论文标题
调查用于多视图立体3D重建的球形表现矫正
Investigating Spherical Epipolar Rectification for Multi-View Stereo 3D Reconstruction
论文作者
论文摘要
多视图立体声（MVS）重建对于创建3D模型至关重要。该方法涉及应用表现整流，然后进行密集匹配以进行差异估计。但是，现有方法在应用密集匹配的图像时面临挑战，这些图像的观点不同，主要是由于对象尺度上的差异很大。在本文中，我们提出了一个用于表现整流的球形模型，以最大程度地减少主射线差异引起的扭曲。我们使用两个由多相机头系统组成的空中数据集评估了提出的方法。我们通过定性和定量评估表明，提出的方法通过将点云的完整性提高高达4.05％，同时使用激光雷达数据作为地面真相提高准确性高达10.23％，从而提高了高达4.05％的倍数。
Multi-view stereo (MVS) reconstruction is essential for creating 3D models. The approach involves applying epipolar rectification followed by dense matching for disparity estimation. However, existing approaches face challenges in applying dense matching for images with different viewpoints primarily due to large differences in object scale. In this paper, we propose a spherical model for epipolar rectification to minimize distortions caused by differences in principal rays. We evaluate the proposed approach using two aerial-based datasets consisting of multi-camera head systems. We show through qualitative and quantitative evaluation that the proposed approach performs better than frame-based epipolar correction by enhancing the completeness of point clouds by up to 4.05% while improving the accuracy by up to 10.23% using LiDAR data as ground truth.
