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2005
Springer

Gesture Recognition Using Image Comparison Methods

10 years 7 months ago
Gesture Recognition Using Image Comparison Methods
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.
Philippe Dreuw, Daniel Keysers, Thomas Deselaers,
Added 27 Jun 2010
Updated 27 Jun 2010
Type Conference
Year 2005
Where GW
Authors Philippe Dreuw, Daniel Keysers, Thomas Deselaers, Hermann Ney
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