Abstract
A gesture is a motion that has special status in a domain or context. Recent interest in gesture recognition has been spurred by its broad range of applicability in more natural user interface designs. However, the recognition of gestures, especially natural gestures, is difficult because gestures exhibit human variability. We present a technique for quantifying this variability for the purposes of representing and recognizing gesture.
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References
A. V. Aho, J. E. Hoperoft, and J. D. Ullman. Data structures and algorithms. Addison-Wesley, Reading, 1983.
C. M. Bishop. Neural networks for pattern recognition. Clarendon Press, Oxford, 1995.
C. Bregler and S. M. Omohundro. Nonlinear image interpolation using surface learning. In G. Tesauro J. D. Cowan and J. Alspector, editors, Advances in neural information processing systems 6, pages 43–50, San Fransisco, CA, 1994. Morgan Kaufmann Publishers.
E. Catmull and R. Rom. A class of local interpolating splines. In R. Barnhill and R. Riesenfeld, editors, Computer Aided Geometric Design, pages 317–326, San Francisco, 1974. Academic Press.
Y. Cui and J. Weng. Learning-based hand sign recognition. In Proc. of the Intl. Workshop on Automatic Face-and Gesture-Recognition, Zurich, 1995.
T.J. Darrell and A.P. Pentland. Space-time gestures. Proc. Comp. Vis. and Pattern Rec., pages 335–340, 1993.
J. W. Davis and M. Shah. Gesture recognition. Proc. European Conf. Comp. Vis., pages 331–340, 1994.
R. Duda and P. Hart. Pattern classification and scene analysis. John Wiley, New York, 1973.
K. Gould and M. Shah. The trajectory primal sketch: a multi-scale scheme for representing motion characteristics. Proc. Comp. Vis. and Pattern Rec., pages 7985, 1989.
T. Hastie and W. Stuetzle. Principal curves. Journal of the American Statistical Association, 84 (406): 502–516, 1989.
G. Johansson. Visual perception of biological motion and a model for its analysis. Perception and Psychophysics, 14 (2): 201–211, 1973.
A. Kendon. How gestures can become like words. In F. Poyatos, editor, Cross-cultural perspectives in nonverbal communication, New York, 1988. C.J. Hogrefe.
J.S. Lipscomb. A trainable gesture recognizer. Pattern Recognition, 24 (9): 895–907, 1991.
K. V. Mardia, N. M. Ghali, M. Howes T. J. Hainsworth, and N. Sheehy. Techniques for online gesture recognition on workstations. Image and Vision Computing, 11 (5): 283–294, 1993.
H. Murase and S. Nayar. Learning and recognition of 3d objects from appearance. In IEEE 2nd Qualitative Vision Workshop, New York, June 1993.
H. Murase and S. Nayar. Visual learning and recognition of 3-D objects from appearance. Int. J. of Comp. Vis., 14: 5–24, 1995.
R. Polana and R. Nelson. Low level recognition of human motion. In Proc. of the Workshop on Motion of Non-Rigid and Articulated Objects, pages 77–82, Austin, Texas, Nov. 1994.
L. R. Rabiner and B. H. Juang. Fundamentals of speech recognition. Prentice Hall, Englewood Cliffs, 1993.
K. Rangarajan, W. Allen, and M. Shah. Matching motion trajectories using scale-space. Pattern Recognition, 26 (4): 595–610, 1993.
K. Rohr. Towards model-based recognition of human movements in image sequences. Comp. Vis., Graph., and Img. Proc., 59 (1): 94–115, 1994.
J. Schlenzig, E. Hunter, and R. Jain. Recursive identification of gesture inputs using hidden markov models. Proc. Second Annual Conference on Applications of Computer Vision, pages 187–194, December 1994.
J. Schlenzig, E. Hunter, and R. Jain. Vision based hand gesture interpretation using recursive estimation. In Proc. of the Twenty-Eighth Asilomar Conf. on Signals, Systems and Comp., October 1994.
G. Sperling, M. Landy, Y. Cohen, and M. Pavel. Intelligible encoding of ASL image sequences at extremely low information rates. Comp. Vis., Graph., and Img. Proc., 31: 335–391, 1985.
T. E. Starner and A. Pentland. Visual recognition of American Sign Language using hidden markov models. In Proc. of the Intl. Workshop on Automatic Face-and Gesture-Recognition, Zurich, 1995.
A.I. Tew and C.J. Gray. A real-time gesture recognizer based on dynamic programming. Journal of Biomedical Eng., 15: 181–187, May 1993.
M. Turk and A. Pentland. Eigenfaces for recognition. Journal of Cognitive Neuroscience, 3 (1): 71–86, 1991.
A. D. Wilson and A. F. Bobick. Learning visual behavior for gesture analysis. In Proc. IEEE Int’l. Symp. on Comp. Vis., Coral Gables, Florida, November 1995.
A. D. Wilson, A. F. Bobick, and J. Cassell. Recovering the temporal structure of natural gesture. In Proc. of the Intl. Workshop on Automatic Face-and Gesture-Recognition, Killington, 1996.
J. Yamato, J. Ohya, and K. Ishii. Recognizing human action in time-sequential images using hidden markov model. Proc. Comp. Vis. and Pattern Rec., pages 379–385, 1992.
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© 1997 Springer Science+Business Media Dordrecht
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Bobick, A.F., Wilson, A.D. (1997). State-Based Recognition of Gesture. In: Shah, M., Jain, R. (eds) Motion-Based Recognition. Computational Imaging and Vision, vol 9. Springer, Dordrecht. https://doi.org/10.1007/978-94-015-8935-2_9
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DOI: https://doi.org/10.1007/978-94-015-8935-2_9
Publisher Name: Springer, Dordrecht
Print ISBN: 978-90-481-4870-7
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