@inproceedings{SeidlBennemann2016, author = {Seidl, Tobias and Bennemann, Michael}, title = {Image Stitching of Microscopic Images}, series = {Konferenz: "Society for Experimental Biology (SEB)", 3.-7. Juli 2016 in Brighton (England)}, booktitle = {Konferenz: "Society for Experimental Biology (SEB)", 3.-7. Juli 2016 in Brighton (England)}, url = {http://nbn-resolving.de/urn:nbn:de:hbz:1010-opus4-5076}, pages = {1}, year = {2016}, abstract = {Method to stich many microscopic images to gain one image with a very high resolution.}, subject = {Bildverarbeitung}, language = {en} } @article{UngerRobensAnderleetal.2024, author = {Unger, Sebastian and Robens, Sibylle and Anderle, Laura and Ostermann, Thomas}, title = {Digital Drawing Tools for Assessing Mental Health Conditions - A Scoping Review}, series = {German Medical Data Sciences 2024 - Health - Thinking, Researching and Acting Together ; Proceedings of the 69th Annual Meeting of the German Association of Medical Informatics, Biometry, and Epidemiology e.V. (gmds) 2024 in Dresden, Germany Studies in Health Technology and Informatics, Bd. 317}, journal = {German Medical Data Sciences 2024 - Health - Thinking, Researching and Acting Together ; Proceedings of the 69th Annual Meeting of the German Association of Medical Informatics, Biometry, and Epidemiology e.V. (gmds) 2024 in Dresden, Germany Studies in Health Technology and Informatics, Bd. 317}, doi = {10.3233/SHTI240864}, pages = {251 -- 259}, year = {2024}, abstract = {Introduction: Drawing tasks are an elementary component of psychological assessment in the evaluation of mental health. With the rise of digitalization not only in psychology but healthcare in general, digital drawing tools (dDTs) have also been developed for this purpose. This scoping review aims at summarizing the state of the art of dDTs available to assess mental health conditions in people above preschool age. Methods: PubMed, PsycInfo, PsycArticles, CINAHL, and Psychology and Behavioral Sciences Collection were searched for dDTs from 2000 onwards. The focus was on dDTs, which not only evaluate the final drawing, but also process data. Results: After applying the search and selection strategy, a total of 37 articles, comprising unique dDTs, remained for data extraction. Around 75 \% of these articles were published after 2014 and most of them target adults (86.5 \%). In addition, dDTs were mainly used in two areas: tremor detection and assessment of cognitive states, utilizing, for example, the Spiral Drawing Test and the Clock Drawing Test. Conclusion: Early detection of mental diseases is an increasingly important field in healthcare. Through the integration of digital and art based solutions, this area could expand into an interdisciplinary science. This review shows that the first steps in this direction have already been taken and that the possibilities for further research, e.g., on the optimized application of dDTs, are still open.}, language = {en} } @inproceedings{SurmannDigakisKremeretal.2023, author = {Surmann, Hartmut and Digakis, Niklas and Kremer, Jan-Niklas and Meine, Julien and Schulte, Max and Voigt, Niklas}, title = {Redefining Recon: Bridging Gaps with UAVs, 360° Cameras, and Neural Radiance Fields}, url = {http://nbn-resolving.de/urn:nbn:de:hbz:1010-opus4-44603}, pages = {1 -- 6}, year = {2023}, abstract = {In the realm of digital situational awareness during disaster situations, accurate digital representations, like 3D models, play an indispensable role. To ensure the safety of rescue teams, robotic platforms are often deployed to generate these models. In this paper, we introduce an innovative approach that synergizes the capabilities of compact Unmaned Arial Vehicles (UAVs), smaller than 30 cm, equipped with 360° cameras and the advances of Neural Radiance Fields (NeRFs). A NeRF, a specialized neural network, can deduce a 3D representation of any scene using 2D images and then synthesize it from various angles upon request. This method is especially tailored for urban environments which have experienced significant destruction, where the structural integrity of buildings is compromised to the point of barring entry—commonly observed post-earthquakes and after severe fires. We have tested our approach through recent post-fire scenario, underlining the efficacy of NeRFs even in challenging outdoor environments characterized by water, snow, varying light conditions, and reflective surfaces.}, language = {en} } @misc{MeineVoigtKremeretal.2023, author = {Meine, Julien and Voigt, Niklas and Kremer, Jan-Niklas and Digakis, Niklas and Schulte, Max and Surmann, Hartmut}, title = {3D point cloud model from the DRZ trainings site}, url = {http://nbn-resolving.de/urn:nbn:de:hbz:1010-opus4-43134}, year = {2023}, abstract = {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.}, language = {de} } @misc{MeineVoigtKremeretal.2023, author = {Meine, Julien and Voigt, Niklas and Kremer, Jan-Niklas and Digakis, Niklas and Schulte, Max and Surmann, Hartmut}, title = {Drone Flight Documentation with ARGUS at rescue operations}, url = {http://nbn-resolving.de/urn:nbn:de:hbz:1010-opus4-43141}, year = {2023}, abstract = {ARGUS is a tool for the systematic acquisition, documentation and evaluation of drone flights in rescue operations. In addition to the very fast generation of RGB and IR orthophotos, a trained AI can automatically detect fire, people and cars in the images captured by the drones.}, language = {de} } @misc{MeineVoigtKremeretal.2023, author = {Meine, Julien and Voigt, Niklas and Kremer, Jan-Niklas and Digakis, Niklas and Schulte, Max and Surmann, Hartmut}, title = {NeRF: 3D Reconstruction of Chemical Company After Tank Explosion in Kempen (August 17, 2023)}, url = {http://nbn-resolving.de/urn:nbn:de:hbz:1010-opus4-43236}, year = {2023}, abstract = {The video showcases a 3D model of a chemical company following a tank explosion that occurred on August 17, 2023, in Kempen computed with the AI algorithm Neural Radiance Field (NeRF). Captured by a compact mini drone measuring 18cm x 18cm and equipped with a 360° camera, these images offer an intricate perspective of the aftermath. After a comprehensive aerial survey and inspection of the 360° images taken within the facility, authorities confirmed that it was safe for the evacuated residents to return to their homes. See also: https://www1.wdr.de/fernsehen/aktuelle-stunde/alle-videos/video-grosser-chemieunfall-in-kempen-100.html}, language = {de} } @misc{MeineVoigtKremeretal.2023, author = {Meine, Julien and Voigt, Niklas and Kremer, Jan-Niklas and Digakis, Niklas and Schulte, Max and Surmann, Hartmut}, title = {Nerf(acto) for 3D modeling of the DRZ outside testing area}, url = {http://nbn-resolving.de/urn:nbn:de:hbz:1010-opus4-43156}, year = {2023}, abstract = {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).}, language = {en} } @misc{MeineVoigtKremeretal.2023, author = {Meine, Julien and Voigt, Niklas and Kremer, Jan-Niklas and Digakis, Niklas and Schulte, Max and Surmann, Hartmut}, title = {Nerf(acto) for the 3D modeling of the Computer Science building of Westf{\"a}lische Hochschule GE}, url = {http://nbn-resolving.de/urn:nbn:de:hbz:1010-opus4-43165}, year = {2023}, abstract = {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).}, language = {de} } @misc{MeineVoigtKremeretal.2023, author = {Meine, Julien and Voigt, Niklas and Kremer, Jan-Niklas and Digakis, Niklas and Schulte, Max and Surmann, Hartmut and Goos, Richard and Grafe, Robert}, title = {Challenging Dataset: 3D point cloud generated with the nerfacto neural network model for 360° videos}, url = {http://nbn-resolving.de/urn:nbn:de:hbz:1010-opus4-43199}, year = {2023}, abstract = {Challenging Dataset: 3D point cloud generated with the nerfacto neural network model for 360° videos}, language = {de} } @misc{MeineVoigtKremeretal.2023, author = {Meine, Julien and Voigt, Niklas and Kremer, Jan-Niklas and Digakis, Niklas and Schulte, Max and Surmann, Hartmut and Goos, Richard and Grafe, Robert}, title = {Challenging Dataset: 3D Pointcloud generated with the PatchMatch algorithm for 360° videos}, url = {http://nbn-resolving.de/urn:nbn:de:hbz:1010-opus4-43188}, year = {2023}, abstract = {Challenging Dataset: 3D Pointcloud generated with the PatchMatch algorithm for 360° videos}, language = {de} } @misc{MeineVoigtKremeretal.2023, author = {Meine, Julien and Voigt, Niklas and Kremer, Jan-Niklas and Digakis, Niklas and Schulte, Max and Surmann, Hartmut}, title = {3D model generated with the nerfacto AI algorithm after a fire based on 360° camera images}, url = {http://nbn-resolving.de/urn:nbn:de:hbz:1010-opus4-43212}, year = {2023}, abstract = {Essen 2 2022, indoor, DJI FPV with insta360}, language = {de} }