Augmented reality can enhance people’s perception of the environment by embedding virtual objects or other information in real-time images. In this paper, the color image is used as a reference to calculate the confidence of the original depth map, and stereo matching is performed according to the feature points. The depth map is mainly enhanced by the color, edge, and segmentation results of the color image. A deep computing system based on augmented reality is designed. The system can use a binocular camera to collect object images in real time and obtain better parallax images by correcting the calibrated image. The semi-global block matching algorithm and depth calculation are used to realize the tracking registration of virtual objects. Experiments in different environments show that the system has good real-time performance, light invariance, and depth consistency.

通过将虚拟对象或其他信息嵌入实时图像中，增强现实可以增强人们对环境的感知。本文以彩色图像为参考来计算原始深度图的置信度，并根据特征点进行立体匹配。深度图主要通过彩色图像的颜色，边缘和分割结果得到增强。设计了一种基于增强现实的深度计算系统。该系统可以使用双目相机实时收集物体图像，并通过校正校准后的图像获得更好的视差图像。利用半全局块匹配算法和深度计算实现虚拟物体的跟踪配准。在不同环境中进行的实验表明，该系统具有良好的实时性能，光不变性，