Application of VR recognition based on image object detection algorithm in urban street landscape art design

Abstract

Abstract Image target detection plays an important role in the field of VR recognition and art design. It is applied in many fields such as urban planning and weather monitoring in China. In recent years, depth neural network has become an important part of target detection algorithm. Target detection has shown excellent functions in segmentation, tracking and recognition. With the rapid development of image detection technology, targeted image detection has improved the quantity and quality of data. In the application of VR technology to the artistic design of urban street landscape, it not only helps designers better observe the world characteristics, but also constantly stimulates designers' thinking inspiration in the interactive environment, thus generating new ideas, new creativity, new means and rich creative content. Therefore, design can play a role from the conceptual stage to the final effect display stage. At this stage, VR recognition technology is not mature enough in the design of urban street landscape, which is still in the exploration stage. Select a suitable VR system, and further explore and study the functions of the selected engine system on this basis. Explore the virtual work route suitable for building street landscape, and select the virtual environment of street landscape to lay a solid foundation for VR identification technology. Based on the main technical content of VR identification, the actual change and interaction of operating materials can be reflected, and the results of urban street landscape design can be presented in the most intuitive way.