Intelligent visual enhancement system

Abstract

Vision-based augmented reality is a new kind of visual application technology, which transfers synthetic sensory information into a user's perception of a real environment. It is perceived by human senses. However, the existing visual enhancement equipment has single function, limited processing capacity and poor interaction. To overcome these shortcomings, we designed a visual enhancement system that integrates cloud computing, AR technology and deep learning. First, small, remote and wireless cameras are used to obtain image data, which need to be uploaded to a cloud. Then, the method of deep learning and feature matching is adopted to carry out facial consistency analysis, which improves the robustness of target detection. And stable target tracking is achieved by time sequence state filtering. Finally, the information of image analysis and processing is transmitted back to the AR device, so the prompts of target text and voice are given for intelligent auxiliary decision-making in time.