Hand Gesture Recognition: A Survey

Abstract

Hand gesture recognition (HGR) is an emerging technology that allows the intuitive human-computer interaction by explaining the input of the movements of the human hand. The main objective of this research is to explore the novel's approach, classification, and explanation of hand gestures for various applications, ranging from the translation of the symbolic language to virtual reality, gaming and robotics. We review the sophisticated techniques in computer vision and intensive education, emphasizing methods such as Convolutional neural networks (CNN), room sensing and complex gestures in real-time. Analysing performance in terms of accuracy, reinforcement and computer efficiency, presents a wide evaluation paper of various datasets, algorithms and system architecture. Our conclusions indicate that while significant progress is being made, challenges in obtaining real-time recognition with high accuracy in different environmental conditions. Future work will focus on improving gesture identification models, increasing cross- dominated adaptability, and reducing hardware dependence on the integration of practical applications.