Sparse resultant-based minimal solvers in computer vision and their connection with the action matrix

DOI10.1007/s10851-024-01182-1zbMATH Open1547.68761MaRDI QIDQ6596057

Janne Heikkilä, Snehal Bhayani, Zuzana Kukelova

Publication date: 2 September 2024

Published in: Journal of Mathematical Imaging and Vision (Search for Journal in Brave)

zbMATH Keywords

Gröbner basissparse resultantsminimal solversaction matrixgeometric computer vision

Mathematics Subject Classification ID

Numerical computation of solutions to systems of equations (65H10) Gröbner bases; other bases for ideals and modules (e.g., Janet and border bases) (13P10) Machine vision and scene understanding (68T45)

Cites Work

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• Stable normal forms for polynomial system solving
• Solving Polynomial Systems via Truncated Normal Forms
• Matrix eigenproblems are at the heart of polynomial system solving
• A subdivision-based algorithm for the sparse resultant

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