Combination of tangent distance and an image distortion model for appearance-based sign language recognition

Authors:
Morteza Zahedi;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:
PR'05 Proceedings of the 27th DAGM conference on Pattern Recognition
Year:
2005

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Abstract

In this paper, we employ a zero-order local deformation model to model the visual variability of video streams of American sign language (ASL) words. We discuss two possible ways of combining the model with the tangent distance used to compensate for affine global transformations. The integration of the deformation model into our recognition system improves the error rate on a database of ASL words from 22.2% to 17.2%.