Hand Gesture Recognition to Facilitate Tasks for the Disabled
Swati Nitnaware, Ashutosh Bagde
Abstract
Deaf and dumb people communicate with gestures. Number of applications have been developed using gesture recognition computer vision, machine learning etc. A simple technique to recognize gestures is presented in this paper. Here Python libraries such as Opencv, Numpy are used. The technique involves capture of live gestures and recognition of the same using Opencv functions. Parameters such as the area ratio and convexity defects are considered to differentiate between different gestures. The system will also display text message and an audio file will be used for vocalizing the different gestures. A functionality where gestures are recognized for entertainment purpose is presented. This can be of use to blind people for the purpose of entertainment such as playing music, radio or listening to news. Here Multiprocessing library is used. The tasks are assigned to specific gestures.