PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Sign Language Recognition
Hellen Cooper, Brian Holt and Richard Bowden
In: Visual Analysis of Humans: Looking at People (2011) Springer Verlag , pp. 539-562. ISBN 978-0-85729-996-3

Abstract

This chapter covers the key aspects of Sign Language Recognition (SLR), starting with a brief introduction to the motivations and requirements, followed by a precis of sign linguistics and their impact on the field. The types of data available and the relative merits are explored allowing examination of the features which can be extracted. Classifying the manual aspects of sign (similar to gestures) is then discussed from a tracking and non-tracking viewpoint before summarising some of the approaches to the non-manual aspects of sign languages. Methods for combining the sign classification results into full SLR are given showing the progression towards speech recognition techniques and the further adaptations required for the sign specific case. Finally the current frontiers are discussed and the recent research presented. This covers the task of continuous sign recognition, the work towards true signer independence, how to effectively combine the different modalities of sign, making use of the current linguistic research and adapting to larger more noisy data sets.

EPrint Type:Book Section
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Machine Vision
ID Code:8944
Deposited By:Helen Cooper
Deposited On:21 February 2012