Topologically Stable Hough Transform
Fuente:
arXiv
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| Auteurs principaux: | , , , |
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| Format: | Preprint |
| Publié: |
2026
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| _version_ | 1866912962854256640 |
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| author | Huber, Stefan Huszár, Kristóf Kerber, Michael Uray, Martin |
| author_facet | Huber, Stefan Huszár, Kristóf Kerber, Michael Uray, Martin |
| contents | We propose an alternative formulation of the well-known Hough transform to detect lines in point clouds. Replacing the discretized voting scheme of the classical Hough transform by a continuous score function, its persistent features in the sense of persistent homology give a set of candidate lines. We also devise and implement an algorithm to efficiently compute these candidate lines. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_08245 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Topologically Stable Hough Transform Huber, Stefan Huszár, Kristóf Kerber, Michael Uray, Martin Computational Geometry Computer Vision and Pattern Recognition We propose an alternative formulation of the well-known Hough transform to detect lines in point clouds. Replacing the discretized voting scheme of the classical Hough transform by a continuous score function, its persistent features in the sense of persistent homology give a set of candidate lines. We also devise and implement an algorithm to efficiently compute these candidate lines. |
| title | Topologically Stable Hough Transform |
| topic | Computational Geometry Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2603.08245 |