A Survey Paper on Real-Time Sign Language Gesture Recognition
Sign Language Recognition has been used for serving deaf and dumb humans and is being researched for last previous years. It helps make communication between humans and computers. Recognizing sign gestures through continuous gestures was a very challenging research topic. There are many methods for recognizing these gestures like Data Acquisition Method, Hidden Markov Model (HMM), Recurrent Neural Network (RNN), gradient-based keyframe method. This paper aims to convert single-handed gestures into text in real-time. It will be a revolutionary development in establishing a communication path between the dumb and deaf people and the real world.