Stereo vision systems have become popular in computer vision applications, such as 3D reconstruction, object tracking, and autonomous navigation. However, traditional stereo vision systems that use rectilinear lenses may not be suitable for certain scenarios due to their limited field of view. This has led to the popularity of vision systems based on one or multiple fisheye cameras in different orientations, which can provide a field of view of 180x180 degrees or more. However, fisheye cameras introduce significant distortion at the edges that affects the accuracy of stereo matching and depth estimation. To overcome these limitations, this paper proposes a method for distortion-removal and depth estimation analysis for stereovision system using orthogonally divergent fisheye cameras (ODFC). The proposed method uses two virtual pinhole cameras (VPC), each VPC captures a small portion of the original view and presents it without any lens distortions, emulating the behavior of a pinhole camera. By carefully selecting the captured regions, it is possible to create a stereo pair using two VPCs. The performance of the proposed method is evaluated in both simulation using virtual environment and experiments using real cameras and their results compared to stereo cameras with parallel optical axes. The results demonstrate the effectiveness of the proposed method in terms of distortion removal and depth estimation accuracy.

翻译：立体视觉系统在计算机视觉应用中已变得十分普及，例如三维重建、目标跟踪和自主导航。然而，传统采用直线型镜头的立体视觉系统由于视野有限，可能并不适用于某些场景。这促使基于一个或多个不同朝向鱼眼相机的视觉系统逐渐流行，其能够提供180×180度或更大的视野。然而，鱼眼相机在图像边缘引入显著畸变，这会影响立体匹配和深度估计的精度。为克服这些局限，本文提出了一种针对正交发散鱼眼相机（ODFC）立体视觉系统的畸变去除与深度估计分析方法。该方法采用两个虚拟针孔相机（VPC），每个VPC捕获原始视图中的一小部分区域，并以无镜头畸变的形式呈现，模拟针孔相机的行为。通过精心选择捕获区域，可利用两个VPC构建立体像对。本文在虚拟环境仿真和真实相机实验中均对所提方法进行了评估，并将其结果与光轴平行的立体相机进行了比较。实验结果表明，该方法在畸变去除和深度估计精度方面具有有效性。