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.

Innovation and Research of Digital Artwork Design Based on Big Data and Integrated Media

“…Linear models use a large number of sparse one-hot codes for computation, which are simple and effective but have poor performance and cannot design complex relationships between features. The nonlinear model is an algorithmic model that maps binarized features to a low-dimensional space on the basis of the linear model and designs the relationship between features by inner product, which eventually leads to improved performance [21]. The gradient boosting tree algorithm is its representative, by constructing a tree and thus achieving automatic learning.…”

Systematic Literature Review of Machine Learning in Virtual Reality and Augmented Reality

“…In addition, Huy Le's research approach can be helpful in education, where the content of textbook images must remain unchanged, and high detection accuracy is required [21]. Research by Xu et al, analyzed and processed visual interaction screen data based on calculations for predicting image differences built with deep learning and establishing an image prediction model [29].…”