Mobile visual media design based on artificial intelligence and augmented reality technology

In recent years, with the development of computer and network technologies, digital video and image information is emerging more and more, the information era based on multimedia information services is coming to us, and people's demand for visual media content such as video and images is becoming more and more extensive. In this paper, we use the Gaussian mixture model pixel detection technology method and image detection technology to study visual media to meet the various needs of users. SVM is used to perform classification tests on 3688 Chinese painting images and 4827 general images. The result is that the positive detection rate of national painting images is 87.25%, and the rate of non-national painting images being wrongly detected as national painting images is 7.63%. This indicates that the CCV feature also has a relatively good discriminative property for national painting images. The focus is on providing technical methods for the design of various visual media shapes such as sports and art, thus providing solutions to help users better access and use the digital multimedia information they are interested in. © 2023 Xiaoting Wang, published by Sciendo.