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2007

Sign Language Recognition Using Boosted Volumetric Features

10 years 18 hour ago
Sign Language Recognition Using Boosted Volumetric Features
This paper proposes a method for sign language recognition that bypasses the need for tracking by classifying the motion directly. The method uses the natural extension of haar like features into the temporal domain, computed efficiently using an integral volume. These volumetric features are assembled into spatio-temporal classifiers using boosting. Results are presented for a fast feature extraction method and 2 different types of boosting. These configurations have been tested on a data set consisting of both seen and unseen signers performing 5 signs producing competitive results.
Helen Cooper, Richard Bowden
Added 30 Oct 2010
Updated 30 Oct 2010
Type Conference
Year 2007
Where MVA
Authors Helen Cooper, Richard Bowden
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