Human Action Recognition Using Machine Learning

Abstract

People with speech disabilities communicate in sign language and therefore 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 sign language. A functional unobtrusive Indian sign language recognition system was implemented and tested on real world data. A vocabulary of 26 symbols was collected. The vocabulary consisted mostly of two-handed signs which were drawn from a wide repertoire of words of technical and daily-use origins. Our project aims to create a computer application and train a model which when shown a real time video of hand gestures of Indian Sign Language shows the output for that particular sign in text format on the screen.