Gesture Recognition using CNN and RNN

Abstract

Gesture Recognition is a major area in Human-Computer Interaction (HCI). HCI allows computers to capture and interpret human gestures as commands. A real-time Hand Gesture Recognition System is implemented and is used for operating electronic appliances. This system is implemented using the deep learning models such as the Convolution Neural Network (CNN) and the Recurrent Neural Network (RNN). The combined model will effectively recognize both static and dynamic hand gestures. Also the model accuracy while using VGG16 pre-trained CNN model is investigated.