A Comparison of Hardware Based Approaches for Sign Language Gesture Recognition Systems

Sign language is a gesture-based language used worldwide by the deaf people to communicate with one another. This language comprises of different hand movements and facial expressions. Over the years, different tools and applications have been built and developed by the researchers to facilitate the deaf community in their communication with normal people. One branch of research deals with the recognition of gestures by machines, i.e. the machine is able to understand the gesture performed by a person. Many different approaches involving a variety of hardware including gloves, Microsoft Kinect, and sensors have been used for this purpose. The literature survey reveals that the most significant and advanced work in this regard has been accomplished in American Sign Language (ASL). Whereas, recently noticeable research is being conducted for the development of different Asian sign languages as well. This work presents a study of hardware-based approaches for gesture recognition in ASL and Asian sign languages.