Visual Design Comfort of OCULUS VR Panoramic Stereo Video Based on Image Recognition Algorithm

This article explores the issue of visual design comfort in OCULUS VR panoramic stereoscopic videos based on image recognition algorithms. Traditional flat video only includes information in two-dimensional space, while panoramic stereoscopic video contains more information and a richer visual experience. However, there are also some challenges, such as visual fatigue and exposure to inappropriate scenes. Therefore, how to ensure the visual comfort of people when watching panoramic stereoscopic videos is a very important task. This article analyzes and optimizes OCULUS VR panoramic stereoscopic videos using image recognition algorithms. We improve the comfort of video viewing by reducing the rapid movement and jumping of images in the video. At the same time, we consider the device positioning of OCULUS VR as an important factor in visual design, adjusting the lighting, color, and other parameters of the scene in the video to meet the needs of human eye observation. The experimental results show that the optimized OCULUS VR panoramic stereoscopic video has better comfort and user experience. This research result has certain reference significance for the development of 360-degree video visual design and virtual reality technology. In summary, this article focuses on the visual design comfort of OCULUS VR panoramic stereoscopic videos, and improves users' viewing comfort and visual experience through image recognition algorithms and optimization methods. This research achievement provides useful reference and inspiration for the development of related fields.