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Nerf(acto) for the 3D modeling of the Computer Science building of Westfälische Hochschule GE
(2023)
The video shows a very high resolution 3D point cloud !!! of the computer science building of the University of Applied Science Gelsenkirchen. For the recording a 3 minute flight with a M30T was performed. The 105 images taken by the wide-angle camera during this flight were localized within 3 minutes using colmap and processed using Neural Radiance Fields (NeRF). The nerfacto model of Nerfstudio was trained on an Nvidia RTX 4090 for 8 minutes. Thus, a top 3D model is available after about 15 minutes.
The video shown here shows a free camera path rendered at 60 hz (Full HD).
The video shows a very high resolution 3D point cloud !!! of the outdoor area of the German Rescue Robotics Center. For the recording, a 25-second POI flight was performed with a Mavic 3. From the 4K video footage captured during this flight, 77 images were cropped and localized within 4 minutes using colmap and processed using Neural Radiance Fields (NeRF). The nerfacto model of Nerfstudio was trained on an Nvidia RTX 4090 for 8 minutes. In summary, a top 3D model is available to task forces after about 13 minutes. The calculation is performed locally on site by the RobLW of the DRZ. The video shown here shows a free camera path rendered at 60 hz (Full HD).
From the 360° images of the former video (
• German rescue robotic center captured... ) we now generate the 3D point cloud. The UAV needs 3 minutes to capture the outdoor scenario and the hall from inside and outside. The 3D point cloud generation is 5x slower than the video. It uses a VSLAM algorithm to localize the k-frames (green) and with 3 k-frames it use a 360° PatchMatch algorithm implemented at a NVIDIA graphic card (CUDA) to calculated the dense point clouds.The hall ist about 70 x 20 meters.
An EJB container can host three types of beans: Session beans to model business processes, entity beans to represent business objects and message-driven beans to provide for asynchronous method calls. This paper addresses entity beans and their mapping to persistent storage, especially relational and object-relational databases. A tool named BeanMaker is presented which can do object mapping either automatically by metadata analysis of a database schema or manually based on intrinsic real world semantics supplied by the user. BeanMaker is a running prototype system with an intuitive GUI interface. This paper looks what's behind the scenes and focuses on design issues and concepts of code generation.
Dieser Artikel bietet einen Bericht über Entwicklungstendenzen und erste Erfahrungen virtueller Lernräume im Internet. Der Autor geht auf die Kommunikation im Internet, Lernräume im WWW, die Rollenverteilung im Lernraum ein, mit den Anforderungen aus Sicht der Lernenden, Lehrenden und der Verwaltung.