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There are many applications where hand gesture can be used for interaction with systems like videogames, controlling UAV’s, medical equipment’s, etc. These hand gestures can also be used by handicapped people to interact with the systems. The main focus of this work is to create a vision based system to identify sign language gestures from real-time image capturing. The reason for choosing a system based on vision relates to the fact that it provides a simpler and more intuitive way of communication between a human and a computer. Our project has developed 3 modules that involve 49 different gestures overall, which can be predicted.

Python 100.00%
machine-learning cnn-keras contours research-paper deep-learning deaf-communications asl-recognizer american-sign-language

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