Search Results for author: Lennart Svensson

Found 38 papers, 19 papers with code

Iterated Posterior Linearization PMB Filter for 5G SLAM

no code implementations5 Dec 2021 Yu Ge, Yibo Wu, Fan Jiang, Ossi Kaltiokallio, Jukka Talvitie, Mikko Valkama, Lennart Svensson, Henk Wymeersch

In this paper, we study the linearization of the measurement function with respect to the posterior PDF, and implement the iterated posterior linearization filter into the Poisson multi-Bernoulli SLAM filter.

Simultaneous Localization and Mapping

A time-weighted metric for sets of trajectories to assess multi-object tracking algorithms

1 code implementation26 Oct 2021 Ángel F. García-Fernández, Abu Sajana Rahmathullah, Lennart Svensson

This paper proposes a metric for sets of trajectories to evaluate multi-object tracking algorithms that includes time-weighted costs for localisation errors of properly detected targets, for false targets, missed targets and track switches.

Multi-Object Tracking

A Computationally Efficient EK-PMBM Filter for Bistatic mmWave Radio SLAM

no code implementations8 Sep 2021 Yu Ge, Ossi Kaltiokallio, Hyowon Kim, Fan Jiang, Jukka Talvitie, Mikko Valkama, Lennart Svensson, Sunwoo Kim, Henk Wymeersch

Millimeter wave (mmWave) signals are useful for simultaneous localization and mapping (SLAM), due to their inherent geometric connection to the propagation environment and the propagation channel.

Simultaneous Localization and Mapping

Extended Object Tracking Using Sets Of Trajectories with a PHD Filter

no code implementations2 Sep 2021 Jakob Sjudin, Martin Marcusson, Lennart Svensson, Lars Hammarstrand

PHD filtering is a common and effective multiple object tracking (MOT) algorithm used in scenarios where the number of objects and their states are unknown.

Multiple Object Tracking

An Uncertainty-Aware Performance Measure for Multi-Object Tracking

no code implementations10 Aug 2021 Juliano Pinto, Yuxuan Xia, Lennart Svensson, Henk Wymeersch

Evaluating the performance of multi-object tracking (MOT) methods is not straightforward, and existing performance measures fail to consider all the available uncertainty information in the MOT context.

Multi-Object Tracking

Next Generation Multitarget Trackers: Random Finite Set Methods vs Transformer-based Deep Learning

1 code implementation1 Apr 2021 Juliano Pinto, Georg Hess, William Ljungbergh, Yuxuan Xia, Lennart Svensson, Henk Wymeersch

We show that the proposed model outperforms state-of-the-art Bayesian filters in complex scenarios, while matching their performance in simpler cases, which validates the applicability of deep-learning also in the model-based regime.

Autonomous Driving

A Poisson multi-Bernoulli mixture filter for coexisting point and extended targets

1 code implementation9 Nov 2020 Ángel F. García-Fernández, Jason L. Williams, Lennart Svensson, Yuxuan Xia

This paper proposes a Poisson multi-Bernoulli mixture (PMBM) filter for coexisting point and extended targets, i. e., for scenarios where there may be simultaneous point and extended targets.

Backward Simulation for Sets of Trajectories

no code implementations5 Aug 2020 Yuxuan Xia, Lennart Svensson, Ángel F. García-Fernández, Karl Granström, Jason L. Williams

This paper presents a solution for recovering full trajectory information, via the calculation of the posterior of the set of trajectories, from a sequence of multitarget (unlabelled) filtering densities and the multitarget dynamic model.

DACS: Domain Adaptation via Cross-domain Mixed Sampling

1 code implementation17 Jul 2020 Wilhelm Tranheden, Viktor Olsson, Juliano Pinto, Lennart Svensson

In this paper we address the problem of unsupervised domain adaptation (UDA), which attempts to train on labelled data from one domain (source domain), and simultaneously learn from unlabelled data in the domain of interest (target domain).

Semantic Segmentation Synthetic-to-Real Translation +1

Exploiting Diffuse Multipath in 5G SLAM

no code implementations28 Jun 2020 Yu Ge, Hyowon Kim, Fuxi Wen, Lennart Svensson, Sunwoo Kim, Henk Wymeersch

5G millimeter wave (mmWave) signals can be used to jointly localize the receiver and map the propagation environment in vehicular networks, which is a typical simultaneous localization and mapping (SLAM) problem.

Simultaneous Localization and Mapping

Trajectory Poisson multi-Bernoulli filters

no code implementations28 Mar 2020 Ángel F. García-Fernández, Lennart Svensson, Jason L. Williams, Yuxuan Xia, Karl Granström

The filters are based on propagating a Poisson multi-Bernoulli (PMB) density on the corresponding set of trajectories through the filtering recursion.

A general framework for ensemble distribution distillation

1 code implementation26 Feb 2020 Jakob Lindqvist, Amanda Olmin, Fredrik Lindsten, Lennart Svensson

Ensembles of neural networks have been shown to give better performance than single networks, both in terms of predictions and uncertainty estimation.

Poisson Multi-Bernoulli Mixtures for Sets of Trajectories

1 code implementation17 Dec 2019 Karl Granström, Lennart Svensson, Yuxuan Xia, Jason Williams, Ángel F. García-Fernández

First, we show that, for the standard point target model, the PMBM density is conjugate also for sets of trajectories.

Bayesian Linear Regression on Deep Representations

no code implementations14 Dec 2019 John Moberg, Lennart Svensson, Juliano Pinto, Henk Wymeersch

A simple approach to obtaining uncertainty-aware neural networks for regression is to do Bayesian linear regression (BLR) on the representation from the last hidden layer.

Model-based Reinforcement Learning

Multi-Scan Implementation of the Trajectory Poisson Multi-Bernoulli Mixture Filter

1 code implementation4 Dec 2019 Yuxuan Xia, Karl Granström, Lennart Svensson, Ángel F. García-Fernández, Jason L. Williams

A multi-scan trajectory PMBM filter and a multi-scan trajectory MBM filter, with the ability to correct past data association decisions to improve current decisions, are presented.

Signal Processing

Lidar-Camera Co-Training for Semi-Supervised Road Detection

1 code implementation28 Nov 2019 Luca Caltagirone, Lennart Svensson, Mattias Wahde, Martin Sanfridson

Recent advances in the field of machine learning and computer vision have enabled the development of fast and accurate road detectors.

Extended target Poisson multi-Bernoulli mixture trackers based on sets of trajectories

1 code implementation19 Nov 2019 Yuxuan Xia, Karl Granström, Lennart Svensson, Ángel F. García-Fernández, Jason L. Williams

The Poisson multi-Bernoulli mixture (PMBM) is a multi-target distribution for which the prediction and update are closed.

Signal Processing

Spooky effect in optimal OSPA estimation and how GOSPA solves it

no code implementations23 Aug 2019 Ángel F. García-Fernández, Lennart Svensson

In this paper, we show the spooky effect at a distance that arises in optimal estimation of multiple targets with the optimal sub-pattern assignment (OSPA) metric.

Gaussian implementation of the multi-Bernoulli mixture filter

1 code implementation23 Aug 2019 Ángel F. García-Fernández, Yuxuan Xia, Karl Granström, Lennart Svensson, Jason L. Williams

This paper presents the Gaussian implementation of the multi-Bernoulli mixture (MBM) filter.

Poisson multi-Bernoulli mixture trackers: continuity through random finite sets of trajectories

2 code implementations12 Dec 2018 Karl Granström, Lennart Svensson, Yuxuan Xia, Jason Williams, Angel F Garcia-Fernandez

By showing that the prediction and update in the PMBM filter can be viewed as an efficient method for calculating the time marginals of the RFS of trajectories, continuity in the same sense as MHT is established for the PMBM filter.

An Implementation of the Poisson Multi-Bernoulli Mixture Trajectory Filter via Dual Decomposition

1 code implementation29 Nov 2018 Yuxuan Xia, Karl Granström, Lennart Svensson, Ángel F. García-Fernández

This paper proposes an efficient implementation of the Poisson multi-Bernoulli mixture (PMBM) trajectory filter.

Trajectory PHD and CPHD filters

no code implementations21 Nov 2018 Ángel F. García-Fernández, Lennart Svensson

This paper presents the probability hypothesis density filter (PHD) and the cardinality PHD (CPHD) filter for sets of trajectories, which are referred to as the trajectory PHD (TPHD) and trajectory CPHD (TCPHD) filters.

Poisson Multi-Bernoulli Mapping Using Gibbs Sampling

no code implementations7 Nov 2018 Maryam Fatemi, Karl Granström, Lennart Svensson, Francisco J. R. Ruiz, Lars Hammarstrand

The proposed method can handle uncertainties in the data associations and the cardinality of the set of landmarks, and is parallelizable, making it suitable for large-scale problems.

Infinite Factorial Finite State Machine for Blind Multiuser Channel Estimation

no code implementations18 Oct 2018 Francisco J. R. Ruiz, Isabel Valera, Lennart Svensson, Fernando Perez-Cruz

New communication standards need to deal with machine-to-machine communications, in which users may start or stop transmitting at any time in an asynchronous manner.

LIDAR-Camera Fusion for Road Detection Using Fully Convolutional Neural Networks

1 code implementation21 Sep 2018 Luca Caltagirone, Mauro Bellone, Lennart Svensson, Mattias Wahde

Whereas in the former two fusion approaches, the integration of multimodal information is carried out at a predefined depth level, the cross fusion FCN is designed to directly learn from data where to integrate information; this is accomplished by using trainable cross connections between the LIDAR and the camera processing branches.

Poisson Multi-Bernoulli Approximations for Multiple Extended Object Filtering

no code implementations4 Jan 2018 Yuxuan Xia, Karl Granström, Lennart Svensson, Maryam Fatemi, Ángel F. García-Fernández, Jason L. Williams

The Poisson multi-Bernoulli mixture (PMBM) is a multi-object conjugate prior for the closed-form Bayes random finite sets filter.

Imitation Learning for Vision-based Lane Keeping Assistance

no code implementations12 Sep 2017 Christopher Innocenti, Henrik Lindén, Ghazaleh Panahandeh, Lennart Svensson, Nasser Mohammadiha

This paper aims to investigate direct imitation learning from human drivers for the task of lane keeping assistance in highway and country roads using grayscale images from a single front view camera.

Imitation Learning

LIDAR-based Driving Path Generation Using Fully Convolutional Neural Networks

no code implementations27 Mar 2017 Luca Caltagirone, Mauro Bellone, Lennart Svensson, Mattias Wahde

The fully convolutional neural network trained using all the available sensors together with driving directions achieved the best MaxF score of 88. 13% when considering a region of interest of 60x60 meters.

Scene Parsing

Poisson multi-Bernoulli mixture filter: direct derivation and implementation

no code implementations13 Mar 2017 Ángel F. García-Fernández, Jason L. Williams, Karl Granström, Lennart Svensson

We provide a derivation of the Poisson multi-Bernoulli mixture (PMBM) filter for multi-target tracking with the standard point target measurements without using probability generating functionals or functional derivatives.

Fast LIDAR-based Road Detection Using Fully Convolutional Neural Networks

no code implementations10 Mar 2017 Luca Caltagirone, Samuel Scheidegger, Lennart Svensson, Mattias Wahde

The FCN is specifically designed for the task of pixel-wise semantic segmentation by combining a large receptive field with high-resolution feature maps.

Semantic Segmentation

Multiple target tracking based on sets of trajectories

1 code implementation26 May 2016 Ángel F. García-Fernández, Lennart Svensson, Mark R. Morelande

We propose a solution of the multiple target tracking (MTT) problem based on sets of trajectories and the random finite set framework.

Trajectory probability hypothesis density filter

no code implementations24 May 2016 Ángel F. García-Fernández, Lennart Svensson

This paper presents the probability hypothesis density (PHD) filter for sets of trajectories: the trajectory probability density (TPHD) filter.

Poisson multi-Bernoulli conjugate prior for multiple extended object filtering

1 code implementation20 May 2016 Karl Granstrom, Maryam Fatemi, Lennart Svensson

Both the prediction and the update preserve the PMBM form of the density, and in this sense the PMBM density is a conjugate prior.

A metric on the space of finite sets of trajectories for evaluation of multi-target tracking algorithms

1 code implementation4 May 2016 Ángel F. García-Fernández, Abu Sajana Rahmathullah, Lennart Svensson

In this paper, we propose a metric on the space of finite sets of trajectories for assessing multi-target tracking algorithms in a mathematically sound way.

Generalized optimal sub-pattern assignment metric

2 code implementations21 Jan 2016 Abu Sajana Rahmathullah, Ángel F. García-Fernández, Lennart Svensson

This paper presents the generalized optimal sub-pattern assignment (GOSPA) metric on the space of finite sets of targets.

Infinite Factorial Dynamical Model

1 code implementation NeurIPS 2015 Isabel Valera, Francisco Ruiz, Lennart Svensson, Fernando Perez-Cruz

We propose the infinite factorial dynamic model (iFDM), a general Bayesian nonparametric model for source separation.

On the relation between Gaussian process quadratures and sigma-point methods

no code implementations22 Apr 2015 Simo Särkkä, Jouni Hartikainen, Lennart Svensson, Fredrik Sandblom

This article is concerned with Gaussian process quadratures, which are numerical integration methods based on Gaussian process regression methods, and sigma-point methods, which are used in advanced non-linear Kalman filtering and smoothing algorithms.

Numerical Integration

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