Claus Brenner
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View article: Integrated Multi-Stereo Camera System for Robust Indoor Localization with Temporal Fusion
Integrated Multi-Stereo Camera System for Robust Indoor Localization with Temporal Fusion Open
This paper presents a novel multi-stereo camera system for robust indoor localization, leveraging point cloud data and temporal fusion techniques. The system integrates three synchronized stereo cameras to capture point clouds from multipl…
View article: Calibrated and Efficient Sampling-Free Confidence Estimation for LiDAR Scene Semantic Segmentation
Calibrated and Efficient Sampling-Free Confidence Estimation for LiDAR Scene Semantic Segmentation Open
Reliable deep learning models require not only accurate predictions but also well-calibrated confidence estimates to ensure dependable uncertainty estimation. This is crucial in safety-critical applications like autonomous driving, which d…
View article: Gap Completion in Point Cloud Scene occluded by Vehicles using SGC-Net
Gap Completion in Point Cloud Scene occluded by Vehicles using SGC-Net Open
Recent advances in mobile mapping systems have greatly enhanced the efficiency and convenience of acquiring urban 3D data. These systems utilize LiDAR sensors mounted on vehicles to capture vast cityscapes. However, a significant challenge…
View article: Exploring User Semantic Annotation from Trajectories in the Scenario of Shared Locations
Exploring User Semantic Annotation from Trajectories in the Scenario of Shared Locations Open
Over the past decade(s), collecting spatiotemporal data has become easier due to technological advancements and more user-friendly collection processes. Additionally, government agencies, companies, and open data projects have made general…
View article: Intraoperative Precision Sampling of Tumor Microenvironments based on 7T MRSI: A pipeline development
Intraoperative Precision Sampling of Tumor Microenvironments based on 7T MRSI: A pipeline development Open
View article: Semantic segmentation of mobile mapping point clouds via multi-view label transfer
Semantic segmentation of mobile mapping point clouds via multi-view label transfer Open
View article: VOXEL-BASED POINT CLOUD LOCALIZATION FOR SMART SPACES MANAGEMENT
VOXEL-BASED POINT CLOUD LOCALIZATION FOR SMART SPACES MANAGEMENT Open
This paper proposes a voxel-based approach for creating a digital twin of an urban environment that is capable of efficiently managing smart spaces. The paper explains the registration and localization procedure of the point cloud dataset,…
View article: Maximum Consensus Localization using an Objective Function based on Helmert's Point Error
Maximum Consensus Localization using an Objective Function based on Helmert's Point Error Open
Ego-localization is a crucial task for autonomous vehicles. On the one hand, it needs to be very accurate, and on the other hand, very robust to provide reliable pose (position and orientation) information, even in challenging environments…
View article: Gaussian Process Mapping of Uncertain Building Models with GMM as Prior
Gaussian Process Mapping of Uncertain Building Models with GMM as Prior Open
Mapping with uncertainty representation is required in many research domains, especially for localization. Although there are many investigations regarding the uncertainty of the pose estimation of an ego-robot with map information, the qu…
View article: SELF-SUPERVISED ADVERSARIAL SHAPE COMPLETION
SELF-SUPERVISED ADVERSARIAL SHAPE COMPLETION Open
The goal of this paper is 3D shape completion: given an incomplete instance of a known category, hallucinate a complete version of it that is geometrically plausible. We develop an adversarial framework that makes it possible to learn shap…
View article: Determination of building flood risk maps from LiDAR mobile mapping data
Determination of building flood risk maps from LiDAR mobile mapping data Open
View article: MAXIMUM CONSENSUS LOCALIZATION USING LIDAR SENSORS
MAXIMUM CONSENSUS LOCALIZATION USING LIDAR SENSORS Open
Real world localization tasks based on LiDAR usually face a high proportion of outliers arising from erroneous measurements and changing environments. However, applications such as autonomous driving require a high integrity in all of thei…
View article: Building Change Detection of Airborne Laser Scanning and Dense Image Matching Point Clouds using Height and Class Information
Building Change Detection of Airborne Laser Scanning and Dense Image Matching Point Clouds using Height and Class Information Open
Detecting changes is an important task to update databases and find irregularities in spatial data. Every couple of years, national mapping agencies (NMAs) acquire nation-wide point cloud data from Airborne Laser Scanning (ALS) as well as …
View article: Classification and Change Detection in Mobile Mapping LiDAR Point Clouds
Classification and Change Detection in Mobile Mapping LiDAR Point Clouds Open
View article: Flood severity mapping from Volunteered Geographic Information by interpreting water level from images containing people: A case study of Hurricane Harvey
Flood severity mapping from Volunteered Geographic Information by interpreting water level from images containing people: A case study of Hurricane Harvey Open
View article: GEOMETRY-BASED POINT CLOUD CLASSIFICATION USING HEIGHT DISTRIBUTIONS
GEOMETRY-BASED POINT CLOUD CLASSIFICATION USING HEIGHT DISTRIBUTIONS Open
Semantic segmentation is one of the main steps in the processing chain for Airborne Laser Scanning (ALS) point clouds, but it is also one of the most labour intensive steps, as it requires many labelled examples to train a classifier. Nati…
View article: Conditional Adversarial Networks for Multimodal Photo-Realistic Point Cloud Rendering
Conditional Adversarial Networks for Multimodal Photo-Realistic Point Cloud Rendering Open
We investigate whether conditional generative adversarial networks (C-GANs) are suitable for point cloud rendering. For this purpose, we created a dataset containing approximately 150,000 renderings of point cloud–image pairs. The dataset …
View article: Learning a Precipitation Indicator from Traffic Speed Variation Patterns
Learning a Precipitation Indicator from Traffic Speed Variation Patterns Open
View article: Integrity and Collaboration in Dynamic Sensor Networks
Integrity and Collaboration in Dynamic Sensor Networks Open
Global Navigation Satellite Systems (GNSS) deliver absolute position and velocity, as well as time information (P, V, T). However, in urban areas, the GNSS navigation performance is restricted due to signal obstructions and multipath. This…
View article: Generation and communication of dynamic maps using light projection
Generation and communication of dynamic maps using light projection Open
Many accidents are caused by miscommunication between traffic participants. Much research is being conducted in the area of car to car and car to infrastructure communication in order to eliminate this cause of accidents. How-ever, less at…
View article: ASSESSING TEMPORAL BEHAVIOR IN LIDAR POINT CLOUDS OF URBAN ENVIRONMENTS
ASSESSING TEMPORAL BEHAVIOR IN LIDAR POINT CLOUDS OF URBAN ENVIRONMENTS Open
Self-driving cars and robots that run autonomously over long periods of time need high-precision and up-to-date models of the changing environment. The main challenge for creating long term maps of dynamic environments is to identify chang…
View article: EXTRACTING LANE GEOMETRY AND TOPOLOGY INFORMATION FROM VEHICLE FLEET TRAJECTORIES IN COMPLEX URBAN SCENARIOS USING A REVERSIBLE JUMP MCMC METHOD
EXTRACTING LANE GEOMETRY AND TOPOLOGY INFORMATION FROM VEHICLE FLEET TRAJECTORIES IN COMPLEX URBAN SCENARIOS USING A REVERSIBLE JUMP MCMC METHOD Open
Highly automated driving (HAD) requires maps not only of high spatial precision but also of yet unprecedented actuality. Traditionally small highly specialized fleets of measurement vehicles are used to generate such maps. Nevertheless, fo…
View article: Forest point processes for the automatic extraction of networks in raster data
Forest point processes for the automatic extraction of networks in raster data Open
View article: Generating a Hazard Map of Dynamic Objects Using Lidar Mobile Mapping
Generating a Hazard Map of Dynamic Objects Using Lidar Mobile Mapping Open
One of the hardest problems for future self-driving cars is to predict hazardous situations involving pedestrians and cyclists. Human drivers solve this problem typically by having a deeper understanding of the scene. The technical equival…
View article: Scalable estimation of precision maps in a MapReduce framework
Scalable estimation of precision maps in a MapReduce framework Open
This paper presents a large-scale strip adjustment method for LiDAR mobile mapping data, yielding highly precise maps. It uses several concepts to achieve scalability. First, an efficient graph-based pre-segmentation is used, which directl…
View article: VEHICLE LOCALIZATION BY LIDAR POINT CORRELATION IMPROVED BY CHANGE DETECTION
VEHICLE LOCALIZATION BY LIDAR POINT CORRELATION IMPROVED BY CHANGE DETECTION Open
LiDAR sensors are proven sensors for accurate vehicle localization. Instead of detecting and matching features in the LiDAR data, we want to use the entire information provided by the scanners. As dynamic objects, like cars, pedestrians or…
View article: VEHICLE LOCALIZATION BY LIDAR POINT CORRELATION IMPROVED BY CHANGE DETECTION
VEHICLE LOCALIZATION BY LIDAR POINT CORRELATION IMPROVED BY CHANGE DETECTION Open
LiDAR sensors are proven sensors for accurate vehicle localization. Instead of detecting and matching features in the LiDAR data, we want to use the entire information provided by the scanners. As dynamic objects, like cars, pedestrians or…
View article: GPS-Aided Video Tracking
GPS-Aided Video Tracking Open
Tracking moving objects is both challenging and important for a large variety of applications. Different technologies based on the global positioning system (GPS) and video or radio data are used to obtain the trajectories of the observed …