Prof. Dr.-Ing. Andreas Wichmann
Artikel und Bücher
Kada, Martin; Wichmann, Andreas; Manzke, Nina; Filippovska, Yevgeniya (2016):
A Data Model for the Interactive Construction and Correction of 3D Building Geometry Based on Planar Half-Spaces. Springer International Publishing
, doi: https://doi.org/10.1007/978-3-319-25691-7_26 , Weblink
Kada, Martin; Wichmann, Andreas; Filippovska, Yevgeniya; Hermes, Tobias (2016):
Animation Strategies for Smooth Transformations Between Discrete LODs of 3D Building Models. ISPRS Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
, doi: https://doi.org/10.5194/isprs-archives-XLI-B2-413-2016 , Weblink
Albers, Bastian; Kada, Martin; Wichmann, Andreas (2016):
Automatic Extraction and Regularization of Building Outlines from Airborne LiDAR Point Clouds. ISPRS Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
, doi: https://doi.org/10.5194/isprs-archives-XLI-B3-555-2016 , Weblink
Wichmann, Andreas; Kada, Martin (2016):
Joint Simultaneous Reconstruction of Regularized Building Superstructures from Low-Density LiDAR Data Using ICP. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
, doi: https://doi.org/10.5194/isprs-annals-III-3-371-2016 , Weblink
Jung, Jaewook; Sohn, Gunho; Bang, Kiin; Wichmann, Andreas; Armenakis, Costas; Kada, Martin (2016):
Matching Aerial Images to 3D Building Models Using Context-Based Geometric Hashing. Sensors
, doi: https://doi.org/10.3390/s16060932 , Weblink
Preise und Auszeichnungen
- ASPRS Esri Award for Best Scientific Paper in GIS (2020)
American Society for Photogrammetry and Remote Sensing (ASPRS) - ISPRS Best Paper Award (2018)
International Society for Photogrammetry and Remote Sensing (ISPRS) - AOLS Best Poster Award (2016)
Association of Ontario Land Surveyors (AOLS)
Lehre
- Geobasisdaten
- Kartographie
- Kartographische Informationsverarbeitung
- Projekt Visualisierung
- Seminar Kartographie
- Web Engineering
Abschlussarbeiten
Untersuchung zur Qualität von amtlichen LoD2-Gebäudemodellen anhand von 3D-Punktwolken (2020/2)