Journal of Korea Multimedia Society (한국멀티미디어학회논문지)

Korea Multimedia Society (한국멀티미디어학회)
권호 표지

Evaluation of Face Recognition System based on Scenarios

얼굴인식 시스템의 시나리오 기반 평가 방법론

  • Received : 2009.08.10
  • Accepted : 2010.01.06
  • Published : 2010.04.30
Download PDF
⟨ Previous Next ⟩

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.

바이오인식 (Biometrics) 시스템의 사용이 보편화 되면서 그들의 성능에 대해서 보다 정확하고 안정된 평가를 제공하는 방법이 요구된다. 다양한 바이오 인식 기술 중에서 얼굴인식 기술이 널리 사용되고 있으며 안정적인 얼굴인식 시스템의 개발을 위한 지표를 마련하고 얼굴인식 시스템이 제공해야 하는 성능에 대한 기준을 제시하기 위해서 얼굴인식 시스템의 성능을 평가해야 할 필요성이 커지게 되었다. 하지만 얼굴인식 시스템의 성능에 영향을 미치는 요소들이 매우 다양하고 복잡하기 때문에 얼굴인식 시스템의 성능을 평가하는 것은 어려운 일이다. 그렇기 때문에 이러한 환경요소에 대해서 개별적으로 평가하는 것보다 종합적으로 얼굴인식 시스템의 활용 시나리오를 기반으로 평가하는 것이 보다 효율적이고 효과적이다. 이 논문에서는 얼굴인식 시스템에 영향을 미치는 환경변수들을 분석하고 그 환경변수들을 고려하는 얼굴인식 시스템에 대한 평가방법을 제안하는 것을 목적으로 한다. 특별히 환경변수들을 개별적으로 평가하는 것이 아니고 그들의 조합을 고려하는 시나리오를 기반으로 평가하는 방법을 제안한다. 또한 일반적인 환경을 가정하는 시나리오 예시를 통해서 얼굴인식 시스템을 종합적인 환경변수를 고려하여 평가하는 것을 보여주었다.

Keywords

Acknowledgement

Supported by : 한국과학재단

References

  1. Modernising Government, Biometrics for Identification and Authentication Advice on Product Selection - Issue 2.0, UK Biometrics Working Group, 22 Mar. 2002.
  2. T. Mansfield, G. Kelly, D and Chanler, J. Kane, "Biometric Product Testing Final Report," GESG/BWG Biometric Test Programme, 19 March 2001.
  3. JH. Hong, EK. Yun and SB. Cho, "A Study on Evaluation Methodology for Biometrics Systems," Dept. of Computer Science, Yonsei University.
  4. P.J. Philips, A. Martin, C. L. Wilson, M. Przybocki, "An Introduction to Evaluating Biometric Systems," IEEE Computer, pp.56-63, Feb. 2000.
  5. 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.
  6. 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.
  7. 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.
  8. 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.
  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. 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. https://doi.org/10.1109/34.927464