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Tytuł artykułu

Facial portraits matching by means of two-dimensional CCA and PLS

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Paper presents implementation of the method of two-dimensional canonical correlation analysis and two-dimensional partial least squares applied to image matching. Both methods are based on representing the image as the sets of its rows and columns and implementation of CCA using these sets (hence we named the methods as CCArc and PLSrc). CCArc and PLSrc features simple implementation and lesser complexity than other known approaches. In applications to biometrics, CCArc and PLSrc are suitable to solving the problems when dimension of images (dimension of feature space) is greater than number of images, i.e. Small Sample Size problem (SSS). The paper demonstrates high efficiency of CCArc and PLSrc for a number of computer experiments using benchmark image databases.
Rocznik
Tom
Strony
69--86
Opis fizyczny
Bibliogr. 21 poz., rys., tab.
Twórcy
autor
autor
  • West Pomeranian University of Technology, Szczecin, Faculty of Computer Science and Information Technologies
Bibliografia
  • [1] Hotelling H. Relations between two sets of variates. Biometrika 28, 1936, pp. 321–377.
  • [2] Wold S. Nonlinear estimation by iterative least squares procedures. In: Research Papers in Statistics. (F. N. David, ed.), 1966, pp. 411 – 444.
  • [3] Donner R., Reiter M., Langs G., Peloschek P., Bischof H. Fast Active Appearance Model Search Using Canonical Correlation Analysis. IEEE Transaction on PAMI, Vol. 28, No. 10, October 2006, pp. 1960 – 1964.
  • [4] Dong Yi, Rong Liu, RuFeng Chu, Zhen Lei, Stan Z. Li, Face Matching Between Near Infrared and Visible Light Images. Lecture Notes in Computer Science, Volume 4642, 2007, pp. 523-530.
  • [5] Shan C., Gong S., McOwan P. W. Fusing gait and face cues for human gender recognition. Neurocomputing No. 71, 2008, 1931– 1938
  • [6] Szaber M., Kamenskaya E. Face recognition systems for visible and infrared images with application of CCA (in Polish). Metody Informatyki Stosowanej, No. 3/2008, Vol. 16, 2008, pp. 223-236.
  • [7] Alın A., Kurt S., McIntosh A. R., Öniz A., Özgören M. Partial Least Squares Analysis in Electrical Brain Activity. Journal of Data Science 7(2009), pp. 99-110
  • [8] ISO/IEC JTC 1/SC 37 N 506: Biometric Data Interchange Formats, Part 5: Face Image Data. http://www.icao.int/mrtd/download/technical.cfm
  • [9] Borga M. Canonical Correlation a Tutorial. January 12, 2001. http://www.imt.liu.se/~magnus/cca/tutorial/tutorial.pdf.
  • [10] Wegelin J. A. A survey of partial least squares (PLS) methods, with emphasis on the two-block case. Technical report No. 371, University of Washington, March 19, 2000.
  • [11] Forczmanski P., Kukharev G. Comparative analysis of simple facial features extractors. Journal Real-Time Image Processing, 2007, No. 1, pp. 239–255
  • [12] Lee Sun Ho, Choi Seungjin. Two-Dimensional CCA. IEEE Signal Processing Letters, Vol. 14, No. 10, October 2007, pp. 735 – 738.
  • [13] Zou Cai-rong, Sun Ning, Ji Zhen-hai, Zhao Li. 2DCCA: A Novel Method for Small Sample Size Face Recognition. IEEE Workshop on Application of Computer Vision, WACV’07, 2007, pp. 43-47.
  • [14] Kukharev G., Kamenskaya E. Two-Dimensional Canonical Correlation Analysis for Face Image Processing and Recognition. Metody Informatyki Stosowanej, Vol. 18, No. 3, 2009, pp. 103-112.
  • [15] Mao-Long Yang, Quan-Sen Sun, De-Shen Xia. Two-dimensional partial least squares and its application in image recognition. In: D.-S Huang et al. (Eds.): ICIC 2008, CCIS 15, pp. 208-215, 2008, Springer-Verlag Berlin Heidelberg 2008.
  • [16] Kukharev G., Forczmanski P. Facial Images Dimensionality Reduction and Recognition by Means of 2DKLT. Machine GRAPHICS & VISION, Vol.16, No. 3/4, 2007, pp. 401-425.
  • [17] Kukharev G., Miklasz M., Nguyen The Binh. Strategy of constructions a class Face Retrieval system, Metody Informatyki Stosowanej, 2007, 2 (Vol. 12), pp. 61–72.
  • [18] Liang Sun, Shuiwang Ji, Shipeng Yu, Jieping Ye. On the Equivalence Between Canonical Correlation Analysis and Orthonormalized Partial Least Squares. http://ijcai.org/papers09/Papers/IJCAI09-207.pdf
  • [19] Philips P.J., Wechler H., Huang J., Rauss P. The FERET database and Evaluation Procedure for Face Recognition algorithms. Image and Vision Computing, Vol. 16, No. 5, 1998, pp. 295-306.
  • [20] The Equinox IR Face database: http://www.equinoxsensors.com/products/HID.html
  • [21] Kukharev G. Biometric Systems: Methods and Means of People Identification. Sankt-Petersburg: Politechnika, 2001. 240 p (in Russian)
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BPS3-0016-0088
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