Abstract
We present a marker-based geometric estimation framework for the absolute pose of a camera by analyzing the 1D observations in a single radially distorted pixel scanline. We leverage a pair of known co-planar pencils of lines, along with lens distortion parameters, to propose an ensemble of solvers exploring the space of estimation strategies applicable to our setup. First, we present a minimal algebraic solver requiring only six measurements and yielding eight solutions, which relies on the intersection of two conics defined by one of the pencils of lines. Then, we present a unique closed-form geometric solver from seven measurements. Finally, we present an homography-based formulation amenable to linear least-squares from eight or more measurements. Our geometric framework constitutes a theoretical analysis on the minimum geometric context necessary to solve in closed form for the absolute pose of a single camera from a single radially distorted scanline.
| Original language | English |
|---|---|
| Pages (from-to) | 15843-15851 |
| Number of pages | 9 |
| Journal | Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition |
| DOIs | |
| State | Published - 2025 |
| Event | 2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2025 - Nashville, United States Duration: 11 Jun 2025 → 15 Jun 2025 |
Keywords
- camera pose
- cross ratio
- rolling shutter
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