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Tytuł artykułu

Complex colour detection methods used in skin detection systems

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
In this paper we present high computational complexity algorithms for detecting skin and non-skin colour. Because of their complexity they are not suitable for nowadays mobile devices but can be used in systems working on more demanding machines. The selection and implementation of algorithms gives accuracy about 80-90%.
Rocznik
Strony
40--52
Opis fizyczny
Bibliogr. 31 poz., rys., tab.
Twórcy
  • Computer Sciences, University of Lodz, Poland
autor
  • Computer Sciences, University of Lodz, Poland
Bibliografia
  • [1] Crowley J. L., Coutaz J. (1997) Vision for Man Machine Interaction, Robotics and Autonomous Systems, Vol. 19, 347-358.
  • [2] Kjeldsen R., Kender. J. (1996) Finding Skin in Color Images, Proceedings of the Second International Conference on Automatic Face and Gesture Recognition, 312-317.
  • [3] Nachlieli H., Bergman R., Greig D., Staelin C., Oicherman B., Ruckenstein G., Shaked D. (2009) Skin-Sensitive Automatic Color Correction, SIGGRAPH, New Orleans.
  • [4] Qian Chen, Haiyuan Wu, Masahiko Yachida (1995) Face detection by fuzzy pattern matching, In Proc. of Fifth Intl.Conf. on Computer Vision, 591–596, Cambridge.
  • [5] Symon D’Oyly Cotton, Ela Claridge (1996) Do all human skin colors lie on a defined surface within LMS space? Technical Report CSR-96-01, School of Computer Science, Univ. of Birmingham, UK.
  • [6] Van Gemert M. J. C., Jacques S. L., Sterenborg H. J. C. M., Star W. M. (1989) Skin optic,. IEEE Trans. On Biomedical Engineering, 36 (12): 1146–1154.
  • [7] Jebara T. S., Pentland A. (1997) Parameterized structure from motion for 3d adaptive feedback tracking of faces, In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pages 144–150, San Juan, Puerto Rico.
  • [8] Schiele B., Waibel A. (1995) Gaze tracking based on face-color, In Proceedings of the International Workshop on Automatic Face- and Gesture-Recognition, 344–349, Zurich, Switzerland.
  • [9] Terrillon J-C., David M., Akamatsu S. (1998) Automatic Detection of HumanFaces in Natural Scene Images by Use of a Skin Color Model and of Invariant Moments. In Proc. of the Third International Conference on Automatic Face and Gesture Recognition, Nara, Japan, 112-117.
  • [10] Zeng H. (2011) Preferred skin colour reproduction. PhD thesis, University of Leeds.
  • [11] Zarit B. D., Super B. J., Quek F. K. H. (1999) Comparison of five color models in skin pixel classification, In ICCV’99 Int’l Workshopon recognition, analysis and tracking of faces and gestures in Real-Time systems, 58–63.
  • [12] Poynton C. A. (1995) Frequently asked questions about colour. In: ftp://www.inforamp.net/pub/users/poynton/doc/colour/ColorFAQ.ps.gz
  • [13] Ahlberg J. (1999) A system for face localization and facial feature extraction, Tech. Rep. LiTH-ISY-R-2172, Linkoping University.
  • [14] Phung S. L., Bouzerdoum A., Chai D. (2002) A novel skin color model in ycbcr color space and its application to human face detection, In IEEE International Conference on Image Processing (ICIP’2002), Vol. 1, 289–292.
  • [15] Hsu R.-L., Abdel-Mottaleb M., Jain A. K. (2002) Face detection in color images, IEEE Trans. Pattern Analysis and Machine Intelligence 24, 5, 696–706.
  • [16] Brown D., Craw I., Lewthwaite J. (2001) A som based approach to skin detection with application in real time systems, In Proc. of the British Machine Vision Conference.
  • [17] Abdullah-Al-Wadud M., Chae O. (2007) Region-of-interest selection for skin detection based applications, In Proceedings of the International Conference on Convergence Information Technology (ICCIT ’07), pp. 1999–2004, Gyeongju, Korea.
  • [18] Bera A. K., Jarque C. M. (1980) Efficient tests for normality, homoscedasticity and serial independence of regression residuals, Economics Letters, vol. 6 (3), 255–259.
  • [19] Bera A. K., Jarque C. M. (1981) Efficient tests for normality, homoscedasticity and serial independence of regression residuals: Monte Carlo Evidence, Economics Letters, vol. 7, no. 4, 313–318.
  • [20] Judge G. G., Hill R. C., Griffiths W. E., Lutkepohl H., Lee T. C. (1988) Introduction to he Theory and Practice of Econometrics, JohnWiley & Sons, New York, NY, USA, 3rd edition.
  • [21] Jones M. J., Rehg J. M. (1999) Statistical color models with application to skin detection, In Proc. of the CVPR ’99, vol. 1, 274–280.
  • [22] Chai D., Bouzerdoum A. (2000) A bayesian approach to skin color classification in ycbcr color space, In Proceedings IEEE Region Ten Conference (TENCON’2000), vol. 2, 421–424.
  • [23] Viola P., Jones M. (2004) Robust real-time face detection, International Journal of Computer Vision, vol. 57, no. 2, pp. 137–154.
  • [24] Martinez B. O. (2004) Semantic retrieval of memory color content, Ph.D. dissertation, Universitat Autonoma de Barcelona.
  • [25] Luo Ronnier G. C., Li C. (2006) Uniform colour spaces based on ciecam02 colour appearance model, Color Research and Application, vol. 31, no. 4, 320–330.
  • [26] Lee J. Y., Yoo S. I. (2002) An elliptical boundary model for skin color detection, In Proc. of the 2002 International Conference on Imaging Science, Systems and Technology.
  • [27] Yang M.-H., Ahuja N. (1998) Detecting human faces in color images, In International Conference on Image Processing (ICIP), vol. 1, 127–130.
  • [28] Menser B., Wien M. (2000) Segmentation and tracking of facial regions in color image sequences, In Proc. SPIE Visual Communications and Image Processing 2000, 731–740.
  • [29] Saber E., Tekalp A. (1998) Frontal-view face detection and facial feature extraction using color, shape and symmetry based cost functions, Pattern Recognition Letters 19, 8, 669–680.
  • [30] Gomez G., Morales E. (2002) Automatic feature construction and a simple rule induction algorithm for skin detection, In Proc. of the ICML Workshop on Machine Learning in Computer Vision, 31–38.
  • [31] Stawska Z., Milczarski P. Algorithms and methods used in skin and face detection suitable for mobile applications, in preprint.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-8df46c79-1d79-4761-a806-09bba59e625c
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