Research map / Learning theory and algorithms / Combinatorial and search optimization
A Sparse Resultant Based Method for Efficient Minimal Solvers
Check your idea against 108,967 papers
AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.
Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use the sparse resultant solver with the added equation xᵢ − λ instead of the heuristic Gröbner solver | Minimal camera-geometry solvers · Rel. pose λ+E+λ 6pt | solver template size: 53 × 105 -> 39 × 95 | Helped |
| Use the sparse resultant solver instead of the heuristic Gröbner solver | Minimal camera-geometry solvers · Rel. pose E+fλ 7pt | solver template size: 24 × 43 -> 22 × 41 | Helped |
| Use the sparse resultant solver instead of the heuristic Gröbner solver | Minimal camera-geometry solvers · Rel. pose F+λ 8pt | solver template size: 7 × 15 vs. 7 × 16 | Mixed |
| Use the sparse resultant solver instead of the previous solver | Minimal camera-geometry solvers · Rel. pose f+E+f 6pt | solver failures: 2.36 -> 0.52 | Helped |
| Use the sparse resultant solver instead of the previous solver | Minimal camera-geometry solvers · Rel. pose λ+E+λ 6pt | mean log10 normalized equation residual: -6.92 -> -8.99 | Helped |
| Use the sparse resultant solver instead of the previous solver | Minimal camera-geometry solvers · Rel. pose λ+E+λ 6pt | solver failures: 25.9 -> 14.66 | Helped |
| Use the sparse resultant solver instead of the previous solver | Minimal camera-geometry solvers · Rel. pose E+fλ 7pt, elim λ | solver failures: 7.58 -> 0.36 | Helped |
| Use the sparse resultant solver instead of the previous solver | Minimal camera-geometry solvers · Abs. pose P4Pfr | solver failures: 0 -> 0 | No clear effect |
| Use the sparse resultant solver rather than a polynomial eigenvalue formulation of the hidden-variable resultant | Resultant-based minimal solvers · Minimal camera-geometry problems | solver efficiency | Helped |
| Add the special-form equation xᵢ − λ rather than use a general-form u-resultant | Sparse resultant solver · Minimal camera-geometry problems | solver size | Helped |
| Test candidate bases for full rank before accepting them | Sparse resultant solver generation · Minimal camera-geometry problems | solver rank | Helped |
Closest papers by meaning
- Beyond Grobner Bases: Basis Selection for Minimal Solvers (CVPR 2018 · similarity 0.93)
- Solving Minimal Problems Without Matrix Inversion Using FFT-Based Interpolation (CVPR 2026 · similarity 0.91)
- A Clever Elimination Strategy for Efficient Minimal Solvers (CVPR 2017 · similarity 0.89)
- Efficient Solution of Point-Line Absolute Pose (CVPR 2024 · similarity 0.84)
- Minimal Perspective Autocalibration (CVPR 2024 · similarity 0.84)
- Camera Resection from Known Line Pencils and a Radially Distorted Scanline (CVPR 2025 · similarity 0.83)
Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.