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Gesture Recognition using Indian Sign Language: A Survey

Author(s):

Tanvi B. Patel , Shri S'ad Vidya Mandal Institute of Technology; Jalpa T. Patel, Shri S'ad Vidya Mandal Institute of Technology

Keywords:

Hidden Markov Model (HMM), artificial neural network (ANN), K-Nearest Neighbor classifier, Scale Invariant Feature Transform (SIFT)

Abstract

Gestures are expressive, meaningful body motions, i.e., physical movements of the fingers, hands, arms, head, face or body with the intent to convey information or interact with the environment. Gesture recognition is helpful for establishing interaction between human and computer. Sign language is a system of communication using visual gestures and signs, as used by deaf and dumb people. Sign Language is visual gesture language. Sign language helps the deaf and dumb people to communicate with each other. People usually used their hands and arms to convey their messages to others. However, various methods for gesture recognition such as HMM (Hidden Markov Model), ANN (Artificial neural network), classification, pattern matching and recognition, HOG (Histogram of Oriented Gradients), SIFT (Scale Invariant Feature Transform) etc are used. Applications of gesture recognition are human computer interaction, robotics, sign language recognition, etc. In this paper, study of various methods, its applications, advantages and disadvantages of the gesture recognition is analyzed.

Other Details

Paper ID: IJSRDV4I70439
Published in: Volume : 4, Issue : 7
Publication Date: 01/10/2016
Page(s): 878-881

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