Visual Communication-Based Virtual Reality Design of Imaging Information Collection and Display System. (25th September 2022)

• Record Type: Journal Article
• Authors: Qi, Yichen; Sun, Tong; Li, Yan
• Other Names: Ye Jun Academic Editor.
• Is Part Of: Wireless communications and mobile computing. Volume 2022(2022)
• Publication Date: 2022-09-25
• Subjects: Wireless communication systems -- Periodicals; Mobile communication systems -- Periodicals; 621.38205
• DOI: 10.1155/2022/1929596
• Languages: English
• ISSNs: 1530-8669

Abstract

Abstract : Imaging image acquisition and display has always been an important application field of visual communication art. A good imaging acquisition and display system can give the audience an excellent visual experience. However, conventional imaging image acquisition equipment is too bulky and expensive. At the same time, the existing imaging acquisition technology is generally only suitable for two-dimensional plane design. It is difficult to construct the three-dimensional and realistic sense of actual objects, which makes the development of the entire imaging system slow. Existing imaging acquisition technologies have difficulty keeping pace with the technological age. In this paper, according to the actual needs, a three-dimensional imaging technology was proposed to improve the efficiency of imaging image acquisition. And the principle of imaging information display was used to enhance the visual communication effect. Then, at the algorithm level, virtual reality technology was combined with convolutional neural network-related algorithms to improve the overall accuracy of the algorithm and control the error well. The experimental results showed that the optimized VR technology leads the whole stage in terms of mean square error. Among them, after testing 400 samples in the two experiments, the error performance is controlled below 0.32, and the best error control performance is 0.07; the unoptimized virtual reality technology error control is not ideal. The minimum error failed to break below 0.2, and the optimized algorithm had a high accuracy of 99.3%, which greatly improved the feasibility of the imaging information acquisition and display system.