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Title: Gesture Recognition for Indian Sign Language
Researcher : Ansari, Zafar Ahmed
Supervisor: Harit, Gaurav
Adhikari, Bibhas
Department: Center for Information Communication and Technology
Issue Date: May-2013
Citation: Ansari, Zafar Ahmed. (2013). Gesture Recognition for Indian Sign Language (Master's thesis). Indian Institute of Technology Jodhpur, Jodhpur.
Abstract: Sign Language recognition is an important research area. People with speech disabilities have trouble in mingling with the able-bodied. There is a need for an interpretation system which could act as a bridge between them and those who do not know their language. A functional unobtrusive Indian sign language recognition system was implemented and tested on real world data. A vocabulary of 140 symbols was collected using 18 subjects, totalling 5041 images. The vocabulary consisted mostly of two handed signs which were drawn from a wide repertoire of words of technical and daily-use origins. The system was implemented using Microsoft Kinect which enables variations in surrounding light conditions and object colour to have negligible effect on the efficiency of the system. The system proposes the method for a novel low-cost and easy-to-use application for the Microsoft Kinect camera, ie Indian Sign Language recognition. A variety of features and their recognition heuristics were experimented on the dataset and their results compared. The software stack and the corresponding dataset would be released for public research use.
Pagination: xiv, 75p.
Accession No.: TM00039
Appears in Collections:M. Tech. Theses

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