Research on Human-Computer Interaction Technology with Artificial Intelligence-based Gesture Recognition

Gesture is an important way for people to communicate information. It has been explored as a communication channel both in human-computer interaction and human-robot interaction. It unlocks a new communication channel that people can express rich semantic information through hand movements. The common gesture interaction systems can be roughly divided into: gesture interaction system based on sensing, signal and visual gesture interaction system. With the progression of scientific and technological advancements, gesture recognition technology has undergone significant evolution and innovation. The integration of artificial intelligence (AI) in gesture recognition has expanded its application across numerous domains. Human-computer interaction technology based on visual gesture recognition involves computer pattern recognition technology, involving mathematics, computer graphics, physiology, pattern recognition, medicine and other disciplines, is an interdisciplinary research topic. This manuscript presents a deep learning-based gesture recognition system for human-computer interaction. The paper delves into the basic issues of gesture recognition: components of the hardware system, the principles of gesture recognition, the algorithms employed, and the key stages of human-computer interaction. The main steps of gesture recognition process are studied and analyzed, and the relevant experimental test applications are carried out. Experimental evaluations demonstrate that this methodology achieves a high recognition accuracy of 90% for diverse gestures, thereby satisfying the interaction requirements of typical human-computer interaction systems.