DocumentCode :
3233369
Title :
Delayed absolute difference (DAD) signatures of dynamic features for sign language segmentation
Author :
Khan, Shujjat ; Bailey, Donald ; Gupta, Gourab Sen
Author_Institution :
Sch. of Eng. & Adv. Technol., Massey Univ., Palmerston North, New Zealand
fYear :
2011
fDate :
6-8 Dec. 2011
Firstpage :
109
Lastpage :
114
Abstract :
In sign language segmentation, individual gestures are extracted out of a continuous stream and then matched with models for recognition. We have hypothesized an improvement in word segmentation without affecting the language naturalness by incorporating a novel set of segmentation features (pause, repetition and directional variations). To analyze these segmentation features, a unified tool (DAD signature) is presented that encodes the segmentation features in form of distinct patterns. It is shown that the DAD signature can easily detect the pauses, repetitions and reversal of direction.
Keywords :
feature extraction; gesture recognition; handicapped aids; image coding; image matching; image segmentation; DAD signature; deaf-mute community; delayed absolute difference signatures; directional variation segmentation feature; dynamic features; gesture extraction; gesture matching; pause segmentation feature; repetition segmentation feature; sign language segmentation; word segmentation; Accuracy; Communities; Delay; Feature extraction; Handicapped aids; Hidden Markov models; Robots; Gesture segmentation; delayed absolute difference signatures; directional variations; repetition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Automation, Robotics and Applications (ICARA), 2011 5th International Conference on
Conference_Location :
Wellington
Print_ISBN :
978-1-4577-0329-4
Type :
conf
DOI :
10.1109/ICARA.2011.6144866
Filename :
6144866
Link To Document :
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