Gesture recognition using image comparison methods

Authors:
Philippe Dreuw;Daniel Keysers;Thomas Deselaers;Hermann Ney
Affiliations:
Lehrstuhl für Informatik VI, Computer Science Department, RWTH Aachen University, Aachen, Germany;Lehrstuhl für Informatik VI, Computer Science Department, RWTH Aachen University, Aachen, Germany;Lehrstuhl für Informatik VI, Computer Science Department, RWTH Aachen University, Aachen, Germany;Lehrstuhl für Informatik VI, Computer Science Department, RWTH Aachen University, Aachen, Germany
Venue:
GW'05 Proceedings of the 6th international conference on Gesture in Human-Computer Interaction and Simulation
Year:
2005

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Abstract

We introduce the use of appearance-based features, and tangent distance or the image distortion model to account for image variability within the hidden Markov model emission probabilities to recognize gestures. No tracking, segmentation of the hand or shape models have to be defined. The distance measures also perform well for template matching classifiers. We obtain promising first results on a new database with the German finger-spelling alphabet. This newly recorded database is freely available for further research.