Research on the Application of Visual Sensing Technology in Art Education

Abstract

It is essential to have a new understanding of the development of visual sensing technology in digital image art at this stage, in order to make traditional art education have new professional ability teaching. Based on the current research results in related fields, a three-dimensional (3D) image visual communication system based on digital image automatic reconstruction is proposed with two schemes as the premise. In scheme 1, the hardware part is divided into two modules. The hardware used by the analysis of the 3D image layer module is the HUJ-23 3D image processor. The acquisition of a 3D image layer module uses the hardware of a realistic infrared camera. The software of the system consists of two parts: a 3D image computer expression module and a 3D image reconstruction module. A simulation platform is established. The test data of 3D image reconstruction accuracy and visual communication integrity of the designed system show that both of them show a good trend. In scheme 2, regarding digital image processing, the 3D image visual perception reconstruction is affected by the modeling conditions, and some images are incomplete and damaged. The depth camera and image processor that can be used in the visual communication technology are selected, and their internal parameters are modified to borrow them in the original system hardware. Gaussian filtering model combined with scale-invariant feature transform (SIFT) feature point extraction algorithm is adopted to select image feature points. Previous system reconstruction technology is used to upgrade the 3D digital image, and the feature point detection equation is adopted to detect the accuracy of the upgraded results. Based on the above hardware and software research, the 3D digital image system based on visual communication is successfully upgraded. The test platform is established, and the test samples are selected. Unlike the previous systems, the 3D image reconstruction accuracy of the designed visual communication system can be as high as 98%; the upgraded system has better image integrity and stronger performance than the previous systems and achieves higher visual sensing technology. In art education, it can provide a new content perspective for digital image art teaching.