Study of Enhanced Communication of Human-Computer Using Gesture Recognition Technique

Hand gestures serve as a fundamental mode of non- verbal communication, intricately conveying messages through the positioning of palms, arrangement of fingers, and the form of the hand itself. Their significance lies in their ability to facilitate intuitive communication and provide a natural avenue for interaction. Gesture recognition, categorized into sensor-based and vision-based approaches, forms the backbone of systems enabling seamless human-machine communication. Sensor-based systems employ wearable devices such as data gloves and wrist bands, while vision-based systems utilize cameras or depth sensors like Leap Motion Controller (LMC) and Microsoft Kinect. This paper delves into the realm of depth- sensing techniques within gesture recognition, aiming to present a comprehensive analysis and comparison. By exploring existing methodologies, this study seeks to shed light on the advancements, challenges, and future prospects in the dynamic field of hand gesture recognition.