Peer-Reviewed Journal Details
Mandatory Fields
Kelly, D;Mc Donald, J;Markham, C
2011
April
Ieee Transactions On Systems Man And Cybernetics Part B-Cybernetics
Weakly Supervised Training of a Sign Language Recognition System Using Multiple Instance Learning Density Matrices
Published
24 ()
Optional Fields
HAND POSTURES CLASSIFICATION FRAMEWORK
41
526
541
A system for automatically training and spotting signs from continuous sign language sentences is presented. We propose a novel multiple instance learning density matrix algorithm which automatically extracts isolated signs from full sentences using the weak and noisy supervision of text translations. The automatically extracted isolated samples are then utilized to train our spatiotemporal gesture and hand posture classifiers. The experiments were carried out to evaluate the performance of the automatic sign extraction, hand posture classification, and spatiotemporal gesture spotting systems. We then carry out a full evaluation of our overall sign spotting system which was automatically trained on 30 different signs.
PISCATAWAY
1083-4419
10.1109/TSMCB.2010.2065802
Grant Details