Title :
Object Based Key Frame Selection for Hand Gesture Recognition
Author :
Kshirsagar, Ketki P. ; Doye, Dharmpal
Author_Institution :
SGGS Inst. of Eng. & Tech. Nanded, Nanded, India
Abstract :
The sign language recognition is the most popular research area involving computer vision, pattern recognition and image processing. It enhances communication capabilities of the mute person. In this paper, we present an object based key frame selection., Hausdorff distance, Forward Algorithm and Euclidean distance are used for shape similarity for hand gesture recognition. We proposed use to the hidden markov model and nonlinear time alignment model with key frame selection facility and gesture trajectory features for hand gesture recognition. Experimental results demonstrate the effectiveness of our proposed scheme for recognizing American Sign Language.
Keywords :
computer vision; gesture recognition; hidden Markov models; object recognition; American sign language; Euclidean distance; Hausdorff distance; computer vision; forward algorithm; frame selection facility; gesture trajectory features; hand gesture recognition; hidden markov model; image processing; mute person; nonlinear time alignment model; object based key frame selection; pattern recognition; sign language recognition; Decision support systems; Dynamic time warping and Trajectory feature; Finite state machine; Hidden markov model; Sign language;
Conference_Titel :
Advances in Recent Technologies in Communication and Computing (ARTCom), 2010 International Conference on
Conference_Location :
Kottayam
Print_ISBN :
978-1-4244-8093-7
Electronic_ISBN :
978-0-7695-4201-0
DOI :
10.1109/ARTCom.2010.80
