Publication Type
Conference Proceeding Article
Version
publishedVersion
Publication Date
7-2006
Abstract
This paper presents an efficient algorithm for gesture detection in lecture videos by combining visual, speech and electronic slides. Besides accuracy, response time is also considered to cope with the efficiency requirements of real-time applications. Candidate gestures are first detected by visual cue. Then we modifity HMM models for complete gestures to predict and recognize incomplete gestures before the whole gestures paths are observed. Gesture recognition is used to verify the results of gesture detection. The relations between visual, speech and slides are analyzed. The correspondence between speech and gesture is employed to improve the accuracy and the responsiveness of gesture detection.
Discipline
Databases and Information Systems | Graphics and Human Computer Interfaces
Research Areas
Intelligent Systems and Optimization
Publication
Proceedings of the 2006 IEEE International Conference on Multimedia and Expo, ICME 2006, Toronto, Canada, July 9-12
Volume
2006
First Page
653
Last Page
656
ISBN
9781424403677
Identifier
10.1109/ICME.2006.262530
Publisher
IEEE
City or Country
Toronto, Canada
Citation
WANG, Feng; NGO, Chong-wah; and PONG, Ting-Chuen.
Prediction-based gesture detection in lecture videos by combining visual, speech and electronic slides. (2006). Proceedings of the 2006 IEEE International Conference on Multimedia and Expo, ICME 2006, Toronto, Canada, July 9-12. 2006, 653-656.
Available at: https://ink.library.smu.edu.sg/sis_research/6627
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Included in
Databases and Information Systems Commons, Graphics and Human Computer Interfaces Commons