Vision based hand gesture interpretation using recursive estimation

• Published in: Proceedings of 1994 28th Asilomar Conference on Signals, Systems and Computers Vol. 2; pp. 1267 - 1271 vol.2
• Main Authors: Schlenzig, J., Hunter, E., Jain, R.
• Format: Conference Proceeding
• Language: English
• Published: IEEE Comput. Soc. Press 1994
• Subjects: Application software; Hidden Markov models; Human robot interaction; Image recognition; Image sequence analysis; Laboratories; Man machine systems; Recursive estimation; Speech recognition; State estimation
• ISBN: 0818664053; 9780818664052
• ISSN: 1058-6393
• DOI: 10.1109/ACSSC.1994.471662

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.< >