Sign Language Recognition (bibtex)
by Helen Cooper, Brian Holt, Richard Bowden
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.
Reference:
Helen Cooper, Brian Holt, Richard Bowden, "Sign Language Recognition", Chapter in Visual Analysis of Humans: Looking at People, Springer, pp. 539 - 562, 2011. (pre-print)
Bibtex Entry:
@INCOLLECTION{Cooper_Visual_2011,
  author = {Helen Cooper and Brian Holt and Richard Bowden},
  title = {Sign Language Recognition},
  booktitle = {Visual Analysis of Humans: Looking at People},
  publisher = {Springer},
  year = {2011},
  editor = {Thomas B. Moeslund and Adrian Hilton and Volker Kr\"{u}ger and Leonid
	Sigal},
  chapter = {27},
  pages = {539 -- 562},
  month = oct,
  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.},
  comment = {<a target="_blank" href="http://personal.ee.surrey.ac.uk/Personal/H.Cooper/research/papers/SLR-LAP.pdf">pre-print</a>},
  doi = {10.1007/978-0-85729-997-0_27},
  url = {http://www.springer.com/computer/image+processing/book/978-0-85729-996-3}
}
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