Search Results for author: Tomas Pajdla

Found 34 papers, 10 papers with code

PL₁P - Point-line Minimal Problems under Partial Visibility in Three Views

no code implementations ECCV 2020 Timothy Duff, Kathlén Kohn, Anton Leykin, Tomas Pajdla

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.

3D Reconstruction

On the Usage of the Trifocal Tensor in Motion Segmentation

1 code implementation ECCV 2020 Federica Arrigoni, Luca Magri, Tomas Pajdla

Motion segmentation, i. e., the problem of clustering data in multiple images based on different 3D motions, is an important task for reconstructing and understanding dynamic scenes.

Motion Segmentation

Reconstructing Small 3D Objects in front of a Textured Background

no code implementations24 May 2021 Petr Hruby, Tomas Pajdla

It is a particular variation of multibody structure from motion, which specializes to two objects only.

3D Reconstruction Structure from Motion

Galois/monodromy groups for decomposing minimal problems in 3D reconstruction

no code implementations10 May 2021 Timothy Duff, Viktor Korotynskiy, Tomas Pajdla, Margaret H. Regan

We consider three classical cases--3-point absolute pose, 5-point relative pose, and 4-point homography estimation for calibrated cameras--where the decomposition and symmetries may be naturally understood in terms of the Galois/monodromy group.

3D Reconstruction Homography Estimation +1

Making Affine Correspondences Work in Camera Geometry Computation

1 code implementation ECCV 2020 Daniel Barath, Michal Polic, Wolfgang Förstner, Torsten Sattler, Tomas Pajdla, Zuzana Kukelova

The main advantage of such solvers is that their sample size is smaller, e. g., only two instead of four matches are required to estimate a homography.

Homography Estimation

From two rolling shutters to one global shutter

no code implementations CVPR 2020 Cenek Albl, Zuzana Kukelova, Viktor Larsson, Tomas Pajdla, Konrad Schindler

Most consumer cameras are equipped with electronic rolling shutter, leading to image distortions when the camera moves during image capture.

PL${}_{1}$P -- Point-line Minimal Problems under Partial Visibility in Three Views

no code implementations10 Mar 2020 Timothy Duff, Kathlén Kohn, Anton Leykin, Tomas Pajdla

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.

3D Reconstruction

Robust Motion Segmentation from Pairwise Matches

1 code implementation ICCV 2019 Federica Arrigoni, Tomas Pajdla

In this paper we address a classification problem that has not been considered before, namely motion segmentation given pairwise matches only.

General Classification Motion Segmentation

PLMP -- Point-Line Minimal Problems in Complete Multi-View Visibility

1 code implementation24 Mar 2019 Timothy Duff, Kathlén Kohn, Anton Leykin, Tomas Pajdla

We present a complete classification of all minimal problems for generic arrangements of points and lines completely observed by calibrated perspective cameras.

3D Reconstruction General Classification

Trifocal Relative Pose from Lines at Points and its Efficient Solution

1 code implementation23 Mar 2019 Ricardo Fabbri, Timothy Duff, Hongyi Fan, Margaret Regan, David da Costa de Pinho, Elias Tsigaridas, Charles Wampler, Jonathan Hauenstein, Benjamin Kimia, Anton Leykin, Tomas Pajdla

We present a new minimal problem for relative pose estimation mixing point features with lines incident at points observed in three views and its efficient homotopy continuation solver.

Pose Estimation Structure from Motion

Linear solution to the minimal absolute pose rolling shutter problem

no code implementations30 Dec 2018 Zuzana Kukelova, Cenek Albl, Akihiro Sugimoto, Tomas Pajdla

Our best 6-point solver, based on the new alternation technique, shows an identical or even better performance than the state-of-the-art R6P solver and is two orders of magnitude faster.

Neighbourhood Consensus Networks

3 code implementations NeurIPS 2018 Ignacio Rocco, Mircea Cimpoi, Relja Arandjelović, Akihiko Torii, Tomas Pajdla, Josef Sivic

Second, we demonstrate that the model can be trained effectively from weak supervision in the form of matching and non-matching image pairs without the need for costly manual annotation of point to point correspondences.

Ranked #2 on Semantic correspondence on PF-PASCAL (PCK (weak) metric)

Semantic correspondence Visual Localization

Fast and Accurate Camera Covariance Computation for Large 3D Reconstruction

no code implementations ECCV 2018 Michal Polic, Wolfgang Förstner, Tomas Pajdla

Estimating uncertainty of camera parameters computed in Structure from Motion (SfM) is an important tool for evaluating the quality of the reconstruction and guiding the reconstruction process.

3D Reconstruction Structure from Motion

Beyond Grobner Bases: Basis Selection for Minimal Solvers

no code implementations CVPR 2018 Viktor Larsson, Magnus Oskarsson, Kalle Astrom, Alge Wallis, Zuzana Kukelova, Tomas Pajdla

In this paper we show how we can make polynomial solvers based on the action matrix method faster, by careful selection of the monomial bases.

Beyond Gröbner Bases: Basis Selection for Minimal Solvers

no code implementations12 Mar 2018 Viktor Larsson, Magnus Oskarsson, Kalle Åström, Alge Wallis, Zuzana Kukelova, Tomas Pajdla

In this paper we show how we can make polynomial solvers based on the action matrix method faster, by careful selection of the monomial bases.

On the Two-View Geometry of Unsynchronized Cameras

no code implementations CVPR 2017 Cenek Albl, Zuzana Kukelova, Andrew Fitzgibbon, Jan Heller, Matej Smid, Tomas Pajdla

We present new methods for simultaneously estimating camera geometry and time shift from video sequences from multiple unsynchronized cameras.

A clever elimination strategy for efficient minimal solvers

no code implementations CVPR 2017 Zuzana Kukelova, Joe Kileel, Bernd Sturmfels, Tomas Pajdla

We present a new insight into the systematic generation of minimal solvers in computer vision, which leads to smaller and faster solvers.

Distortion Varieties

no code implementations6 Oct 2016 Joe Kileel, Zuzana Kukelova, Tomas Pajdla, Bernd Sturmfels

The distortion varieties of a given projective variety are parametrized by duplicating coordinates and multiplying them with monomials.

Rolling Shutter Absolute Pose Problem With Known Vertical Direction

no code implementations CVPR 2016 Cenek Albl, Zuzana Kukelova, Tomas Pajdla

We compare our R5Pup to the state of the art RS and perspective methods and demonstrate that it outperforms them when vertical direction is known in the range of accuracy available on modern mobile devices.

Structure from Motion

NetVLAD: CNN architecture for weakly supervised place recognition

13 code implementations CVPR 2016 Relja Arandjelović, Petr Gronat, Akihiko Torii, Tomas Pajdla, Josef Sivic

We tackle the problem of large scale visual place recognition, where the task is to quickly and accurately recognize the location of a given query photograph.

Image Retrieval Visual Place Recognition

R6P - Rolling Shutter Absolute Camera Pose

no code implementations CVPR 2015 Cenek Albl, Zuzana Kukelova, Tomas Pajdla

Therefore we can use the standard P3P algorithm to estimate camera orientation and to bring the camera rotation matrix close to the identity.

24/7 Place Recognition by View Synthesis

no code implementations CVPR 2015 Akihiko Torii, Relja Arandjelovic, Josef Sivic, Masatoshi Okutomi, Tomas Pajdla

We address the problem of large-scale visual place recognition for situations where the scene undergoes a major change in appearance, for example, due to illumination (day/night), change of seasons, aging, or structural modifications over time such as buildings built or destroyed.

Visual Place Recognition

Radial Distortion Homography

no code implementations CVPR 2015 Zuzana Kukelova, Jan Heller, Martin Bujnak, Tomas Pajdla

The importance of precise homography estimation is often underestimated even though it plays a crucial role in various vision applications such as plane or planarity detection, scene degeneracy tests, camera motion classification, image stitching, and many more.

Homography Estimation Image Stitching

Hand-Eye and Robot-World Calibration by Global Polynomial Optimization

no code implementations13 Feb 2014 Jan Heller, Didier Henrion, Tomas Pajdla

We show that the method of convex linear matrix inequality (LMI) relaxations can be used to effectively solve these problems and to obtain globally optimal solutions.

Visual Place Recognition with Repetitive Structures

no code implementations CVPR 2013 Akihiko Torii, Josef Sivic, Tomas Pajdla, Masatoshi Okutomi

Even more importantly, they violate the feature independence assumed in the bag-of-visual-words representation which often leads to over-counting evidence and significant degradation of retrieval performance.

Visual Place Recognition

Learning and Calibrating Per-Location Classifiers for Visual Place Recognition

no code implementations CVPR 2013 Petr Gronat, Guillaume Obozinski, Josef Sivic, Tomas Pajdla

The aim of this work is to localize a query photograph by finding other images depicting the same place in a large geotagged image database.

Object Recognition Two-sample testing +1

Euclidean Upgrade from a Minimal Number of Segments

no code implementations25 Apr 2013 Tanja Schilling, Tomas Pajdla

In this paper, we propose an algebraic approach to upgrade a projective reconstruction to a Euclidean one, and aim at computing the rectifying homography from a minimal number of 9 segments of known length.

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