Tag: HELIOS

  • Major HELIOS++ Release: v2.0.0

    Major HELIOS++ Release: v2.0.0

    We are happy to release a new major version of HELIOS++: https://github.com/3dgeo-heidelberg/helios/releases What’s new in this release? Installation The new way to install HELIOS++ is via the conda or mamba package managers. We recommend mamba or micromamba. After creating a dedicated Python environment for your HELIOS++ project and activating it, run: mamba install helios or…

  • Kick-off: Extract4D Project

    Kick-off: Extract4D Project

    Last week, we, 3DGeo Heidelberg (Prof. Dr. Bernhard Höfle), had a kick-off meeting for our new joint research project Extract4D, led by Prof. Dr. Katharina Anders (TU Munich, Remote Sensing Applications). Here is a sneak peek at this exciting research project. Background The Earth’s surface is constantly being shaped by wind, water and gravity. Observing…

  • Deep learning with simulated laser scanning data for 3D point cloud classification

    Deep learning with simulated laser scanning data for 3D point cloud classification

    Esmorís, A.M., Weiser, H., Winiwarter, L., Cabaleiro, J.C. & Höfle, B. (2024): Deep learning with simulated laser scanning data for 3D point cloud classification. ISPRS Journal of Photogrammetry and Remote Sensing. Vol. 215, pp. 192-213. DOI: 10.1016/j.isprsjprs.2024.06.018 3D point clouds acquired by laser scanning are invaluable for the analysis of geographic phenomena. To extract information…

  • VirtuaLearn3D: New Preprint

    VirtuaLearn3D: New Preprint

    We have published a preprint of our recent work in the VirtuaLearn3D project! Deep learning with simulated laser scanning data for 3D point cloud classification Esmorís, A.M., Weiser, H., Winiwarter, L., Cabaleiro, J.C. & Höfle, B. (2024) Laser scanning is an active remote sensing technique to acquire state-of-the-art spatial measurements in the form of 3D…

  • New paper on the potential of simulated laser scanning and field data to train forest biomass models

    New paper on the potential of simulated laser scanning and field data to train forest biomass models

    In great collaboration with colleagues from Karlsruhe (DE), Vienna (AT), Brno (CZ), Leipzig (DE), Raszyn (PL), and Berlin (DE), we published a paper investigating approaches to improve LiDAR-based biomass models when only limited sample plots with field data are available. The main work was carried out by PhD student Jannika Schäfer (IFGG, Karlsruhe Institute of…

  • DFG Software Grant

    DFG Software Grant

    Successful proposal: Fostering a community-driven and sustainable HELIOS++ scientific software The 3DGeo Group and the Scientific Software Center (SSC) of Heidelberg University have been successful with their proposal in the DFG call “Research Software – Quality assured and re-usable”, together with two other project proposals at Heidelberg University (see press release). The main objective of…

  • 🦇 Halloween release of HELIOS++, v1.3.0

    🦇 Halloween release of HELIOS++, v1.3.0

    We proudly present our Halloween release of HELIOS++, Version 1.3.0: https://github.com/3dgeo-heidelberg/helios/releases What’s new in this release? HELIOS++ now supports LiDAR simulation of dynamic scenes. We can now simulate laser scanning of scenes that change during the simulation. This is done by introducing rigid motions, which are defined with XML syntax in the scene XML file.…

  • Impressions from Silvilaser 2023

    Impressions from Silvilaser 2023

    Last week, our PhD student, Hannah Weiser, joined Silvilaser 2023 at University College London (UCL). The conference covers cutting-edge science and technology from the laser scanning and forest communities, which is a perfect match for Hannah’s PhD topic and 3DGeo research in general. The week started off with interesting workshops on Tuesday using some of…

  • Final meeting of the E-TRAINEE project

    Last week, the 3DGeo research group hosted the final meeting of the E-TRAINEE project, finally and for the first time in presence. For almost three years now, we have been developing a research-oriented open-source e-learning course – soon to be published! The course on “Time Series Analysis in Remote Sensing for Understanding Human-Environment Interactions” teaches…

  • Introducing the VirtuaLearn3D Project

    With VirtuaLearn3D (Virtual Laser Scanning for Machine Learning Algorithms in Geographic 3D Point Cloud Analysis), a new project of the 3DGeo group has started. The focus of this project is to enable powerful machine learning algorithms for geographic point cloud analysis by advancing the concept of virtual laser scanning to overcome the lack of training…

  • Improved Performance of HELIOS++ using High Performance Computing Techniques

    The software HELIOS++ simulates the laser scanning of a given virtual scene that can be composed of different spatial primitives and 3D meshes with distinct granularity. The high computational cost of this type of simulation software demands efficient computational solutions. Classical solutions based on GPU are not well suited when irregular geometries compose the scene…

  • 3DGeo contributions to ISPRS Congress 2022 now online

    From 5 June – 11 June 2022 the ISPRS Congress took place in Nice, France. The 3DGeo research group had three paper contributions which can now be found online: (1) Virtual Laser Scanning of Dynamic Scenes Created From Real 4D Topographic Point Cloud Data. Find all details in the video (link) and paper and check…