35 citations · 58 across the 11 of their papers we have counts for
12 papers
Robust and Accurate Cylinder Triangulation
Anna Gummeson, Magnus Oskarsson
In this paper we present methods for triangulation of infinite cylinders from image line silhouettes. We show numerically that linear estimation of a general quadric surface is inh…
Extending GCC-PHAT using Shift Equivariant Neural Networks
Axel Berg, Mark O'Connor, Kalle Åström +1
Speaker localization using microphone arrays depends on accurate time delay estimation techniques. For decades, methods based on the generalized cross correlation with phase transf…
Multiple Offsets Multilateration: a new paradigm for sensor network calibration with unsynchronized reference nodes
Luca Ferranti, Kalle Åström, Magnus Oskarsson +2
Positioning using wave signal measurements is used in several applications, such as GPS systems, structure from sound and Wifi based positioning. Mathematically, such problems requ…
Points to Patches: Enabling the Use of Self-Attention for 3D Shape Recognition
Axel Berg, Magnus Oskarsson, Mark O'Connor
While the Transformer architecture has become ubiquitous in the machine learning field, its adaptation to 3D shape recognition is non-trivial. Due to its quadratic computational co…
Homotopy Continuation for Sensor Networks Self-Calibration
Luca Ferranti, Kalle Åström, Magnus Oskarsson +2
Given a sensor network, TDOA self-calibration aims at simultaneously estimating the positions of receivers and transmitters, and transmitters time offsets. This can be formulated a…
Detailed 3D Human Body Reconstruction from Multi-view Images Combining Voxel Super-Resolution and Learned Implicit Representation
Zhongguo Li, Magnus Oskarsson, Anders Heyden
The task of reconstructing detailed 3D human body models from images is interesting but challenging in computer vision due to the high freedom of human bodies. In order to tackle t…
A novel joint points and silhouette-based method to estimate 3D human pose and shape
Zhongguo Li, Anders Heyden, Magnus Oskarsson
This paper presents a novel method for 3D human pose and shape estimation from images with sparse views, using joint points and silhouettes, based on a parametric model. Firstly, t…
Deep Ordinal Regression with Label Diversity
Axel Berg, Magnus Oskarsson, Mark O'Connor
Regression via classification (RvC) is a common method used for regression problems in deep learning, where the target variable belongs to a set of continuous values. By discretizi…
Sensor Networks TDOA Self-Calibration: 2D Complexity Analysis and Solutions
Luca Ferranti, Kalle Åström, Magnus Oskarsson +2
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…
Massive MIMO-based Localization and Mapping Exploiting Phase Information of Multipath Components
Xuhong Li, Erik Leitinger, Magnus Oskarsson +2
In this paper, we present a robust multipath-based localization and mapping framework that exploits the phases of specular multipath components (MPCs) using a massive multiple-inpu…
A fast minimal solver for absolute camera pose with unknown focal length and radial distortion from four planar points
Magnus Oskarsson
In this paper we present a fast minimal solver for absolute camera pose estimation from four known points that lie in a plane. We assume a perspective camera model with unknown foc…
Beyond Gröbner Bases: Basis Selection for Minimal Solvers
Viktor Larsson, Magnus Oskarsson, Kalle Åström +3
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…