Tracking, Analysis, and Recognition of Human Gestures in Video

Authors:
Stan Sclaroff;Margrit Betke;George Kollios;Jonathan Alon;Vassilis Athitsos;Rui Li;John Magee;Tai-peng Tian
Affiliations:
Boston University, Boston, MA;Boston University, Boston, MA;Boston University, Boston, MA;Boston University, Boston, MA;Boston University, Boston, MA;Boston University, Boston, MA;Boston University, Boston, MA;Boston University, Boston, MA
Venue:
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Year:
2005

Citing 3
Cited 0

Simultaneous Localization and Recognition of Dynamic Hand Gestures

WACV-MOTION '05 Proceedings of the IEEE Workshop on Motion and Video Computing (WACV/MOTION'05) - Volume 2 - Volume 02
Articulated Pose Estimation in a Learned Smooth Space of Feasible Solutions

CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops - Volume 03
BoostMap: a method for efficient approximate similarity rankings

CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition

Quantified Score

Hi-index	0.00

Visualization

Abstract

An overview of research in automated gesture spotting, tracking and recognition by the Image and Video Computing Group at Boston University is given. Approaches for localization and tracking human hands in video, estimation of hand shape and upper body pose, tracking head and facial motion, as well as efficient spotting and recognition of specific gestures in video streams are summarized. Methods for efficient dimensionality reduction of gesture time series, boosting of classifiers for nearest neighbor search in pose space, and model-based pruning of gesture alignment hypotheses are described. Algorithms are demonstrated in three domains: American Sign Language, hand signals like those employed by flight-directors on airport runways, and gesture-based interfaces for severely disabled users. The methods described are general and can be applied in other domains that require efficient detection and analysis of patterns in time-series, images or video.