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Proceedings of 1994 28th Asilomar Conference on Signals, Systems and Computers (1994)
Pacific Grove, CA, USA
Oct. 31, 1994 to Nov. 2, 1994
ISSN: 1058-6393
ISBN: 0-8186-6405-3
pp: 1267-1271
J. Schlenzig , Visual Comput. Lab., California Univ., San Diego, La Jolla, CA, USA
E. Hunter , Visual Comput. Lab., California Univ., San Diego, La Jolla, CA, USA
R. Jain , Visual Comput. Lab., California Univ., San Diego, La Jolla, CA, USA
ABSTRACT
Gesture recognition requires spatio-temporal image sequence analysis. The actual length of the sequence varies with each instantiation of the gesture, and can be quite long in the case of a multiple gesture sequence. To achieve adequate system response we introduce the concept of recursive estimation of the gesture state. This consists of modeling the gestures as a sequence of static hand poses. Using a hidden Markov model where the unobservable state is the spatio-temporal gesture and the hand poses are the observations allows us to determine the current probabilities of each gesture with a finite state estimator. This decomposes the gesture recognition process into two stages: identification of the hand pose within the current image frame and incorporation of the new information into the probability estimates. We illustrate the performance of the estimator by describing the implementation of a telerobotic application.<>
INDEX TERMS
robot vision, image sequences, image recognition, recursive estimation, hidden Markov models, probability, user interfaces, telerobotics
CITATION

J. Schlenzig, E. Hunter and R. Jain, "Vision based hand gesture interpretation using recursive estimation," Proceedings of 1994 28th Asilomar Conference on Signals, Systems and Computers(ACSSC), Pacific Grove, CA, USA, 1995, pp. 1267-1271.
doi:10.1109/ACSSC.1994.471662
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