Browse > Article

Multi-classifier Decision-level Fusion for Face Recognition  

Yeom, Seok-Won (Daegu University, Division of Computer and Communication Engineering)
Publication Information
Journal of the Institute of Electronics Engineers of Korea SP / v.49, no.4, 2012 , pp. 77-84 More about this Journal
Abstract
Face classification has wide applications in intelligent video surveillance, content retrieval, robot vision, and human-machine interface. Pose and expression changes, and arbitrary illumination are typical problems for face recognition. When the face is captured at a distance, the image quality is often degraded by blurring and noise corruption. This paper investigates the efficacy of multi-classifier decision level fusion for face classification based on the photon-counting linear discriminant analysis with two different cost functions: Euclidean distance and negative normalized correlation. Decision level fusion comprises three stages: cost normalization, cost validation, and fusion rules. First, the costs are normalized into the uniform range and then, candidate costs are selected during validation. Three fusion rules are employed: minimum, average, and majority-voting rules. In the experiments, unfocusing and motion blurs are rendered to simulate the effects of the long distance environments. It will be shown that the decision-level fusion scheme provides better results than the single classifier.
Keywords
face recognition; face classification; photon-counting LDA; decision-level fusion; blurring;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
연도 인용수 순위
1 M. T. Sadeghi, M. Samiei, and J. Kittler, "Fusion of PCA-Based and LDA-Based Similarity Measures for Face Verification," EURASIP Journal on Advances in Signal Processing, Vol. 2010.
2 Y. Pang, N. Yu, R. Zhang, J. Rong, and Z. Liu, "Fusion of SVD and LDA for Face Recognition," 2004 International Conference on Image Processing (ICIP), pp. 1417-1420, 2004.
3 D. D. Freedman, "Overview of Decision Level Fusion Techniques for Identification and Their Application," Proceedings of the American Control Conference, Baltimore, Maryland. (June 1994).
4 S. Yeom, "Multi-frame decision level fusion for face classification based on a photon-counting linear discriminant analysis," IS&T/SPIE Electronic Imaging, Vol. 7877, 2011.
5 S. Yeom, "Photon-counting linear discriminant analysis for face recognition at a distance," International Journal of Fuzzy Logic and Intelligent Systems, Under review.
6 http://www.cl.cam.ac.uk/research/dtg/attarchive /facedatabase.html.
7 MATLAB function reference, MathWorks.
8 조재수, 강현수, 김흥수, 김성득, "멀티미디어 신호 처리: 이론 및 실습," 사이텍 미디어, 2006.
9 D. L. Swets and J. Weng, "Using discriminant eigenfeatures for image retrieval," IEEE Trans. Pattern Analysis and Machine Intelligence. Vol. 18, pp. 831-836, 1996.   DOI   ScienceOn
10 P. N. Belhumer, J. P. Hespanha, and D. J. Kriegman, "Eigenfaces vs. Fisherfaces: recognition using class specific linear projection," IEEE Trans. Pattern Analysis and Machine Intelligence. Vol. 19, No. 7, pp. 711-720, 1997.   DOI   ScienceOn
11 김현철, 김대진, 방승양, "LDA 혼합 모형을 이용한 얼굴인식," 정보과학회논문지, 제32권 소프트웨어 및 응용, 제8호, 789 -794쪽, 2005년 8월.
12 홍은혜, 고병철, 변혜란, "PCA와 LDA를 이용한 실시간 얼굴 검출 및 검증 기법," 정보과학회논문지:소프트웨어 및 응용 제31권 제2호, 2004년 2월.
13 장혜경, 오선문, 강대성, "PCA 기반 LDA 혼합 알고리즘을 이용한 실시간 얼굴인식 시스템 구현," 전자공학회논문지, 제41권 SP편, 제4호, 473-478쪽, 2004년 7월.
14 R. O. Duda, P. E. Hart, and D. G. Stork, Pattern Classification 2nd ed., Wiley Interscience, New York, 2001.
15 K. Fukunaga, Introduction to Statistical Pattern Recognition 2nd ed., Academic Press, Boston, 1990.
16 S. Yeom, B. Javidi, and E. Watson, "Threedimensional distortion-tolerant object recognition using photon-counting integral imaging," Optics Express, Vol. 15, pp. 1513-1533, 2007.   DOI
17 염석원, "포톤 카운팅 선형판별법을 이용한 저해상도 얼굴 영상 인식," 대한전자공학회지, 제45권 SP편 제6호, pp. 597-602, 2008.
18 L. O. Jimenez, A. Morales-Morell, and A. Creus, "Classification of Hyperdimensional Data Based on Feature and Decision Fusion Approaches Using Projection Pursuit, Majority Voting, and Neural Networks," IEEE Trans. on Geoscience and Remote Sensing, Vol. 37, No. 3, pp. 1360-1366, 1999.   DOI   ScienceOn