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On the generation of graph representation of hand postures for syntactic pattern recognition

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Języki publikacji
EN
Abstrakty
EN
The results of research into construction of a method that generates an IE-graph [8] representation of hand postures are presented in the paper. The method allows one to represent hand postures of the Polish Sign Language with a class of graphs that can be parsed with an efficient ETPL(k) graph syntax analyzer introduced in [6].
Rocznik
Strony
71--84
Opis fizyczny
Bibliogr. 26 poz.
Twórcy
  • Jagiellonian University, Chair of Information Technology Systems, ul. F. Straszewskiego 27, 31-110 Cracow, Poland, s.myslinski@mfpartners.pl
Bibliografia
  • [1] Bauer B., Kraiss K.-F.: Towards an automatic sign language recognition system using subunits. In GW'01: Revised Papers from the International Gesture Workshop on Gesture and Sign Languages in Human-Computer Interaction, volume 2298 of Lecture Notes In Computer Science, pages 64-75, London, 2002 Springer-Verlag.
  • [2] Bretzner L., Lindeberg T.: Qualitative multiscale feature hierarchies for object tracking. In SCALE-SPACE'99: Proc. 2nd Int. Conf. Scale-Space Theories Comput. Vision, pages 117-128, 1999.
  • [3] Flasiński M.: Parsing of edNLC-graph grammars for scene analysis. Pattern Recognit., 21(6):623-629, 1988.
  • [4] Flasiński M.: Characteristics of edNLC-graph grammar for syntactic pattern recognition. Comput. Vision Graph. Image Process., 47(1):1-21, 1989.
  • [5] Flasiński M.: Distorted pattern analysis with the help of node label controlled graph languages. Pattern Recognit., 23(7):765-774, 1990.
  • [6] Flasiński M.: On the parsing of deterministic graph languages for syntactic pattern recognition. Pattern Recognit., 26:1-16, 1993.
  • [7] Flasiński M.: Use of graph grammars for the description of mechanical parts. Computer-Aided Design, 27(6):403-433, 1995.
  • [8] Flasiński M.: Power properties of NLC graph grammars with a polynomial membership problem. Theor. Comput. Sci., 201:189-231, 1998.
  • [9] Flasiński M.: Inference of parsable graph grammars for syntactic pattern recognition. Fund. Inform., 80:379-413, 2007.
  • [10] Flasiński M., Jurek J.: Dynamically programmed automata for quasi context sensitive languages as a tool for inference support in pattern recognition-based real-time control expert systems. Pattern Recognit., 32(4):671-690, 1999.
  • [11] Flasiński M., Kotulski L.: On the use of graph grammars for the control of a distributed software allocation. The Comput. Journal, 35(4):167-175, 1992.
  • [12] Flasiński M., Lewicki G.: The convergent method of constructing polynomial discriminant functions for pattern recognition. Pattern Recognit., 24(10):1009-1015, 1991.
  • [13] Flasiński M., Schaefer R., Toporkiewicz W.: Optimal stochastic scaling of cae parallel computations. Lect. Notes Comput. Sci., 1424:557-564, 1998.
  • [14] Holden E.-J., Owens R.: Visual sign language recognition. Lect. Notes Comput. Sc., 2032:270-287, 2001.
  • [15] Huang T. S., Pavlovic V.: Hand gesture modeling, analysis and synthesis. In Int. Workshop on Automatic Face and Gesture Recognition, Zurich, Switzerland, May 1995.
  • [16] Janssens D., Rozenberg G., Verraedt R.: On sequential and parallel node-rewriting graph grammars. Computer Vision, Graphics, and Image Processing, 18:279-304, 1982.
  • [17] Janssens D., Rozenberg G., Verraedt R.: On sequential and parallel node-rewriting graph grammars II. Computer Vision, Graphics, and Image Processing, 23(3):295-312, 1983.
  • [18] Krüger M., von der Malsburg C., Würtz R. P.: Self-organized evaluation of dynamic hand gestures for sign language recognition. In R. P. Würtz, editor, Organic Computing. Springer, 2007.
  • [19] Kuch J., Huang T. S.: Vision based hand modeling and tracking for virtual teleconferencing and telecollaboration. ICCV '95: Proc. 5th Int. Conf. On Computer Vision, page 666, Washington, DC, USA, 1995. IEEE Computer Society.
  • [20] Lee J., Kunii T. L.: Model-based analysis of hand posture. IEEE Comput. Graph. Appl., 15(5):77-86, 1995.
  • [21] Marnik J. M.: The polish finger alphabet hand postures recognition using elastic graph matching. In Innovations in Hybrid Intelligent Systems, volume 45 of Advances in Soft Computing, pages 454-461, 2008.
  • [22] Ogiela M. R., Tadeusiewicz R., Ogiela L.: Graph image language techniques supporting radiological, hand image interpretations, Computer Vision and Image Understanding, 103(2):112-120, 2006.
  • [23] Ogiela M. R., Tadeusiewicz R., Ogiela L.: Image languages in intelligent radiological palm diagnostics, Pattern Recognit., 39(11):2157-2165, 2006.
  • [24] Tadeusiewicz R., Ogiela M. R.: Modern Computational Intelligence Methods for the Interpretation of Medical Images, Springer-Verlag, 2008.
  • [25] Triesch J., von der Malsburg C.: A gesture interface for human-robot-interaction. In 3rd IEEE Int. Conf. on Automatic Face and Gesture Recognition, pages 546-551, 14-16 April 1998.
  • [26] Triesch J., von der Malsburg C.: Classification of hand postures against complex backgrounds using elastic graph matching. Image and Vision Computing, 20(13):937-943, 2002.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-LOD9-0009-0006
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