Prediction-based gesture detection in lecture videos by combining visual, speech and electronic slides

• Main Authors: WANG, Feng, NGO, Chong-wah, PONG, Ting-Chuen
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2006
• Subjects: Databases and Information Systems; Graphics and Human Computer Interfaces
• Online Access: https://ink.library.smu.edu.sg/sis_research/6627; https://ink.library.smu.edu.sg/context/sis_research/article/7630/viewcontent/icme06.pdf
• Institution: Singapore Management University

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.