A Literature Survey on Hand Gesture Recognition

Thermal imaging presents a promising approach for hand gesture recognition, offering enhanced robustness compared to traditional RGB camera-based systems in challenging environments. Unlike RGB camera-based solutions, thermal imaging offers robustness in diverse environments, particularly under varying lighting conditions. The study reviews advanced tools and techniques, including CNN-based feature extraction, real-time gesture mapping, and efficient model training methodologies. Key findings highlight the potential of thermal imaging in achieving precise and intuitive control of media functionalities like play, pause, and volume adjustments. The research emphasizes resource efficient designs for seamless operation on devices with constrained computational resources. This work provides a foundation for developing adaptive, reliable, and user-friendly gesture-controlled systems. Key Words: Thermal Imaging, Gesture Recognition, Media Control, Deep Learning, Real-Time Systems, Human-Computer Interaction