Hand Gesture Recognition

Abstract

Hand gestures constitute a kind of nonverbal communication applicable in several domains, including interactions among deaf-mute individuals, robotic manipulation, human-computer interface (HCI), home automation, and medical applications. Research publications concerning hand gestures have used many methodologies, including those using instrumented sensor technologies and computer vision. The hand sign may be categorized under many classifications, including posture and gesture, as well as dynamic and static, or a combination of both. This study reviews the research on hand gesture strategies, highlighting their advantages and disadvantages in various contexts. Furthermore, it enumerates the efficacy of these methodologies, emphasizing computer vision techniques that address points of similarity and divergence, hand segmentation methods employed, classification algorithms and their limitations, the quantity and categories of gestures, the dataset utilized, detection range (distance), and the type of camera implemented. This article provides a comprehensive introduction of hand gesture techniques, along by a concise assessment of potential applications.