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Sign Language Recognition Using Sub-units

Cooper, Helen, Ong, Eng-Jon, Pugeault, Nicolas and Bowden, Richard (2017) Sign Language Recognition Using Sub-units In: Gesture Recognition. The Springer Series on Challenges in Machine Learning . Springer International Publishing, pp. 89-118. ISBN 978-3-319-57020-4

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This chapter discusses sign language recognition using linguistic sub-units. It presents three types of sub-units for consideration; those learnt from appearance data as well as those inferred from both 2D or 3D tracking data. These sub-units are then combined using a sign level classifier; here, two options are presented. The first uses Markov Models to encode the temporal changes between sub-units. The second makes use of Sequential Pattern Boosting to apply discriminative feature selection at the same time as encoding temporal information. This approach is more robust to noise and performs well in signer independent tests, improving results from the 54% achieved by the Markov Chains to 76%.

Item Type: Book Section
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering > Centre for Vision Speech and Signal Processing
Faculty of Engineering and Physical Sciences > Electronic Engineering
Authors :
Editors :
Escalera, Sergio
Guyon, Isabelle
Athitsos, Vassilis
Date : 2017
DOI : 10.1007/978-3-319-57021-1_3
Copyright Disclaimer : © Springer International Publishing AG 2017
Additional Information : Series ISSN: 2520-131X
Depositing User : Clive Harris
Date Deposited : 31 Aug 2017 09:03
Last Modified : 06 Jul 2019 05:24

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