Conference PaperPDF Available

Exploring the techniques applies to Sign Language Recognition

February 2011

Conference: National conference on Innovations and Trends in Computer & Communication Engineering ITCCE-2010
At: MET, Nashik, Maharashtra, India

Authors:

Pimpri Chinchwad College Of Engineering

Rajiv Vasantrao Dharaskar

Director, IIIT Kottayam, Kerala, India Institute of National Importance

Sign language is the primary modality of communication among deaf and mute society all over the world. Gesture use is an important part of human communication to exchange ideas, thought. The automatic recognition of gestures enriches human-computer interaction by offering a natural and intuitive method of data input. In Sign language, hand gesture is one of the typical methods of non-verbal communication for human beings and we naturally use various gestures to express our own intentions in everyday life. Till date, there have been studies on Sign language recognition based visual approach. However, the emphasis on these works is limited to a small lexicon of sign language. This paper has summarized the researchers work in the Sign language domain and highlights the different techniques & outcomes when applied to Vision based approach used in Sign language Recognition Systems (SLRS).

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Chapter

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Body gesture is the most important way of non-verbal communication for deaf and dumb people. Thus, a novel sign language recognition procedure is presented here where the movements of hands play a pivotal role for such kind of communications. Microsoft’s Kinect sensor is used to act as a medium to interpret such communication by tracking the movement of human body using 20 joints. A procedural ... [Show full abstract] approach has been developed to deal with unknown gesture recognition by generating in-order expression for AVL tree as a feature. Here, 12 gestures are taken into consideration, and for the classification purpose, kernel function-based support vector machine is employed with results to gesture recognition into an accuracy of 88.3%. The foremost goal is to develop an algorithm that act as a medium to human–computer interaction for deaf and dumb people. Here, the novelty lies in the fact that for gesture recognition in sign language interpretation, the whole body of the subject is represented using a hierarchical balanced tree (here AVL).

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