Interactive Hand Gesture Recognition With Audio Response
P. Jeyanthi, Abdul Ajees I., Abel Priya Kumar, Vikash Ajin P., S. Revathy, Mary Gladence L. · Advances in computational intelligence and robotics book series · 2024
This research introduces a comprehensive sign language recognition system designed to address challenges faced by individuals seeking to learn sign language, particularly those with limited access to interactive and varied learning resources. Leveraging machine learning and computer vision technologies, the system integrates advanced hand landmark detection, dataset creation, model training using a random forest classifier and real-time inference. The core technology, powered by Media Pipe Hands, enables real-time capture and processing of hand landmarks for accurate sign language interpretation. This concept differs from classical network technology based on photon or electron transmission. Underlying principles of quantum theory and several aspects of quantum behavior make quantum networking possible. Here are some important quantum principles are incorporated in this project. The project underscores the potential to positively impact the lives of individuals with hearing impairments and contributes to the broader field of accessible communication systems.