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Multi-view stereo (MVS) reconstruction is essential for creating 3D models.The approach involves applying epipolar rectification followed by densematching for disparity estimation. However, existing approaches face challengesin applying dense matching for images with different viewpoints primarily dueto large differences in object scale. In this paper, we propose a sphericalmodel for epipolar rectification to minimize distortions caused by differencesin principal rays. We evaluate the proposed approach using two aerial-baseddatasets consisting of multi-camera head systems. We show through qualitativeand quantitative evaluation that the proposed approach performs better thanframe-based epipolar correction by enhancing the completeness of point cloudsby up to 4.05% while improving the accuracy by up to 10.23% using LiDAR data asground truth.

Investigating Spherical Epipolar Rectification for Multi-View Stereo 3D Reconstruction