English(EN) Robust Global Structure-from-Motion via View Graph Pruning

新的SfM方法通过剪枝视图图实现鲁棒的三维重建

作者 PulseAugur 编辑部 · [1 个来源] · 2026-08-25 04:00

研究人员开发了一个新的鲁棒全局运动恢复结构（SfM）框架，该框架解决了现有方法对视图图中错误边的敏感性问题。这种新颖的方法将视图图划分为局部一致的子图，在这些子图中估计相机姿态，然后使用基于RANSAC的边剪枝来移除不一致的连接。精炼后的视图图能够实现更精确的全局SfM，从而改善重建伪影并提高新视图合成的质量，这在具有挑战性的图像数据集上得到了证明。 AI

影响提高了三维重建质量和新视图合成，可能使AR/VR和机器人等应用受益。

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报道来源 [1]

arXiv cs.CV TIER_1 English(EN) · Jiamin Xu, Lixing Yao, Weichen Dai, Renshu Gu, Zunjie Zhu, Weiwei Xu, Gang Xu · 2026-08-25 04:00

通过视图图剪枝实现鲁棒的全局运动恢复结构

arXiv:2608.22054v1 Announce Type: new Abstract: Structure-from-Motion (SfM) aims to estimate camera poses and reconstruct 3D structures from a collection of unordered images. Compared with incremental SfM, global SfM achieves better scalability by jointly estimating camera poses …

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通过视图图剪枝实现鲁棒的全局运动恢复结构

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