Mitarbeiter

Dr.-Ing. David Nakath

FB 2: Marine Biogeochemie
FE Marine Geosysteme

Postdoc Oceanic Machine Vision

Büro: Gebäude 8b / Raum 202

Telefon: +49 431 600-2272

E-Mail: dnakath(at)geomar.de

Forschungsinteressen

  • Unterwasser Computer Vision
    • Physikalisch korrekte Simulation von Unterwasserszenen
    • Kalibrierung und Parameterschätzung in Unterwasserszenen
    • Radiometrisch wie auch Geometrisch

 

Parameteridentifikation und Farbrestauration

Verschiedene Beleuchtungsszenarien der Wassersäule

Komplexe Bildgebungsmodelle

  • Autonomous Systems
    • Probabilistic Robotics
    • Aktives Messen /  Reduktion von Unsicherheit

 

Publikationen

generated by bibbase.org
  2022 (6)
Refractive geometry for underwater domes. She, M.; Nakath, D.; Song, Y.; and Köser, K. ISPRS Journal of Photogrammetry and Remote Sensing, 183: 525–540. 2022.
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An Optical Digital Twin for Underwater Photogrammetry. Nakath, D.; She, M.; Song, Y.; and Köser, K. PFG–Journal of Photogrammetry, Remote Sensing and Geoinformation Science, 90(1): 69–81. 2022.
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A Vision on a UNESCO Global Geopark at the Southeastern Dead Sea in Jordan—How Natural Hazards May Offer Geotourism Opportunities. Al-Halbouni, D.; AlRabayah, O.; Nakath, D.; and Rüpke, L. Land, 11(4): 553. 2022.
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Optical Imaging and Image Restoration Techniques for Deep Ocean Mapping: A Comprehensive Survey. Song, Y.; Nakath, D.; She, M.; and Köser, K. PFG–Journal of Photogrammetry, Remote Sensing and Geoinformation Science,1–25. 2022.
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Towards Cross Domain Transfer Learning for Underwater Correspondence Search. Schöntag, P.; Nakath, D.; Röhrl, S.; and Köser, K. In International Conference on Image Analysis and Processing, pages 461–472, 2022. Springer, Cham
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Digital twinning in the ocean-chanllenges in multimodal sensing and multiscale fusion based on faithful visual models. Grossmann, V.; Nakath, D.; Urlaub, M.; Oppelt, N.; Koch, R.; and Köser, K. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 4: 345–352. 2022.
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  2021 (4)
Optimization of multi-led setups for underwater robotic vision systems. Song, Y.; Sticklus, J.; Nakath, D.; Wenzlaff, E.; Koch, R.; and Köser, K. In International Conference on Pattern Recognition, pages 390–397, 2021. Springer, Cham
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Deep Sea Robotic Imaging Simulator. Song, Y.; Nakath, D.; She, M.; Elibol, F.; and Köser, K. In Proceedings of the Computer Vision for Automated Analysis of Underwater Imagery Workshop (CVAUI)., pages 375–389, 2021. Springer
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In-situ joint light and medium estimation for underwater color restoration. Nakath, D.; She, M.; Song, Y.; and Köser, K. In Proceedings of the IEEE/CVF International Conference on Computer Vision, pages 3731–3740, 2021.
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MaCal-Macro Lens Calibration and the Focus Stack Camera Model. Weng, X.; She, M.; Nakath, D.; and Köser, K. In 2021 International Conference on 3D Vision (3DV), pages 136–144, 2021. IEEE
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  2020 (3)
Active asteroid-SLAM. Nakath, D.; Clemens, J.; and Rachuy, C. Journal of Intelligent & Robotic Systems, 99(2): 303–333. 2020.
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Light Pose Calibration for Camera-light Vision Systems. Song, Y.; Elibol, F.; She, M.; Nakath, D.; and Köser, K. arXiv preprint arXiv:2006.15389. 2020.
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Deep Sea Robotic Imaging Simulator for UUV Development. Song, Y.; Nakath, D.; She, M.; Elibol, F.; and Köser, K. CoRR. 2020.
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  2019 (1)
Active Perception for Autonomous Systems: In a Deep Space Navigation Scenario. Nakath, D. Ph.D. Thesis, Universität Bremen, 2019.
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  2018 (1)
Multi-sensor fusion and active perception for autonomous deep space navigation. Nakath, D.; Clemens, J.; and Schill, K. In 2018 21st International Conference on Information Fusion (FUSION), pages 2596–2605, 2018. IEEE
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  2017 (1)
Rigid body attitude control based on a manifold representation of direction cosine matrices. Nakath, D.; Clemens, J.; and Rachuy, C. In Journal of Physics: Conference Series, volume 783, pages 012040, 2017. IOP Publishing
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  2016 (1)
Optimal rotation sequences for active perception. Nakath, D.; Rachuy, C.; Clemens, J.; and Schill, K. In Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2016, volume 9872, pages 20–32, 2016. SPIE
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  2015 (3)
KaNaRiA: Identifying the challenges for cognitive autonomous navigation and guidance for missions to small planetary bodies. Probst, A.; Peytavi, G.; Nakath, D.; Schattel, A.; Rachuy, C.; Lange, P.; Clemens, J; Echim, M; Schwarting, V; Srini-vas, A; and others In International Astronautical Congress (IAC), 2015.
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Adaptive information selection in images: Efficient naive bayes nearest neighbor classification. Reineking, T.; Kluth, T.; and Nakath, D. In International Conference on Computer Analysis of Images and Patterns, pages 350–361, 2015. Springer, Cham
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Autonomous orbit navigation for a mission to the asteroid main belt. Peytavı́, G González; Clemens, J; Nakath, D; Probst, A; Schill, F.; and Eissfeller, B In In. Proc. of the 66th International Astronautical Congress, 2015.
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  2014 (4)
Virtual Reality for Simulating Autonomous Deep-Space Navigation and Mining. Büskens, C.; Clemens, J.; Eissfeller, B.; Förstner, R.; Gadzicki, K.; Peytavi, G. G.; Lange, P.; Nakath, D.; Probst, A.; Rachuy, C.; and others In ICAT-EGVE (Posters and Demos), 2014.
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Active sensorimotor object recognition in three-dimensional space. Nakath, D.; Kluth, T.; Reineking, T.; Zetzsche, C.; and Schill, K. In International Conference on Spatial Cognition, pages 312–324, 2014. Springer
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Affordance-based object recognition using interactions obtained from a utility maximization principle. Kluth, T.; Nakath, D.; Reineking, T.; Zetzsche, C.; and Schill, K. In European Conference on Computer Vision, pages 406–412, 2014. Springer, Cham
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Virtual Reality for Simulating Autonomous Deep-Space Navigation and Mining. Büskens, C.; Clemens, J.; Eissfeller, B.; Förstner, R.; Gadzicki, K.; Peytavi, G. G.; Lange, P.; Nakath, D.; Probst, A.; Rachuy, C.; and others In ICAT-EGVE (Posters and Demos), 2014.
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  2013 (1)
Sensorimotor integration using an information gain strategy in application to object recognition tasks. Kluth, T; Nakath, D; Reineking, T; Zetzsche, C; and Schill, K Perception ECVP abstract, 42: 223–223. 2013.
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  2012 (1)
A distributed online learning tracking algorithm. Schrader, S.; Dambek, M.; Block, A.; Brending, S.; Nakath, D.; Schmid, F.; and van de Ven, J. In 2012 12th International Conference on Control Automation Robotics & Vision (ICARCV), pages 1083–1088, 2012. IEEE
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