Immersive Display Design Based on Deep Learning Intelligent VR Technology

Abstract

Introducing deep learning into smart VR devices can make them iteratively upgraded and allow users to have a better immersive design experience. This study analyzes and processes the data of visual interaction screens based on image difference prediction computation established by deep learning to build an image prediction model. After the definition of VR technology is clarified, the first VR devices and the mainstream devices today are introduced. After adding the extensions to image difference and difference prediction, the final image prediction computation model for the immersive display design screen is established. This experiment uses the image difference prediction model to perform the removal of redundant pixels from multiple screenshots of the display device, and multiple determinations of the color display, and based on the data of the acquisition points on the initial color, which eventually leads to a quality level improvement of the display screen effect. More polygonal modeling was added to make the display of clothes and props more realistic. The specular reflections are also no longer mirror mapped but are the result of real-time algorithm production images. The final results of the questionnaire distributed showed that 83% of the users were very satisfied with the immersive display screen effect.