Give Me a Sign : A Person Independent Interactive Sign Dictionary (bibtex)
by Helen Cooper, Eng-Jon Ong, Richard Bowden
Abstract:
This paper presents a method to perform person independent sign recognition. This is achieved by implementing generalising features based on sign linguistics. These are combined using two methods. The first is traditional Markov models, which are shown to lack the required generalisation. The second is a discriminative approach called Sequential Pattern Boosting, which combines feature selection with learning. The resulting system is introduced as a dictionary application, allowing signers to query by performing a sign in front of a Kinect. Two data sets are used and results shown for both, with the query-return rate reaching 99.9\% on a 20 sign multi-user dataset and 85.1\% on a more challenging and realistic subject independent, 40 sign test set.
Reference:
Helen Cooper, Eng-Jon Ong, Richard Bowden, "Give Me a Sign : A Person Independent Interactive Sign Dictionary", Technical report, FEPS, University of Surrey, no. VSSP-TR-1/2011, Guildford, UK, 2011.
Bibtex Entry:
@TECHREPORT{Cooper-VSSP-TR-1-2011,
  author = {Helen Cooper and Eng-Jon Ong and Richard Bowden},
  title = { Give Me a Sign : A Person Independent Interactive Sign Dictionary},
  institution = {FEPS, University of Surrey},
  year = {2011},
  number = {VSSP-TR-1/2011},
  address = {Guildford, UK},
  month = {October},
  abstract = {This paper presents a method to perform person independent sign recognition.
	This is achieved by implementing generalising features based on sign
	linguistics. These are combined using two methods. The first is traditional
	Markov models, which are shown to lack the required generalisation.
	The second is a discriminative approach called Sequential Pattern
	Boosting, which combines feature selection with learning. The resulting
	system is introduced as a dictionary application, allowing signers
	to query by performing a sign in front of a Kinect. Two data sets
	are used and results shown for both, with the query-return rate reaching
	99.9\% on a 20 sign multi-user dataset and 85.1\% on a more challenging
	and realistic subject independent, 40 sign test set.},
  booktitle = {VSSP-TR-1/2011},
  url = {http://personal.ee.surrey.ac.uk/Personal/H.Cooper/research/papers/VSSP-TR-1-2011.pdf}
}
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