Sign Language Recognition Using Boosted Volumetric Features (bibtex)
by Helen Cooper, Richard Bowden
Abstract:
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.
Reference:
Helen Cooper, Richard Bowden, "Sign Language Recognition Using Boosted Volumetric Features", In Proceedings of the IAPR Conference on Machine Vision Applications, Tokyo, Japan, pp. 359 - 362, 2007.
Bibtex Entry:
@INPROCEEDINGS{Cooper_Sign_2007,
  author = {Helen Cooper and Richard Bowden},
  title = {Sign Language Recognition Using Boosted Volumetric Features},
  booktitle = {Proceedings of the IAPR Conference on Machine Vision Applications},
  year = {2007},
  pages = {359 -- 362},
  address = {Tokyo, Japan},
  month = may # { 16 -- 18},
  abstract = {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.},
  url = {http://personal.ee.surrey.ac.uk/Personal/H.Cooper/research/papers/cooper-mva-2007.pdf}
}
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