DOI QR코드

DOI QR Code

인터랙티브 TV 컨트롤 시스템을 위한 근적외선 영상에서의 얼굴 검출

Face Detection for Interactive TV Control System in Near Infra-Red Images

  • 원철호 (경일대학교 첨단의료기학과)
  • Won, Chul-Ho (Department of High Tech. Medical System, Kyungil University)
  • 투고 : 2011.09.19
  • 심사 : 2011.10.18
  • 발행 : 2011.11.30

초록

In this paper, a face detection method for interactive TV control system using a new feature, edge histogram feature, with a support vector machine(SVM) in the near-infrared(NIR) images is proposed. The edge histogram feature is extracted using 16-directional edge intensity and a histogram. Compared to the previous method using local binary pattern(LBP) feature, the proposed method using edge histogram feature has better performance in both smaller feature size and lower equal error rate(EER) for face detection experiments in NIR databases.

키워드

참고문헌

  1. S. Gundimada and V. Asari, "Face detection technique based on rotation invariant wavelet features", Int's Conf., Information Technology : Coding and Computing, vol. 2, pp. 157-158, Apr. 2004.
  2. F. Y. Shih and C. F. Chuang, "Automatic extraction of head and face boundaries and facial feature", Information Sciences, vol. 158, pp. 117-130, Jan. 2004. https://doi.org/10.1016/j.ins.2003.03.002
  3. Y. J. Fen and P. F. Shi, "Face detection based on kernel fisher discriminant analysis", Proc. sixth IEEE Int'l Conf., Automatic Face and Gesture Recognition, pp. 381-384, May. 2004.
  4. T. Ojala, M. Pietik inen, and T. Maenpaa, "Multiresolution gray-scale and rotation invariant texture classification with local binary patterns" , IEEE Transaction on Pattern Analysis and Machine intelligence, vol. 24, pp. 971-987, 2002. https://doi.org/10.1109/TPAMI.2002.1017623
  5. C. Shan, S. Gong, and P. W. McOwan, "Facial expression recognition based on local binary pattern: A comprehensive study", Image and Vision Computing, vol. 27, pp. 803-816, 2009. https://doi.org/10.1016/j.imavis.2008.08.005
  6. T. Ahonen, A. Hadid, and M. Pietikainen, "Face recognition with local binary patterns", ECCV, pp. 469-481, 2004.
  7. G. Zhang, X. Huang, S. Z. Li, Y. Wang, and X. Wu, "Boosting local binary pattern based face recognition", Proc. Advances in Biometric Person Authentication, vol. 3338, pp. 179-186, 2004. https://doi.org/10.1007/978-3-540-30548-4_21
  8. T. Ahonen, A. Hadid, and M. Pietik inen, "Face description with local binary patterns: Application to face recognition", IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 28, no. 12, Dec. 2006, pp. 2037-2041. https://doi.org/10.1109/TPAMI.2006.244
  9. T. Ahonen and M. Pietikainen, "Soft histograms for local binary patterns", Proc. Finnish Signal Processing Symposium(FINSIG 2007), Oulu, Finland, 2007.
  10. Y. Li, S. Gong, J. Sharrah, and H. Liddell, " Support vector machine based multi-view face detection and recognition", Image and Vision computing, vol. 22, pp. 413-127, 2004. https://doi.org/10.1016/j.imavis.2003.12.005
  11. Y. J. Feng and P. F. Shi, "Face detection based on kernel fisher discriminant analysis", Proc. sixth IEEE Int'l conf., Automatic Face and Gesture Recognition, pp. 381-384, May. 2004.
  12. C. A. Waring and X. Liu, "Face detection using spectral histograms and SVMs", IEEE Trans. Systems, Man and Cybernetics, vol. 99, pp. 467-476, Apr. 2005.