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1997 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'97)
Analysis of Gesture and Action in Technical Talks for Video Indexing
Puerto Rico
June 17-June 19
ISBN: 0-8186-7822-4
Shanon X. Ju, Univ. of Toronto
Michael J. Black, Xerox Palo Alto Research Center
Scott Minneman, Xerox Palo Alto Research Center
Don Kimber, Xerox Palo Alto Research Center
In this paper, we present an automatic system for analyzing and annotating video sequences of technical talks. Our method uses a robust motion estimation technique to detect key frames and segment the video sequence into subsequences containing a single overhead slide. The subsequences are stabilized to remove motion that occurs when the speaker adjusts their slides. Any changes remaining between frames in the stabilized sequences may be due to speaker gestures such as pointing or writing and we use active contours to automatically track these potential gestures. Given the constrained domain we define a simple ``vocabulary'' of actions which can easily be recognized based on the active contour shape and motion. The recognized actions provide a rich annotation of the sequence that can be used to access a condensed version of the talk from a web page.
Index Terms:
automatic video annotation, keyframe detection, motion estimation, gesture tracking and recognition.
Citation:
Shanon X. Ju, Michael J. Black, Scott Minneman, Don Kimber, "Analysis of Gesture and Action in Technical Talks for Video Indexing," cvpr, pp.595, 1997 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'97), 1997
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