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Sign Language Recognition using Sequential Pattern Trees

Ong, E, Bowden, R, Cooper, H and Pugeault, N (2012) Sign Language Recognition using Sequential Pattern Trees In: IEEE Conference on Computer Vision and Pattern Recognition, 2012-06-16 - 2012-06-21.

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Abstract

This paper presents a novel, discriminative, multi-class classifier based on Sequential Pattern Trees. It is efficient to learn, compared to other Sequential Pattern methods, and scalable for use with large classifier banks. For these reasons it is well suited to Sign Language Recognition. Using deterministic robust features based on hand trajectories, sign level classifiers are built from sub-units. Results are presented both on a large lexicon single signer data set and a multi-signer Kinect™ data set. In both cases it is shown to out perform the non-discriminative Markov model approach and be equivalent to previous, more costly, Sequential Pattern (SP) techniques.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Authors :
NameEmailORCID
Ong, Ee.ong@surrey.ac.ukUNSPECIFIED
Bowden, Rr.bowden@surrey.ac.ukUNSPECIFIED
Cooper, Hhelen.cooper@surrey.ac.ukUNSPECIFIED
Pugeault, Nn.pugeault@surrey.ac.ukUNSPECIFIED
Date : 26 July 2012
Identification Number : https://doi.org/10.1109/CVPR.2012.6247928
Depositing User : Symplectic Elements
Date Deposited : 17 May 2017 12:34
Last Modified : 17 May 2017 15:04
URI: http://epubs.surrey.ac.uk/id/eprint/835892

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