基于双目立体视觉的三维重构是计算机视觉技术的主要内容之一, 在机器人视觉导航、航空测绘、医学成像和工业检测等很多领域都有广泛的应用。提出一种基于网格点投影灰度相似性的双目立体视觉的三维重建新方法。首先将被测物体所在的世界坐标系划分成间距相等的矩形网格, 将网格节点作为潜在的物点投影到左右图像坐标系上, 然后根据不同深度的空间点在两幅图像上相应的灰度相似性来判断被测物体在三维空间中的深度信息。通过Matlab平台下的仿真实验证明了本方法的三维重建效果和计算效率都要优于传统方法。与传统的图像匹配方法相比, 具有算法简单、速度快、精度高、且不受摄像装置非线性畸变影响的优点。

The 3D reconstruction based on binocular stereo vision is a main part of the computer vision technology and it has a variety of applications such as robot navigation, aerial surveying and mapping, medical imaging, industrial inspection, etc.. A new binocular stereo vision method based on comparing gray value of the projection points is proposed to reconstruct 3D world. This method divides the world coordinate system into grids and the nodes are considered as candidates of the object coordinates. A group of points with varying depth information are projected on the two pictures. The difference of the gray values of the corresponding pairs implies the depth information of the object in 3D world. It is proved superior over traditional methods in the effectiveness and efficiency by simulatron experiments using Matlab. Compared with traditional method based on image matching, this algorithm has obvious superiority in simplicity, computation and accuracy. Also, it will not be affected by the nonlinear distortion from the camera.