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Developing context sensitive HMM gesture recognition

chapter
posted on 2023-06-07, 14:02 authored by Kingsley Sage, A.J. Howell, Hilary Buxton
We are interested in methods for building cognitive vision systems to understand activities of expert operators for our ActIPret System. Our approach to the gesture recognition required here is to learn the generic models and develop methods for contextual bias of the visual interpretation in the online system. The paper first introduces issues in the development of such flexible and robust gesture learning and recognition, with a brief discussion of related research. Second, the computational model for the Hidden Markov Model (HMM) is described and results with varying amounts of noise in the training and testing phases are given. Third, extensions of this work to allow both top-down bias in the contextual processing and bottom-up augmentation by moment to moment observation of the hand trajectory are described.

History

Publication status

  • Published

Journal

Gesture Workshop

Publisher

Springer Link

Volume

2915

Page range

277-287

Pages

558.0

Book title

Gesture-Based Communication in Human-Computer Interaction

Place of publication

New York, USA

ISBN

9783540210726

Series

Lecture Notes in Computer Science

Department affiliated with

  • Informatics Publications

Full text available

  • No

Peer reviewed?

  • Yes

Editors

Gualtiero Volpe, Antonio Camurri

Legacy Posted Date

2008-02-12

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