Search Results for author: Viktor Larsson

Found 36 papers, 15 papers with code

Handcrafted Outlier Detection Revisited

1 code implementation ECCV 2020 Luca Cavalli, Viktor Larsson, Martin Ralf Oswald, Torsten Sattler, Marc Pollefeys

As a result, outlier detection is a fundamental problem in computer vision and a wide range of approaches, from simple checks based on descriptor similarity to geometric verification, have been proposed over the last decades.

Computer Vision Outlier Detection +1

Calibration-free Structure-from-Motion with Calibrated Radial Trifocal Tensors

no code implementations ECCV 2020 Viktor Larsson, Nicolas Zobernig, Kasim Taskin, Marc Pollefeys

In this paper we consider the problem of Structure-from-Motion from images with unknown intrinsic calibration.

Optimal Thermal Management, Charging, and Eco-driving of Battery Electric Vehicles

no code implementations3 May 2022 Ahad Hamednia, Nikolce Murgovski, Jonas Fredriksson, Jimmy Forsman, Mitra Pourabdollah, Viktor Larsson

The formulated problem is then transformed into a hybrid dynamical system, where the dynamics in driving and charging modes are modeled with different functions and with different state and control vectors.

Camera Pose Estimation Using Implicit Distortion Models

no code implementations CVPR 2022 Linfei Pan, Marc Pollefeys, Viktor Larsson

Low-dimensional parametric models are the de-facto standard in computer vision for intrinsic camera calibration.

Camera Calibration Computer Vision +2

NICE-SLAM: Neural Implicit Scalable Encoding for SLAM

1 code implementation CVPR 2022 Zihan Zhu, Songyou Peng, Viktor Larsson, Weiwei Xu, Hujun Bao, Zhaopeng Cui, Martin R. Oswald, Marc Pollefeys

Neural implicit representations have recently shown encouraging results in various domains, including promising progress in simultaneous localization and mapping (SLAM).

Simultaneous Localization and Mapping

A Quasiconvex Formulation for Radial Cameras

no code implementations CVPR 2021 Carl Olsson, Viktor Larsson, Fredrik Kahl

In this paper we study structure from motion problems for 1D radial cameras.

Back to the Feature: Learning Robust Camera Localization from Pixels to Pose

1 code implementation CVPR 2021 Paul-Edouard Sarlin, Ajaykumar Unagar, Måns Larsson, Hugo Germain, Carl Toft, Viktor Larsson, Marc Pollefeys, Vincent Lepetit, Lars Hammarstrand, Fredrik Kahl, Torsten Sattler

In this paper, we go Back to the Feature: we argue that deep networks should focus on learning robust and invariant visual features, while the geometric estimation should be left to principled algorithms.

Camera Localization Metric Learning +1

Localizing Unsynchronized Sensors with Unknown Sources

1 code implementation6 Feb 2021 Dalia El Badawy, Viktor Larsson, Marc Pollefeys, Ivan Dokmanić

We look at the general case where neither the emission times of the sources nor the reference time frames of the receivers are known.

On the Tightness of Semidefinite Relaxations for Rotation Estimation

no code implementations6 Jan 2021 Lucas Brynte, Viktor Larsson, José Pedro Iglesias, Carl Olsson, Fredrik Kahl

In studying the empirical performance we note that there are few failure cases reported in the literature, in particular for estimation problems with a single rotation, motivating us to gain further theoretical understanding.

Computer Vision

Orthographic-Perspective Epipolar Geometry

no code implementations ICCV 2021 Viktor Larsson, Marc Pollefeys, Magnus Oskarsson

In this paper we consider the epipolar geometry between orthographic and perspective cameras.

Camera Calibration

Infrastructure-based Multi-Camera Calibration using Radial Projections

1 code implementation ECCV 2020 Yukai Lin, Viktor Larsson, Marcel Geppert, Zuzana Kukelova, Marc Pollefeys, Torsten Sattler

In particular, our approach is more robust than the naive approach of first estimating intrinsic parameters and pose per camera before refining the extrinsic parameters of the system.

Camera Calibration Self-Driving Cars +1

AdaLAM: Revisiting Handcrafted Outlier Detection

3 code implementations7 Jun 2020 Luca Cavalli, Viktor Larsson, Martin Ralf Oswald, Torsten Sattler, Marc Pollefeys

Local feature matching is a critical component of many computer vision pipelines, including among others Structure-from-Motion, SLAM, and Visual Localization.

Computer Vision Key Point Matching +2

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.

GAPS: Generator for Automatic Polynomial Solvers

1 code implementation24 Apr 2020 Bo Li, Viktor Larsson

Minimal problems in computer vision raise the demand of generating efficient automatic solvers for polynomial equation systems.

Computer Vision

Minimal Solvers for Rectifying from Radially-Distorted Conjugate Translations

1 code implementation4 Nov 2019 James Pritts, Zuzana Kukelova, Viktor Larsson, Yaroslava Lochman, Ondřej Chum

This paper introduces minimal solvers that jointly solve for radial lens undistortion and affine-rectification using local features extracted from the image of coplanar translated and reflected scene texture, which is common in man-made environments.

Revisiting Radial Distortion Absolute Pose

no code implementations ICCV 2019 Viktor Larsson, Torsten Sattler, Zuzana Kukelova, Marc Pollefeys

In this paper we aim to fill this gap in the literature by proposing the first minimal solvers which can jointly estimate distortion models together with camera pose.

Pose Estimation

Minimal Solvers for Rectifying from Radially-Distorted Scales and Change of Scales

1 code implementation25 Jul 2019 James Pritts, Zuzana Kukelova, Viktor Larsson, Yaroslava Lochman, Ondřej Chum

The proposed solvers use the affine invariant that coplanar repeats have the same scale in rectified space.

Rectification from Radially-Distorted Scales

1 code implementation16 Jul 2018 James Pritts, Zuzana Kukelova, Viktor Larsson, Ondrej Chum

This paper introduces the first minimal solvers that jointly estimate lens distortion and affine rectification from repetitions of rigidly transformed coplanar local features.

Camera Pose Estimation With Unknown Principal Point

no code implementations CVPR 2018 Viktor Larsson, Zuzana Kukelova, Yinqiang Zheng

To estimate the 6-DoF extrinsic pose of a pinhole camera with partially unknown intrinsic parameters is a critical sub-problem in structure-from-motion and camera localization.

Camera Localization Pose Estimation

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.

Computer Vision

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.

Computer Vision

Radially-Distorted Conjugate Translations

1 code implementation CVPR 2018 James Pritts, Zuzana Kukelova, Viktor Larsson, Ondrej Chum

The solvers are derived from constraints induced by the conjugate translations of an imaged scene plane, which are integrated with the division model for radial lens distortion.

Polynomial Solvers for Saturated Ideals

no code implementations ICCV 2017 Viktor Larsson, Kalle Astrom, Magnus Oskarsson

In this paper we present a new method for creating polynomial solvers for problems where a (possibly infinite) subset of the solutions are undesirable or uninteresting.

Making Minimal Solvers for Absolute Pose Estimation Compact and Robust

no code implementations ICCV 2017 Viktor Larsson, Zuzana Kukelova, Yinqiang Zheng

In this paper we present new techniques for constructing compact and robust minimal solvers for absolute pose estimation.

Pose Estimation

Efficient Solvers for Minimal Problems by Syzygy-Based Reduction

no code implementations CVPR 2017 Viktor Larsson, Kalle Astrom, Magnus Oskarsson

In this paper we study the problem of automatically generating polynomial solvers for minimal problems.

Computer Vision

Compact Matrix Factorization With Dependent Subspaces

no code implementations CVPR 2017 Viktor Larsson, Carl Olsson

This imposes constraints on the matrix elements which allow for estimation of missing entries.

Optimal Relative Pose With Unknown Correspondences

no code implementations CVPR 2016 Johan Fredriksson, Viktor Larsson, Carl Olsson, Fredrik Kahl

Previous work on estimating the epipolar geometry of two views relies on being able to reliably match feature points based on appearance.

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