Abstract
A method for the temporal classification of natural gesture from video imagery is presented. The work is motivated by recent developments in the theory of natural gesture which have identified several key temporal aspects of gesture important to communication. In particular, gesticulation during conversation can be coarsely characterized as periods of bi-phasic or tri-phasic gesture separated by a rest state. We first present an automatic procedure for hypothesizing plausible rest state configurations of a speaker. Second, we develop a state-based parsing algorithm used to both select among candidate rest states and to parse an incoming video stream into bi-phasic and tri-phasic gestures. Finally, we demonstrate the use of the bi-phasic/tri-phasic labeling to select semantically significant static images for low bandwidth coding of video of story-telling speakers.
| Original language | English |
|---|---|
| Pages (from-to) | 948-954 |
| Number of pages | 7 |
| Journal | Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition |
| State | Published - 1997 |
| Event | Proceedings of the 1997 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - San Juan, PR, USA Duration: Jun 17 1997 → Jun 19 1997 |