Hand Gesture Recognition in an Interval Fuzzy Approach
DOI:
https://doi.org/10.5540/tema.2007.08.01.0021Abstract
This paper introduces an interval fuzzy rule-based method for the recognition of hand gestures acquired from a data glove, with an application to the recognition of hand gestures of the Brazilian Sign Language. To deal with the uncertainties in the data provided by the data glove, an approach based on interval fuzzy logic is used. The method uses the set of angles of finger joints for the classification of hand configurations, and classifications of segments of hand gestures for recognizing gestures. The segmentation of gestures is based on the concept of monotonic gesture segment. Each gesture is characterized by its list of monotonic segments. The set of all lists of segments of a given set of gestures determine a set of finite automata able to recognize such gestures.References
[1] O. Al-Jarrah, A. Halawani, Recognition of gestures in arabic sign languageusing neuro-fuzzy systems, Artificial Intelligence, 133 (2001), 117–138.
L. Anderson, J. Purdy,W. Viant, Variations on a fuzzy logic gesture recognition algorithm, in “Proc. of the 2004 ACM SIGCHI Intl. Conf. on Advances in Computer Entertainment Technology”, pp. 280–283, Singapore, 2004.
T. Beelitz, B. Lang, C.H. Bischof, Efficient task scheduling in the parallel result-verifying solution of nonlinear systems, Reliable Computing, 12, No. 2(2006), 141–151.
B.C. Bedregal, A.C.R. Costa, G.P. Dimuro, Fuzzy rule-based hand gesture recognition, in “Artificial Intelligence in Theory and Practice” (M. Bramer,ed.), IFIP, Vol. 217, pp. 285-294, Springer, Boston, 2006.
B.C. Bedregal, A. Takahashi, The best interval representations of T-norms and automorphisms, Fuzzy Sets and Systems, 157, No. 42 (2006), 3220–3230.
O. Bimber, Continuous 6DOF gesture recognition: A fuzzy-logic approach, in “Proc. of VII Intl. Conf. in Central Europe on Computer Graphics, Visualization and Interactive Digital Media”, Vol 1, pp. 24–30, 1999.
N.D. Binh, T. Ejima, Hand gesture recognition using fuzzy neural network, in “Proc. of ICGST Intl. Conf. on Graphics, Vision and Image Processing”, pp. 1–6, Cairo, 2005.
L.F. Brito, “Por uma Gramática de Línguas de Sinais”, Tempo Brasileiro, Riode Janeiro, 1995.
G.P. Dimuro, A.C.R. Costa, Interval-based MDP for regulating interactions between two agents in multi-agent systems, in “Applied Parallel Computing” (J. Dongarra et al., eds.), LNCS, No. 3732, pp. 102–111, Springer, 2006.
G. Fang, W. Gao, D. Zhao, Large vocabulary sign language recognition based on FDT, IEEE Trans. Systems, Man and Cybern., 34 (2004), 305–314.
S.S. Fels, G.E. Hinton. Glove-talk: A neural network interface between a dataglove and a speech synthesizer. IEEE Trans. on Neural Networks, 4 (1993), 1–8.
P.S. Grigoletti, G.P. Dimuro, L.V. Barboza, Módulo Python para matemática intervalar, in “Resumos das Comunicações do XXIX CNMAC, Campinas,2006.” (available at http://ppginf.ucpel.tche.br/gracaliz/papers).
P. Hong, M. Turk, T.S. Huang, Gesture modeling and recognition using FSM, in “Proc. of IEEE Conf. on Face and Gesture Recognition”, pp. 410–415, Grenoble, 2000.
R.B. Keafort, V. Kreinovich (eds.), “Applications of Interval Computations”, Kluwer, Boston, 1996.
E.P Klement, R. Mesiar, E. Pap. “Triangular Norms”, Kluwer, Dordrecht, 2000.
S. Mitra, S.K. Pal, Fuzzy sets in pattern recognition and machine intelligence, Fuzzy Sets and Systems, 156 (2005), 381–386.
R.E. Moore, “Methods and Applications of Interval Analysis”, SIAM, Philadelphia, 1979.
J. Ou, X. Chen, J. Yang, Gesture recognition for remote collaborative physical tasks using tablet PCs, in “ Proc. of IX IEEE Intl. Conf. on Computer Vision, Work. on Multimedia Tech. in E-Learning and Collaborat”, Nice, 2003.
G. Rigoll, A. Kosmala, S. Eickeler, High perfomance real-time gesture recognition using HMM, in “Gesture and Sign Language in Human-Computer Interact.” (I. Wachsmuth et al., eds.), LNAI, No. 1371, pp. 69–80, Springer, 1998.
R.H.N. Santiago, B.C. Bedregal, B.M. Acióly. Formal aspects of correctness and optimality of interval computations, Formal Aspects of Computing, 18 (2006), 231–243.
M. Su, A fuzzy rule-based approach to spatio-temporal hand gesture recognition, IEEE Trans. Systems, Man and Cybernetics, Part C, 30 (2000), 276–281.
T. Yamaguchi, M. Yoshihara, M. Akiba, M. Kuga, N. Kanazawa, K. Kamata. Japanese sign language recognition system using information infrastructure, in Proc. of Joint 4th IEEE Intl. Conf. on Fuzzy Systems, 2nd Intl. Fuzzy Eng. Symp., vol. 5, pp. 65–66, Yokohama, 1995.
L.A. Zadeh, Theory of approximate reasoning, in “Machine Intelligence” (J. Hayes, D. Michie and L.I. Mikulich, eds.), pp. 149–194, Ellis Horwood, 1970.
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