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Magnus Oskarsson

14 accepted papers

2024

Noisy One-point Homographies are Surprisingly Good

CVPR 2024poster

Two-view homography estimation is a classic and fundamental problem in computer vision. While conceptually simple the problem quickly becomes challenging when multiple planes are visible in the image pair. Even with correct matches each individual plane (homography) might have a very low number of i…

Cited by 2SourcePDFScholar
2022

Multiple Offsets Multilateration: A New Paradigm for Sensor Network Calibration with Unsynchronized Reference Nodes

ICASSP 2022accepted

Positioning using wave signal measurements is used in several applications, such as GPS systems, structure from sound and Wifi based positioning. Mathematically, such problems require the computation of the positions of receivers and/or transmitters as well as time offsets if the devices are unsynch…

Cited by 0SourceScholar
2021

Fast and Robust Stratified Self-Calibration Using Time-Difference-Of-Arrival Measurements

ICASSP 2021accepted

In this paper we study the problem of estimating receiver and sender positions using time-difference-of-arrival measurements. For this, we use a stratified, two-tiered approach. In the first step the problem is converted to a low-rank matrix estimation problem. We present new, efficient solvers for…

Cited by 0SourceScholar
2021

Sensor Networks TDOA Self-Calibration: 2D Complexity Analysis and Solutions

ICASSP 2021accepted

Given a network of receivers and transmitters, the process of determining their positions from measured pseudoranges is known as network self-calibration. In this paper we consider 2D networks with synchronized receivers but unsynchronized transmitters and the corresponding calibration techniques, k…

Cited by 0SourceScholar
2020

Upgrade Methods for Stratified Sensor Network Self-Calibration

ICASSP 2020accepted

Estimating receiver and sender positions is often solved using a stratified, two-tiered approach. In the first step the problem is converted to a low-rank matrix estimation problem. The second step can be seen as an affine upgrade. This affine upgrade is the focus of this paper. In the paper new eff…

Cited by 0SourceScholar
2019

Robust Self-calibration of Constant Offset Time-difference-of-arrival

ICASSP 2019accepted

In this paper we study the problem of estimating receiver and sender positions from time-difference-of-arrival measurements, assuming an unknown constant time-difference-of-arrival offset. This problem is relevant for example for repetitive sound events. In this paper it is shown that there are thre…

Cited by 0SourceScholar
2018

Beyond Grobner Bases: Basis Selection for Minimal Solvers

CVPR 2018poster

Many computer vision applications require robust estimation of the underlying geometry, in terms of camera motion and 3D structure of the scene. These robust methods often rely on running minimal solvers in a RANSAC framework. In this paper we show how we can make polynomial solvers based on the act…

Cited by 74SourcePDFScholar
2016

Trust No One: Low Rank Matrix Factorization Using Hierarchical RANSAC

CVPR 2016poster

In this paper we present a system for performing low rank matrix factorization. Low-rank matrix factorization is an essential problem in many areas including computer vision, with applications in e.g. affine structure-from-motion, photometric stereo, and non-rigid structure from motion. We specifica…

Cited by 9PDFcodeScholar