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Semi-automatic human emotions recognition method based on I2D features

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
In the paper we present quite new approach to the problem of human emotion recognition with use of face images. We assume that basic emotions such as anger, disgust, fear, happiness, sadness, surprise are expressed by face mimic. Face images with the well defined emotions may be performed using the method based on geometrical wavelets (beamlets) in order to extract intrinsically two dimensional features, the most important ones from the Human Visual System point of view. Such an approach can be successfully applied in extraction process of the most important features that are responsible for recognition of basic elements of face (eyes, nose, lips, etc.). The listed elements of face have a little different location that depends on emotion expressed. It has been proved experimentally that it is possible using very small amount of information extracted from a face image, by the so-called beamlet extractor, to recognize emotion with high accuracy. Very promising results of experiments suggest that the method should be further investigated and improved.
Rocznik
Tom
Strony
215--222
Opis fizyczny
Bibliogr. 17 poz., rys., tab.
Twórcy
autor
  • Institute of Informatics, Silesian University, Będzińska 39, 41-200 Sosnowiec, Poland
autor
  • Institute of Informatics, Silesian University, Będzińska 39, 41-200 Sosnowiec, Poland
autor
  • Institute of Informatics, Silesian University, Będzińska 39, 41-200 Sosnowiec, Poland
Bibliografia
  • [1] DONOHO D. L., HUO X., Beamlet Pyramids: A New Form of Multiresolution Analysis, Suited for Extracting Lines, Curves and Objects from Very Noisy Image Data, Proceedings of SPIE, Vol. 4119, 2000.
  • [2] EKMAN P., FRIESEN W. V., Emotion in the human face: Guidelines for research and an integration of findings, New York, Pergamon Press, 1972.
  • [3] GABOR D., Guest Editorial, IRE Transactions on Information Theory, September, 1959.
  • [4] JIA X., NIXON M., S., Extending the Feature Vector for Automatic Face Recognition, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 17, No. 12, December 1995.
  • [5] KAISER P. K., The Joy of Visual Perception, http://www.yorku.ca/eye/thejoy.htm .
  • [6] KRIEGER G., ZETZSCHE C., Nonlinear Image Operators for the Evaluation of Local Intrinsic Dimensionality, IEEE Transactions on Image Processing, Special Issue on Nonlinear Image Processing, Vol. 5, No. 6, pp. 1026-1042, 1996.
  • [7] KOWNACKI A., Automatic Recognition of Emotions Basing On face’s Image, BSc Thesis, University of Silesia, Institute of Informatics, Sosnowiec, (in Polish), 2004.
  • [8] LISOWSKA A., Intrinsic Dimensional Selective Operator Based On Geomerical Wavelets, Journal of Applied Computer Science, Vol. 12, N0. 2, 2004.
  • [9] LISOWSKA A., Geometrical Wavelets and their Generalizations in Digital Image Coding and Processing, PhD Thesis, University of Silesia, Institute of Informatics, Sosnowiec, 2005.
  • [10] LISOWSKA A., KOTARSKI W., Automatic Perception of Significant Image Features Based on Psychology of Vision, Journal of Medical Informatics & Technologies, Vol. 7, pp. 31-40, 2004.
  • [11] MAKIEŁA M., Methods of Faces’ Image Identification Based on Characteristic Feature Points, MSc Thesis, Institute of Informatics, University of Silesia, Sosnowiec, (in Polish), 2002.
  • [12] MAKIEŁA M., KOTARSKI W, LISOWSKA A., Automatic Human Face Recognition Method Based on Geometrical Face Features, Journal of Medical Informatics & Technologies, Vol. 5, pp. MI-47 – MI-56, 2003.
  • [13] MITRA S. K., SICURANZA G. L., Nonlinear Image Processing, Academic Press, San Diego, 2001.
  • [14] PAŁECZKA D., The Artificial Empathy. The Automatic Recognition Based on Facial Expressions, MSc Thesis, Poznań University of Technology, Poznań 2000, http://www.cs.put.poznan.pl/dobek/empathy/.
  • [15] SHIN Y., Facial Expression Recognition Based Dimension Model Using Sparse Coding, Lecture Notes in Computer Science, Springer-Verlag, Vol. 3039, pp. 205-212, 2004.
  • [16] THE DATABASE OF FACES, http://www.uk.research.att.com/facedatabase.html .
  • [17] ZETZSCHE C., BARTH E., Fundamental Limits of Linear Filters in the Visual Processing of Two-Dimensional Signals, Vision Research, Vol. 30, pp. 1111-1117, 1990.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-PWA4-0012-0025
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