Establishment and Optimization of Video Analysis System in Metaverse Environment

Abstract

The current source space communication architecture has not changed. At present, the key technology of so-called metaverse media only applies its elements to existing communication architectures, and more importantly, this type of integration involves individual examples and promotional marketing methods. How to become a new growth point for the deep collaborative development of metaverse media requires strengthened research and exploration. Although AI analysis technology is powerful, its sensitivity, accuracy and adaptability could be more satisfactory due to the complexity of real-world scenarios. Given the shortcomings of existing research, we designed a video analysis system in the metaverse environment, combining virtual reality and artificial intelligence, with video perception, network, and information technology as the medium and big data as the technical support to build a full intelligence Video analysis system. The system is based on the YOLOv3 model, combined with the actual video scene, and analyzes according to the video's human behavior and environmental changes. Experiments show that the system has obvious advantages in the accuracy and recall rate of video analysis and detection, the system detection performance is significantly improved, and the video target analysis and detection of complex scenes are realized.