Abstract
Advancements in human-computer interaction (HCI) have paved the way for more intuitive and immersive interfaces. The first part of the paper delves into the fundamental principles of 3D gesture recognition, including sensor technologies, machine learning algorithms, and computer vision techniques. It discusses the challenges associated with accurate recognition in various environmental conditions and the ways in which these challenges are being addressed by researchers. The second part focuses on the adaptation aspect of the technology. It highlights how 3D gesture recognition can be integrated into adaptive HCI systems, enabling personalized and context-aware interactions. These adaptations can range from adjusting the interface layout to suit the user's preferences to dynamically changing the system's behavior based on the user's gestures. Additionally, the paper discusses the potential applications of 3D gesture recognition in fields such as gaming, virtual reality, healthcare, and beyond. It emphasizes the need for continued research to improve accuracy, robustness, and user-friendliness, ultimately driving the widespread adoption of 3D gesture recognition in HCI.
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