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Related papers: PLMP -- Point-Line Minimal Problems in Complete Mu…

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We present a complete classification of minimal problems for generic arrangements of points and lines in space observed partially by three calibrated perspective cameras when each line is incident to at most one point. This is a large class…

Computer Vision and Pattern Recognition · Computer Science 2020-03-12 Timothy Duff , Kathlén Kohn , Anton Leykin , Tomas Pajdla

We completely classify all minimal problems for Structure-from-Motion (SfM) where arrangements of points and lines are fully observed by multiple uncalibrated pinhole cameras. We find 291 minimal problems, 73 of which have unique solutions…

Computer Vision and Pattern Recognition · Computer Science 2025-08-01 Kim Kiehn , Albin Ahlbäck , Kathlén Kohn

We introduce a new family of minimal problems for reconstruction from multiple views. Our primary focus is a novel approach to autocalibration, a long-standing problem in computer vision. Traditional approaches to this problem, such as…

Computer Vision and Pattern Recognition · Computer Science 2024-05-10 Andrea Porfiri Dal Cin , Timothy Duff , Luca Magri , Tomas Pajdla

We present a new insight into the systematic generation of minimal solvers in computer vision, which leads to smaller and faster solvers. Many minimal problem formulations are coupled sets of linear and polynomial equations where image…

Computer Vision and Pattern Recognition · Computer Science 2017-03-16 Zuzana Kukelova , Joe Kileel , Bernd Sturmfels , Tomas Pajdla

We propose a minimal solution for pose estimation using both points and lines for a multi-perspective camera. In this paper, we treat the multi-perspective camera as a collection of rigidly attached perspective cameras. These type of…

Computer Vision and Pattern Recognition · Computer Science 2018-07-27 Pedro Miraldo , Tiago Dias , Srikumar Ramalingam

We revisit certain problems of pose estimation based on 3D--2D correspondences between features which may be points or lines. Specifically, we address the two previously-studied minimal problems of estimating camera extrinsics from $p \in…

Computer Vision and Pattern Recognition · Computer Science 2024-04-26 Petr Hruby , Timothy Duff , Marc Pollefeys

Camera calibration is a crucial prerequisite in many applications of computer vision. In this paper, a new, geometry-based camera calibration technique is proposed, which resolves two main issues associated with the widely used Zhang's…

Computer Vision and Pattern Recognition · Computer Science 2019-08-20 Jen-Hui Chuang , Chih-Hui Ho , Ardian Umam , HsinYi Chen , Mu-Tien Lu , Jenq-Neng Hwang , Tai-An Chen

In this paper, a statistically optimal solution to the Perspective-n-Point (PnP) problem is presented. Many solutions to the PnP problem are geometrically optimal, but do not consider the uncertainties of the observations. In addition, it…

Computer Vision and Pattern Recognition · Computer Science 2016-07-28 Steffen Urban , Jens Leitloff , Stefan Hinz

In 3D reconstruction, the recovery of the calibration parameters of the cameras is paramount since it provides metric information about the observed scene, e.g., measures of angles and ratios of distances. Autocalibration enables the…

Computer Vision and Pattern Recognition · Computer Science 2019-01-21 José I. Ronda , Antonio Valdés , Guillermo Gallego

A non-iterative auto-calibration algorithm is presented. It deals with a minimal set of six scene points in three views taken by a camera with fixed but unknown intrinsic parameters. Calibration is based on the image correspondences only.…

Computer Vision and Pattern Recognition · Computer Science 2014-11-12 Evgeniy Martyushev

A minimalist vision system uses the smallest number of pixels needed to solve a vision task. While traditional cameras use a large grid of square pixels, a minimalist camera uses freeform pixels that can take on arbitrary shapes to increase…

Computer Vision and Pattern Recognition · Computer Science 2025-04-29 Jeremy Klotz , Shree K. Nayar

Relative pose estimation using point correspondences (PC) is a widely used technique. A minimal configuration of six PCs is required for two views of generalized cameras. In this paper, we present several minimal solvers that use six PCs to…

Computer Vision and Pattern Recognition · Computer Science 2024-11-14 Banglei Guan , Ji Zhao , Laurent Kneip

We present an approach to solving hard geometric optimization problems in the RANSAC framework. The hard minimal problems arise from relaxing the original geometric optimization problem into a minimal problem with many spurious solutions.…

Computer Vision and Pattern Recognition · Computer Science 2021-12-08 Petr Hruby , Timothy Duff , Anton Leykin , Tomas Pajdla

The problem of calibration from straight lines is fundamental in geometric computer vision, with well-established theoretical foundations. However, its practical applicability remains limited, particularly in real-world outdoor scenarios.…

Computer Vision and Pattern Recognition · Computer Science 2025-05-02 Gregory Schroeder , Mohamed Sabry , Cristina Olaverri-Monreal

We present a new framework for multi-view geometry in computer vision. A camera is a mapping between $\mathbb{P}^3$ and a line congruence. This model, which ignores image planes and measurements, is a natural abstraction of traditional…

Algebraic Geometry · Mathematics 2016-12-28 Jean Ponce , Bernd Sturmfels , Matthew Trager

Understanding perspective is fundamental to human visual perception, yet the extent to which multimodal large language models (MLLMs) internalize perspective geometry remains unclear. We introduce MMPerspective, the first benchmark…

Computer Vision and Pattern Recognition · Computer Science 2025-11-26 Yolo Y. Tang , Pinxin Liu , Zhangyun Tan , Mingqian Feng , Rui Mao , Chao Huang , Jing Bi , Yunzhong Xiao , Susan Liang , Hang Hua , Ali Vosoughi , Luchuan Song , Zeliang Zhang , Chenliang Xu

Camera calibration is an essential first step in setting up 3D Computer Vision systems. Commonly used parametric camera models are limited to a few degrees of freedom and thus often do not optimally fit to complex real lens distortion. In…

Computer Vision and Pattern Recognition · Computer Science 2020-06-24 Thomas Schöps , Viktor Larsson , Marc Pollefeys , Torsten Sattler

Let $P$ be an orthogonal polygon. Consider a sliding camera that travels back and forth along an orthogonal line segment $s\in P$ as its \emph{trajectory}. The camera can see a point $p\in P$ if there exists a point $q\in s$ such that $pq$…

Computational Geometry · Computer Science 2013-03-12 Stephane Durocher , Saeed Mehrabi

Blind Perspective-n-Point (PnP) is the problem of estimating the position and orientation of a camera relative to a scene, given 2D image points and 3D scene points, without prior knowledge of the 2D-3D correspondences. Solving for pose and…

Computer Vision and Pattern Recognition · Computer Science 2020-09-09 Dylan Campbell , Liu Liu , Stephen Gould

Multi-view understanding, the ability to reconcile visual information across diverse viewpoints for effective navigation, manipulation, and 3D scene comprehension, is a fundamental challenge in Multi-Modal Large Language Models (MLLMs) to…

Computer Vision and Pattern Recognition · Computer Science 2025-04-29 Chun-Hsiao Yeh , Chenyu Wang , Shengbang Tong , Ta-Ying Cheng , Ruoyu Wang , Tianzhe Chu , Yuexiang Zhai , Yubei Chen , Shenghua Gao , Yi Ma
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