Face Recognition: The Problem of Compensating for Changes in Illumination Direction , 1997, IEEE Trans. Pattern Anal. Mach. Intell..

[11]  V. Kshirsagar,et al.  Face recognition using Eigenfaces , 2011, 2011 3rd International Conference on Computer Research and Development.

[12]  P. Jonathon Phillips,et al.  Face recognition vendor test 2002 , 2003, 2003 IEEE International SOI Conference. Proceedings (Cat. No.03CH37443).

[13]  Ralph Gross,et al.  Quo vadis Face Recognition , 2001 .

[14]  Alice J. O'Toole,et al.  Face recognition algorithms and the other-race effect: computational mechanisms for a developmental contact hypothesis , 2002, Cogn. Sci..

[15]  David R. Lease Factors Influencing the Adoption of Biometric Security Technologies by Decision Making Information Technology and Security Managers , 2005 .

[16]  Mike Bone,et al.  Face Recognition at a Chokepoint: Scenario Evaluation Results , 2002 .

[17]  Natalie Zemon Davis,et al.  The Return of Martin Guerre , 1983 .

[18]  Lucia Zedner :Against Prediction: Profiling, Policing, and Punishing in an Actuarial Age , 2008 .

[19]  Bruce A. Draper,et al.  How features of the human face affect recognition: a statistical comparison of three face recognition algorithms , 2004, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004..

[20]  Bruce A. Draper,et al.  Focus on quality, predicting FRVT 2006 performance , 2008, 2008 8th IEEE International Conference on Automatic Face & Gesture Recognition.

[21]  Tomaso A. Poggio,et al.  Face recognition: component-based versus global approaches , 2003, Comput. Vis. Image Underst..

[22]  Bruce A. Draper,et al.  A Statistical Assessment of Subject Factors in the PCA Recognition of Human Faces , 2003, 2003 Conference on Computer Vision and Pattern Recognition Workshop.

[23]  Xiaoguang Lu,et al.  Image Analysis for Face Recognition , 2005 .

[24]  Lucas D. Introna,et al.  Picturing Algorithmic Surveillance: The Politics of Facial Recognition Systems , 2002, Surveillance & Society.

[25]  Azriel Rosenfeld,et al.  Face recognition: A literature survey , 2003, CSUR.

[26]  Frederick Schauer,et al.  Profiles, Probabilities, and Stereotypes , 2006 .

[27]  Bernard E. Harcourt,et al.  A Reader's Companion to Against Prediction: A Reply to Ariela Gross, Yoram Margalioth, and Yoav Sapir on Economic Modeling, Selective Incapacitation, Governmentality, and Race , 2008, Law & Social Inquiry.

[28]  Alice J. O'Toole,et al.  FRVT 2006 and ICE 2006 large-scale results , 2007 .

[29]  David A. Wagner,et al.  Security and Privacy Issues in E-passports , 2005, First International Conference on Security and Privacy for Emerging Areas in Communications Networks (SECURECOMM'05).

[30]  H. Nissenbaum Privacy as contextual integrity , 2004 .

[31]  Henning Daum Influences of Image Disturbances on 2D Face Recognition , 2005, AVBPA.

[32]  Patrick J. Flynn,et al.  Overview of the face recognition grand challenge , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[33]  C. Norris From personal to digital : CCTV, the panopticon, and the technological mediation of suspicion and social control , 2005 .

[34]  G. Pike,et al.  When Seeing should not be Believing: Photographs, Credit Cards and Fraud , 1997 .