Three-dimensional reconstruction based on stereo vision technology is an important research direction in the field of computer vision, and has a wide range of applications in industrial measurement, medical image reconstruction, cultural relic preservation, robot navigation, virtual reality and other fields. However, the three-dimensional reconstruction of moving objects usually has poor accuracy, low efficiency and poor visualization effect due to the image noise, motion blur, complex and time-consuming calculation etc. In this article, a disparity optimization method based on depth change constraint is proposed, which utilizes the correlation of the adjacent frames in the continuous video sequence to eliminate mismatches and correct the wrong disparity values by introducing a depth change constraint threshold. The experiments on the video images which are taken by a binocular stereo vision system demonstrate that our method of removing incorrect matches bears satisfactory results and it can greatly improve the effect of the three-dimensional reconstruction of the moving objects.

基于立体视觉技术的三维重建是计算机视觉领域的一个重要研究方向，在工业测量、医学图像重建、文物保护、机器人导航、虚拟现实等领域有着广泛的应用。然而，由于图像噪声、运动模糊、计算复杂耗时等问题，运动物体的三维重建通常精度差、效率低、可视化效果差。 本文提出一种基于深度变化的视差优化方法提出了约束，它利用连续视频序列中相邻帧的相关性，通过引入深度变化约束阈值来消除失配并纠正错误的视差值。