Journal of the Institute of Electronics Engineers of Korea SC (전자공학회논문지SC)

The Institute of Electronics and Information Engineers (대한전자공학회)
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A Study on the Performance Evaluation based on Modular Face Recognition System

모듈화된 얼굴인식 시스템을 이용한 성능 시험에 관한 연구

  • Hong Tae-Hwa (Dept. of Electrical Electronic Engineering, Yonsei University) ;
  • Moon Hyeon-Joon (School of Computer Engineering Department of Computer Software, Sejong University) ;
  • Shin Yong-Nyuo (Korea Information Security Agency) ;
  • Lee Dong-Geun (Korea Information Security Agency) ;
  • Kim Jae-Sung (Korea Information Security Agency)
  • 홍태화 (연세대학교 전기전자공학과) ;
  • 문현준 (세종대학교 소프트웨어공학과) ;
  • 신용녀 (한국정보보호진흥원) ;
  • 이동근 (한국정보보호진흥원) ;
  • 김재성 (한국정보보호진흥원)
  • Published : 2005.07.01
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Abstract

Face recognition out of biometrics is considerable interesting due to high performance and accessibility in applications to security such as access control and banking service. Therefore, a study on the protocol of the performance test is an important issue to understand the art-of state and to show a direction in future works, in addtion to developing algorithms. We present a design criterion for the performance test protocol of face recognition system and show the result of experiment executed on identification and verification scenario based on PCA algorithm and XM2VTS DB

생체인식 기술 중 변별력과 활용성, 편리성이 뛰어난 얼굴인식 기술은 출입통제나 금융관련 업무 처리와 같이 보안관련 응용분야에서 필요성이 급속도로 요구되고 있다. 따라서 얼굴인식 알고리즘의 발전과 더불어 현 기술의 상태를 파악하고 발전 방향을 제시하기 위한 성능 시험 방법에 대한 연구 또한 중대한 이슈로 부각되고 있다. 본 연구에서는 얼굴인식 시스템의 성능 시험을 위한 프로토콜의 설계 기준을 제시하고 XM2VTS 데이터베이스를 사용하여 PCA를 기반으로 한 인식 시스템을 디자인하여 Identification 시나리오와 Verification 시나리오 상에서 성능 시험 결과를 제시한다.

Keywords

References

  1. H. Moon and P, J. Phillips, 'Computational and performance aspects of projection-based face recognition algorithms', Perception, vol. 30, pp. 303-321, 2001 https://doi.org/10.1068/p2896
  2. H. Moon, 'Performance Evaluation Methodology for Face Recognition Algorithms', Ph.D thesis, Dept. of Computer Science and Engineering, SUNY Buffalo, 1999
  3. M. Turk and A. Pentland, 'Eigenfaces for recognition', J. Cognitive Neuroscience, vol. 3, pp. 71-86, 1991 https://doi.org/10.1162/jocn.1991.3.1.71
  4. Belhumeur P. N., Hespanha J. P., Kriegmaqn D. J., 'Eigenfaces vs. Fisherfaces : recognition using class specific Linear Projection,' IEEE Trans. on Pattern Analysis and Machine Intell., Vol.19, No.7, pp.711-720, 1997 https://doi.org/10.1109/34.598228
  5. S. Gutta, J. Huang, D. Singh, I. Shah, B. Takacs, and H. Wechsler, 'Benchmark studies on face recognition', In M. Bichsel, editor, International Workshop on Automatic Face and Gesture Recognition, 1995
  6. 'Best Practices in Testing and Reporting Performance of Biometric Devices', NPL Report CMSC, version 2.01, 2002
  7. 'Face Recognition Vendor Test 2002', Evaluation Reports, 2003
  8. I. T. Jolliffe, Principal Component Analysis, Springer-Verlag, 1986
  9. H. Moon and J. Kim, 'Biometrics identification and verification using projection-based face recognition system', Proceedings of WISA 2003, pp. 380-394, 2003
  10. P. J. Phillips, H. Moon, S. Rizvi, and P. Rauss, 'The FERET evaluation methodology for face-recognition algorithms', IEEE Transactions on Pattern Analysis and Machine Intelligence, pp. 1090-1104, 2000 https://doi.org/10.1109/34.879790
  11. H. Moon, 'Biometics Person Authentication using Projection-based Face Recognition System in Verification Scenario', Proceedings of ICBA 2004, pp. 207-213, 2004
  12. K. Messer, J, Matas, J, Kittler, J, Luettin, and G. Maitre, 'XM2VTSDB: The Extended MeVTS Database,' Proc. of International Conference on Audio- and Video-Based Person Authentication, pp. 72-77, 1999
  13. P. J. Phillips, P. Rauss, and S. Der, 'FERET (face recognition technology) recognition algorithm development and test report', Technical Report ARL-TR-995, U.S. Army Research Laboratory, 1996