Research and Analysis of Gesture Recognition Experimentation Based on YOLOv5

As object detection technology continues to evolve, research topics in computer vision are becoming increasingly diverse. The YOLOv5 object detection model offers robust support for research in this field. This article discusses the development and current state of gesture recognition technology applications, and employs YOLOv5 technology to train a model that can recognize simple gestures. The article identifies some issues encountered in the experiments, analyzes their causes, and offers corresponding solutions. The objective is to demonstrate the feasibility of artificial intelligence technologies, represented by object detection models, in intelligentizing sign language communication for deaf and mute individuals.