Marcus Baum

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• Professor
• Professor at University of Göttingen

This article considers indoor aerial vehicles that use a blimp to obtain a buoyancy that exceeds the vehicle’s weight. A so-called Buoyancy-Inverted Vehicle (BIV) moves directly under the ceiling such that physical contact with the ceiling can be exploited for locomotion. In this article, existing concepts for BIVs from literature are discussed. Fu...

Lidar-only odometry considers the pose estimation of a mobile robot based on the accumulation of motion increments extracted from consecutive lidar scans. Many existing approaches to the problem use a scan-to-map registration, which neglects the accumulation of errors within the maintained map due to drift. Other methods use a refinement step that...

Extended object tracking is concerned with estimation of object properties regarding both the kinematics and extent, i.e., shape. Particular challenges arise in case the orientation of the target is varying. Existing algorithms exhibit reduced filtering quality in difficult situations. We develop a particle filter-based elliptical extended object t...

A novel concept for indoor self-localization based on rotating artificial landmarks with known locations using short-range radar is proposed. First, a processing pipeline for extracting range and angle measurements to the landmarks from a raw radar image is introduced, which consists of a neural network for distance estimation and a basic angle-of-...

A novel concept for indoor self-localization based on relative position measurements to rotating artificial landmarks (with known positions) using short-range radar is proposed. This includes a complete processing pipeline for extracting distance and angle measurements from the raw radar data, which consists of a neural network for distance estimat...

The aeroelastic behaviour of aircraft is parameter variant. Changing flight conditions, such as e.g. flight velocity and altitude may change the vibration damping. When the vibration damping becomes zero or negative, self-excitation of the vibration occurs, called flutter. Modal parameter identification can be applied to extract eigenfrequencies an...

Ground radar stations observing specific regions of interest nowadays provide detections in the form of point-clouds. This article focuses on a framework that consists of an elliptical multitarget tracker, referred to as Principal-Axes based Kalman Filter (PAKF)-based Joint Probabilistic Data Association (JPDA) (PAKF-JPDA), to enable maritime traff...

Background ImputAccur is a software tool to measure genotype-imputation accuracy. Imputation of untyped markers is a standard approach in genome-wide association studies to close the gap between directly genotyped and other known DNA variants. However, high accuracy for imputed genotypes is fundamental. Several accuracy measures have been proposed,...

ImputAccur is a software tool for genotype-imputation accuracy-measures. Imputation of untyped markers is a standard approach in genome-wide association studies to close the gap between directly genotyped and other known DNA variants. However high accuracy for imputed genotypes is fundamental. Several accuracy measures have been proposed, but unfor...

div>This tutorial introduces state-of-the-art methods for tracking multiple spatially extended objects based on unlabeled noisy point clouds, e.g., from radar or lidar sensors. In the first part, the focus lies on tracking a single extended object, i.e., the objective is to simultaneously estimate the shape and position of a moving object based on...

This tutorial introduces state-of-the-art methods for tracking multiple spatially extended objects based on unlabeled noisy point clouds, e.g., from radar or lidar sensors. In the first part, the focus lies on tracking a single extended object, i.e., the objective is to simultaneously estimate the shape and position of a moving object based on spat...

Ellipses are favourable when it comes to tracking the shape of targets in a wide range of applications. With enhanced sensor technologies, the need for efficient measurement process�ing and accurate estimation keeps getting more pronounced. In this paper, we propose an approach called Principal Axes Kalman Filter (PAKF) for tracking an elliptical e...

As autonomous navigation is being implemented in several areas including the maritime domain, the need for robust tracking is becoming more important for traffic situation awareness, assessment and monitoring. We present an online repository comprising three designated marine radar datasets from real-world measurement campaigns to be employed for t...

Herding is a technique to sequentially generate deterministic samples from a probability distribution. In this work, we propose a continuous herded Gibbs sampler, that combines kernel herding on continuous densities with Gibbs sampling. Our algorithm allows for deterministically sampling from high-dimensional multivariate probability densities, wit...

High-resolution automotive radar sensors play an increasing role in detection, classification and tracking of moving objects in traffic scenes. Clustering is frequently used to group detection points in this context. However, this is a particularly challenging task due to variations in number and density of available data points across different sc...

This article considers the tracking of elliptical extended targets parameterized by center, orientation, and semiaxes. The focus of this article lies on the fusion of extended target estimates, e.g., from multiple sensors, by handling the ambiguities in this parameterization and the unclear meaning of the mean square error. For this purpose, we int...

This article considers the fusion of target estimates stemming from multiple sensors, where the spatial extent of the targets is incorporated. The target estimates are represented as ellipses parameterized with center orientation and semi-axis lengths and width. Here, the fusion faces challenges such as ambiguous parameterization and an unclear mea...

In multi-object tracking multiple objects generate multiple sensor measurements, which are used to estimate the objects’ state simultaneously. Since it is unknown from which object a measurement originates, a data association problem arises. Considering all possible associations is computationally infeasible for large numbers of objects and measure...

In multi-object tracking, multiple objects generate multiple sensor measurements, which are used to estimate the objects' state simultaneously. Since it is unknown from which object a measurement originates, a data association problem arises. Considering all possible associations is computationally infeasible for large numbers of objects and measur...

In the case of high-resolution or near field sensors, an object normally gives rise to multiple measurements per scan. One of the key tasks in tracking such objects is to differentiate the origins of the measurements. In this work, a new data association approach for extended object tracking, which is inspired by Joint Integrated Probabilistic Data...

This article considers the fusion of target estimates stemming from multiple sensors, where the spatial extent of the targets is incorporated. The target estimates are represented as ellipses parameterized with center orientation and semi-axis lengths and width. Here, the fusion faces challenges such as ambiguous parameterization and an unclear mea...

Global navigation satellite systems provide accurate positioning nearly worldwide. However, in the urban canyons of dense cities, buildings block and reflect the signals, causing multipath errors. To mitigate multipath errors, knowledge of the distribution of the reflection delays is important. Measurements of this distribution have been done in se...

In multi-object tracking multiple objects generate multiple sensor measurements, which are used to estimate the objects’ state simultaneously. Since it is unknown from which object a measurement originates, a data association problem arises. Considering all possible associations is computationally infeasible for large numbers of objects and measure...

In this article, we present further results on the use of Approximate Bayesian Computation (ABC) particle filters for multiple object tracking (MOT). Based on our previous work that uses the OSPA distance to select the k-nearest simulated measurements with respect to the actual measurements, we present and evaluate two further ABC variants. The fir...

This book constitutes the refereed proceedings of the Second International Workshop on Simulation Science, held in Claustal-Zellerfeld, in May 2019. The 12 full papers were carefully reviewed and selected from 47 submissions. Tha papers are organized according to the following topics: optimization and distributed simulations; simulation of materia...

This article considers the fusion of target estimates stemming from multiple sensors, where the spatial extent of the targets is incorporated. The target estimates are represented as ellipses parameterized with center orientation and semi-axis lengths and width. Here, the fusion faces challenges such as ambiguous parameterization and an unclear mea...

This article considers the fusion of target estimates stemming from multiple sensors, where the spatial extent of the targets is incorporated. The target estimates are represented as ellipses parameterized with center orientation and semi-axis lengths and width. Here, the fusion faces challenges such as ambiguous parameterization and an unclear mea...

Background: The loss of a hand is a traumatic experience that substantially compromises an individual's capability to interact with his environment. The myoelectric prostheses are state-of-the-art (SoA) functional replacements for the lost limbs. Their overall mechanical design and dexterity have improved over the last few decades, but the users h...

HDBSCAN is a density-based clustering algorithm that constructs a cluster hierarchy tree and then uses a specific stability measure to extract flat clusters from the tree. We propose an alternative method for selecting clusters from the HDBSCAN hierarchy. Our approach, HDBSCAN($\hat{\epsilon}$), is particularly useful for data sets with variable de...

The marine radar remains one of the most extensively used sensor for maritime surveillance. Owing to improved technologies, it can nowadays be exploited to gain information about the extents of targets, since multiple measurements can be obtained from a single target. This paper introduces an open multitarget marine radarbased dataset subjected to...

Extended object tracking considers the simultaneous estimation of the kinematic state and the shape parameters of a moving object based on a varying number of noisy detections. A main challenge in extended object tracking is the nonlinearity and high-dimensionality of the estimation problem. This work presents compact closed-form expressions for a...

Global Navigation Satellite Systems provide users with positioning in outdoor environments, however their performance in urban areas is decreased through errors caused by the reception of signals that are reflected on buildings (multipath and non-line-of-sight errors). To detect these errors, we simulated their influence on the correlator output on...

This paper presents a novel interpretation of data driven extended target tracking with applications to the automotive sector. Specifically, learning the spatial distribution of measurements from a vehicle in the form of a Variational Gaussian Mixture (VGM) model is examined. This distribution yields an interpretation applicable for the Expectation...

This paper considers the fusion of multiple estimates of a spatially extended object, where the object extent is modeled as an ellipse parameterized by the orientation and semi-axes lengths. For this purpose, we propose a novel systematic approach that employs a distance measure for ellipses, i.e., the Gaussian Wasserstein distance, as a cost funct...

Endeavours to have a reliable and robust maritime traffic situation assessment are today leading to exploit the improved sensor resolution technology of radars. In such concerned tracking scenarios, multiple noisy scattered measurements arise from targets of interest’s surfaces at each observation step. In this paper, we present a special version o...

This paper considers the fusion of multiple estimates of a spatially extended object, where the object extent is modeled as an ellipse that is parameterized by the orientation and semi-axes lengths. For this purpose, we propose a novel systematic approach that employs a distance measure for ellipses, i.e., the Gaussian Wasserstein distance, as a co...

The Probability Hypotheses Density (PHD) filter is a method for tracking multiple target objects based on unlabeled detections. However, as the PHD filter employs a first-order approximation of random finite sets, it does not provide track labels, i.e., targets of consecutive time steps are not associated with each other. In this work, an intuitive...

Many technical systems like manufacturing plants or software applications generate large event sequences. Knowing the temporal relationship between events is important for gaining insights into the status and behavior of the system. This paper proposes a novel approach for identifying the time lag between different event types. This identification...

This paper presents a framework for robust lane detection towards automated driving using multiple sensors. Since every single source (e.g., camera, digital map, etc.) can fail in certain situations, several independent sources need to be combined. Moreover, the reliability of each source strongly depends on environmental conditions, e.g., existenc...

In this chapter, we present an approach to Multi-Object Tracking (MOT) that is based on the Ensemble Kalman Filter (EnKF). The EnKF is a standard algorithm for data assimilation in high-dimensional state spaces that is mainly used in geosciences, but has so far only attracted little attention for object tracking problems. In our approach, the Optim...

Extended object tracking considers the simultaneous estimation of the kinematic state and the shape parameters of a moving object based on a varying number of noisy detections. A main challenge in extended object tracking is the nonlinearity and high-dimensionality of the estimation problem. This work presents compact closed-form expressions for a...

This Special Section was inspired by the 2016 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2016), see mfi2016.org, which took place 19–21 September 2016 in Baden-Baden, Germany. The conference was sponsored by the IEEE Robotics and Automation Society (RAS) and the IEEE Industrial Electronics Socie...

This article provides an elaborate overview of current research in extended object tracking. We provide a clear definition of an extended object and discuss its delimitation to other object types and sensor models. Next, different shape models and possibilities to model the number of measurements are extensively discussed. Subsequently, we give a t...

In active sonar and radar target tracking, measurements consist of position and often also include range rate. Tracking algorithms use these measurements over time to estimate target state comprising position, velocity and, where applicable, turn rate. In most cases there is an underlying assumption in the tracking algorithm that the target is a “p...

Event correlation is the task of detecting dependencies between events in event sequences, e.g., for predictive maintenance based on log-files. In this work, a new data-driven, generic framework for event correlation is presented. First, we use a fast preliminary test statistic to determine candidate event type pairs. Next, the precise distribution...

Video-on-demand (VoD) streaming services are becoming increasingly popular due to their flexibility in allowing users to access their favorite video content anytime and anywhere from a wide range of access devices, such as smart phones, computers and TV. The content providers rely on highly satisfied subscribers for revenue generation and there hav...

This paper presents a novel approach to track a nonconvex shape approximation of an extended target based on noisy point measurements. For this purpose, a novel type of random hypersurface model (RHM) called Level-set RHM is introduced that models the interior of a shape with level-sets of an implicit function. Based on the Level-set RHM, a nonline...

The objective of extended object tracking is to simultaneously track a target object and estimate its shape. As a consequence, it becomes necessary to incorporate both location and shape errors in the performance assessment of extended object tracking methods. In this work, we highlight the difficulties of selecting a proper metric for this purpose...

This work considers the problem of tracking a mobile object with an unknown shape based on noisy point cloud measurements from the object contour. For this purpose, an Expectation Maximization (EM) method is developed that is capable of simultaneously estimating the location and shape parameters of an object based on a temporal sequence (i.e., batc...

In this paper, we propose a novel method for estimating an elliptic shape approximation of a moving extended object that gives rise to multiple scattered measurements per frame. For this purpose, we parameterize the elliptic shape with its orientation and the lengths of the semi-axes. We relate an individual measurement with the ellipse parameters...

In this work, we apply the probabilistic multi-hypothesis tracker (PMHT) for the problem of underwater bearing-only multisensor multitarget tracking in clutter. The PMHT is a batch tracking algorithm that can efficiently process a large number of measurements from multiple sensors. We investigate both the extended Kalman filter (EKF) and unscented...

We consider the task of recursively estimating the pose and shape parameters of 3D objects based on noisy point cloud measurements from their surface. We focus on objects whose surface can be constructed by transforming a plane curve, such as a cylinder that is constructed by extruding a circle. However, designing estimators for such objects is cha...