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Evaluation of Face Recognition System based on Scenarios  

Maeng, Doo-Lyel (한국인터넷진흥원)
Hong, Byung-Woo (중앙대학교 컴퓨터공학부)
Kim, Sung-Jo (중앙대학교 컴퓨터공학부)
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Abstract
It has been required to develop an accurate and reliable evaluation method for the performance of biometric systems as their use is getting popular. Among a number of biometric systems, face recognition is one of the most widely used techniques and this leads to develop a stable evaluation method for face recognition systems in order to standardize the performance of face recognition systems. However, it is considered as a difficult task to evaluation such systems due to a large number of factors that affect their performance. Thus, it may be infeasible to take into account all the environmental factors that are related to the performance of face recognition systems and this naturally suggests an evaluation method for the overall performance based on scenarios. In this paper, we have analyzed environmental factors that are related to the performance of general face recognition systems and proposed their evaluation method taking into account those factors. We have proposed an evaluation method based on scenario that considers the combination of individual environment factors instead of evaluating the performance of face recognition systems regarding each factor. Indeed, we have presented examples on the evaluation of face recognition systems based on scenario that takes into account overall environmental factors.
Keywords
Biometric; Face recognition; Evaluation system; Scenario-based evaluation system;
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1 Georghiades, A.S. and Belhumeur, P.N. and Kriegman, D.J., From Few to Many: illumination Cone Models for Face Recognition under Variable Lighting and Pose. IEEE Trans. Pattern Anal. Mach Intelligence 23(6): 643-660, 2001.   DOI   ScienceOn
2 P.J. Philips, A. Martin, C. L. Wilson, M. Przybocki, "An Introduction to Evaluating Biometric Systems," IEEE Computer, pp.56-63, Feb. 2000.
3 W. Gao, B. Cao, S. Shan, D. Zhou, X. Zhang, D. Zhao, "THe CAS-PEAL Large-Scale Chinese Face Database & Baseline Evaluations," ICT-VISION Joint Resarch & Development Laboratory for Face Recognition, Chinese Academy of Sciences, May 2004.
4 A. J. Mansfield, J. L. Wayman, "Best Practices in Testing and Reporting Performance of Bimoetric Devices," Centre for Mathematics and Scientific Computing, National Physical Laboratory, Aug. 2002.
5 JH. Hong, EK. Yun and SB. Cho, "A Study on Evaluation Methodology for Biometrics Systems," Dept. of Computer Science, Yonsei University.
6 P.J. Philipse, W.T. Scruggs, A.J. O'Toole,P.J. Flynn, K.W. Bowyer, C.L. Schott, M. Sharpe, "FRVT 2006 and ICE 2006 Large-Scale Results," National Institute of Standards and Techology, Mar. 2007.
7 Modernising Government, Biometrics for Identification and Authentication Advice on Product Selection - Issue 2.0, UK Biometrics Working Group, 22 Mar. 2002.
8 T. Mansfield, G. Kelly, D and Chanler, J. Kane, "Biometric Product Testing Final Report," GESG/BWG Biometric Test Programme, 19 March 2001.
9 P.J. Phillips, P.J. Rauss, S.Z. Der, "FERET (Face Recognition Technology) Recognition Algorithm Development & Test Resutls," Army Research Laboratory, Oct. 1996.
10 H.S. Lee, S. Park, B.N. Kang, J. Shin, J. Lee, H. Je, B, Jun, D. Kim, "The POSTECH Face Database (PF07)," Dept. of Computer Science & Engineering, Pohang University Science and Technology, Feb. 2008.
11 P.J. Phillips, Hyeonjoon Moon, and S.A Rizvi, The FERET Evaluation Methodology for Face-Recognition Algorithms, IEEE Trans. Pattern Anal. Mach Intelligence, Vol.22. No.10., Oct. 2000.