Gesture and Speech for Video Content Navigation

作者: Gary Bradski , Boon-Lock Yeo , Minerva M. Yeung

DOI:

关键词: GestureNatural user interfaceVideo trackingInteraction techniqueGesture recognitionVideo browsingInterface (computing)Computer scienceUsabilityMultimedia

摘要: This article describes ongoing research in the use computer vision gesture and speech recognition techniques as a natural interface for video content navigation, design of navigation browsing system that caters to these means computer-human interaction. For consumer applications, presents two challenges: (1) how parse summarize multiple streams an intuitive efficient manner, (2) what type will enhance ease living room setting or interactive environment. In this paper, we address issues propose combine with recognition, seamlessly intuitively, integrated system. We present new browser navigating content, well browser.

参考文章(8)
Mark Lucente, Gert-Jan Zwart, Andrew D. George, Visualization Space: A Testbed for Deviceless Multimodal User Interface ,(1998)
R. Cutler, M. Turk, View-based interpretation of real-time optical flow for gesture recognition ieee international conference on automatic face and gesture recognition. pp. 416- 421 ,(1998) , 10.1109/AFGR.1998.670984
Minerva M. Yeung, Boon-Lock Yeo, Wayne H. Wolf, Bede Liu, Video browsing using clustering and scene transitions on compressed sequences conference on multimedia computing and networking. ,vol. 2417, pp. 399- 413 ,(1995) , 10.1117/12.206067
Boon-Lock Yeo, Minerva M. Yeung, Retrieving and visualizing video Communications of The ACM. ,vol. 40, pp. 43- 52 ,(1997) , 10.1145/265563.265571
Boon-Lock Yeo, Bede Liu, Rapid scene analysis on compressed video IEEE Transactions on Circuits and Systems for Video Technology. ,vol. 5, pp. 533- 544 ,(1995) , 10.1109/76.475896
J.W. Davis, A.F. Bobick, The representation and recognition of human movement using temporal templates computer vision and pattern recognition. pp. 928- 934 ,(1997) , 10.1109/CVPR.1997.609439
M.M. Yeung, Boon-Lock Yeo, Time-constrained clustering for segmentation of video into story units international conference on pattern recognition. ,vol. 3, pp. 375- 380 ,(1996) , 10.1109/ICPR.1996.546973