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Ohzeki Kazuo (Graduate School of Engineering and Science, Shibaura Institute of Technology, Tokyo), Aoyama Ryota (Graduate School of Engineering and Science, Shibaura Institute of Technology, Tokyo), Hirakawa Yutaka (Graduate School of Engineering and Science, Shibaura Institute of Technology, Tokyo)
Minimum Variance Method to Obtain the Best Shot in Video for Face Recognition
Annals of Computer Science and Information Systems, 2015, vol. 5, s. 869-874, rys., bibliogr. 17 poz.
Słowa kluczowe
This paper describes a face recognition algorithm using feature points of face parts, which is classified as a feature-based method. As recognition performance depends on the combination of adopted feature points, we utilize all reliable feature points effectively. From moving video input, well-conditioned face images with a frontal direction and without facial expression are extracted. To select such well-conditioned images, an iteratively minimizing variance method is used with variable input face images. This iteration drastically brings convergence to the minimum variance of 1 for a quarter to an eighth of all data, which means 3.75-7.5 Hz by frequency on average. Also, the maximum interval, which is the worst case, between the two values with minimum deviation is about 0.8 seconds for the tested feature point sample.(original abstract)
Pełny tekst
  1. Rabia Jafri and Hamid R Arabnia, "A Survey of Face Recognition Techniques", Journal of information Processing Systems Volume: 5, No: 2, pp. 41-68, 2009.
  2. Bonnen, K. Klare, B.F. Jain, A.K., "Component- Based Representation in Automated Face Recognition", IEEE Transactions on Information Forensics and Security, Vol.8, No.1 pp.239-253, Jan. 2013.
  3. JCB 2014 Conference report %20Conference/IJCB14_Conference_Report.pdf
  4. Patrick J. Grother; George W. Quinn; P J. Phillips, "Report on the Evaluation of 2D Still-Image Face Recognition Algorithms", NIST Interagency/Internal Report (NISTIR) - 7709 June, 2010.
  5. M. Ngan and P. Grother, "Face Recognition Vendor Test (FRVT) Performance of Automated Age Estimation Algorithms", NIST Interagency Report 7995 Mar 2014.
  6. Patrick Grother Mei Ngan, "Face Recognition Vendor Test (FRVT) Performance of Face Identification Algorithms" NIST Interagency Report 8009 May 2014.
  7. Carl Gohringer, "Advances in Face Recognition Technology and its Application in Airports", Allevate Limited. Pp.1-10., 17 Jul, 2012.
  8. Drira, H. Ben Amor, B. ; Srivastava, A. ; Daoudi, M. ; Slama, R.," 3D Face Recognition under Expressions, Occlusions, and Pose Variations", IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 35, ,Issue: 9, pp.2270 - 2283 Feb. 2013.
  9. Toderici, G.; Passalis, G. ; Zafeiriou, S. ; Tzimiropoulos, G., "Bidirectional relighting for 3D-aided 2D face recognition", Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2721-2728, 2010 June 2010
  10. Guillaumin, M. ; Verbeek, J. ; Schmid, C.," Is that you? Metric Learning Approaches for Face Identification", Proc. of IEEE 12th International Conference on Computer Vision, 2009 pp. 498-505, Sept. 2009
  11. Kazuo Ohzeki, YuanYu Wei, Yutaka Hirakawa, Toru Sugimoto, "Authentication System using Encrypted Discrete Biometrics Data", Proceedings of TRUST 2014 Greece Springer LNCS 8564 pp.210-211 June 30-July2 2014.
  12. Kazuo Ohzeki, Masahiro Takatsuka, Masaaki Kajihara, Yutaka Hirakawa, Kiyotsugu Sato, "On the False Rejection Ratio of Face Recognition Based on Automatic Detected Feature Points", Proc. international workshops on "Pattern Recognition and Image Understanding"OGRW-9 Mo.3-1, ogrw2014_024_Ohzeki.pdf Dec.2014.
  13. Stephen Milborrow, Fred Nicolls, "Locating Facial Features with an Extended Active Shape Model", Proceeding of ECCV Part IV pp.504- 513, Springer-Verlag Berlin, Heidelberg 2008
  14. S. Milborrow and F. Nicolls, "Active Shape Models with SIFT Descriptors and MARS", International Conference on Computer Vision Theory and Applications (VISAPP) pp.380-387. 2014
  15. Howell and H. Buxton, "Towards unconstrained face recognition from image sequences," in Proceedings of the Second IEEE International Conference on Automatic Face and Gesture Recognition, 1996, pp.224-229.
  16. L. Torres, "Is there any hope for face recognition?" in Proc. of the 5th International Workshop on Image Analysis for Multimedia Interactive Services (WIAMIS 2004). Lisboa, Portugal, 2004.
  17. Yasuko Tanaka, Eigo Miyazaki, and Kazuo Ohzeki, "Feature Point Analysis Using Facial Parts for Face Recognition", National Convention, D-12-36 Institute of Electronics, Information, and Communication Engineers Mar. 2011 (in Japanese
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