Single-View Rolling-Shutter SfM
Fuente:
arXiv
Enregistré dans:
| Auteurs principaux: | , , , |
|---|---|
| Format: | Preprint |
| Publié: |
2026
|
| Sujets: | |
| Accès en ligne: | |
| Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
| _version_ | 1866908881911808000 |
|---|---|
| author | Muñoz, Sofía Errázuriz Kiehn, Kim Hruby, Petr Kohn, Kathlén |
| author_facet | Muñoz, Sofía Errázuriz Kiehn, Kim Hruby, Petr Kohn, Kathlén |
| contents | Rolling-shutter (RS) cameras are ubiquitous, but RS SfM (structure-from-motion) has not been fully solved yet. This work suggests an approach to remedy this: We characterize RS single-view geometry of observed world points or lines. Exploiting this geometry, we describe which motion and scene parameters can be recovered from a single RS image and systematically derive minimal reconstruction problems. We evaluate several representative cases with proof-of-concept solvers, highlighting both feasibility and practical limitations. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_11888 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Single-View Rolling-Shutter SfM Muñoz, Sofía Errázuriz Kiehn, Kim Hruby, Petr Kohn, Kathlén Computer Vision and Pattern Recognition Algebraic Geometry Rolling-shutter (RS) cameras are ubiquitous, but RS SfM (structure-from-motion) has not been fully solved yet. This work suggests an approach to remedy this: We characterize RS single-view geometry of observed world points or lines. Exploiting this geometry, we describe which motion and scene parameters can be recovered from a single RS image and systematically derive minimal reconstruction problems. We evaluate several representative cases with proof-of-concept solvers, highlighting both feasibility and practical limitations. |
| title | Single-View Rolling-Shutter SfM |
| topic | Computer Vision and Pattern Recognition Algebraic Geometry |
| url | https://arxiv.org/abs/2603.11888 |