Published Paper Details:

Everyone can communicate effectively with hand gestures. Hand gesture recognition, as opposed to the traditional text-based or GUI-based method, can be viewed as a means for computers to better comprehend human body language, resulting in a fuller interaction between humans and computers. Hand gestures can simplify work by sending orders to the computer using simple hand movements. The camera captures the movements, the computer interprets them, and suitable action is conducted in response to the gesture. This project is built on sign language translation, which captures hand movements and converts them into commands that the computer can comprehend and give the output as audio and text format and do relevant tasks. In this project, we first use a camera to capture the gesture. The collected picture is then pre-processed for feature extraction, and a convolutional neural network is implemented to successfully detect motions and train the machine.