Abstract
Abstract. 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.
Cited by
2 articles.
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1. A CRITICAL ANALYSIS OF INTERNAL RELIABILITY FOR UNCERTAINTY QUANTIFICATION OF DENSE IMAGE MATCHING IN MULTI-VIEW STEREO;ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences;2023-12-05
2. Advancing Accurate Depth Estimation and Perception with Angled Stereo Camera;2023 15th International Conference on Information Technology and Electrical Engineering (ICITEE);2023-10-26