Hai Huang

Forschte als Postdoktorand in einem DFG Projekt von Prof. Brenner an der automatischen Generierung von 3D-Stadtmodellen mittels statistischer Verfahren.

Hai habilitierte sich kürzlich an der Leibniz Universität Hannover in der Fakultät für Bauingenieurwesen und Geodäsie zum Thema: Bayesian Models for Pattern Recognition in Spatial Data

 

 

PUBLIKATIONEN

Begutachtete Zeitschriftenartikel und Buchkapitel

  • H. Huang, H. Jiang, C. Brenner and H. Mayer (2014): Object-level Segmentation of RGBD DataISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. 2 (3), pp. 73
  • H. Huang, C. Brenner and M. Sester (2013): A generative statistical approach to automatic 3D building roof reconstruction from laser scanning dataISPRS Journal of Photogrammetry and Remote Sensing, vol. 79 (0), pp. 29-43
    DOI: 10.1016/j.isprsjprs.2013.02.004
  • B. Kieler, W. Huang, J.-H. Haunert and J. Jiang (2009): Matching River Datasets of Different Scales>Advances in GIScience: Proceedings of 12th AGILE Conference on GIScience, Lecture Notes in Geoinformation and Cartography, pp. 135-154
  • H. Huang and H. Mayer (2009): Generative Statistical 3D Reconstruction of Unfoliaged Trees from Terrestrial ImagesAnnals of GIS, vol. 15 (2), pp. 97-105 | Datei |
  • H. Huang and H. Mayer (2007): Extraction of the 3D Branching Structure of Unfoliaged Deciduous Trees from Image SequencesPhotogrammetrie -- Fernerkundung -- Geoinformation, vol. (6/2007), pp. 429-436 | Datei |

Begutachtete Konferenzbeiträge

  • H. Huang, L. Zhang and M. Sester (2014): A Recursive Bayesian Filter for Anomalous Behavior Detection in Trajectory DataLecture Notes in Geoinformation and Cartography: Connecting a Digital Europe Through Location and Place, pp. 91-104
    DOI: 10.1007/978-3-319-03611-3_6
  • H. Huang and H. Jiang (2013): Object-level segmentation of RGBD dataIEEE International Conference on Image Processing (ICIP)
  • H. Huang and C. Brenner (2011): Rule-based roof plane detection and segmentation from laser point cloudsUrban Remote Sensing Event (JURSE), 2011 Joint, pp. 293-296 | Datei |
  • H. Huang, C. Brenner and M. Sester (2011): 3D Building Roof Reconstruction from Point Clouds via Generative Models19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (GIS), pp. 16-24 | Datei |
  • H. Huang (2008): Terrestrial Image Based 3D Extraction of Urban Unfoliaged Trees of Different Branching TypesThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. 37 (B3a), pp. 253-258 | Datei |
  • H. Huang and H. Mayer (2007): Extraction of 3D Unfoliaged Trees from Image Sequences via a Generative Statistical ApproachThe Annual Symposium of the German Association for Pattern Recognition (DAGM), vol. (4713/2007), pp. 385-394 | Datei |

Konferenzbeiträge

  • M. Sester, P.P. Altermatt, H. Holst, H. Huang, H. Schilke, V. Schöber, G. Seckmeyer and M. Winter (2015): Vertikale SolarfassadenJahrestagung der Deutschen Gesellschaft für Photogrammetrie und Fernerkundung
  • H. Huang, B. Kieler and M. Sester (2013): Urban building usage labeling by geometric and context analyses of the footprint data26th International Cartographic Conference (ICC) | Datei |
  • H. Huang, M. Sester (2011): A Hybrid Approach to Extraction and Refinement of Building Footprints from Airborne LiDAR DataISPRS Workshop on Geospatial Data Infrastructure: from data acquisition and updating to smarter services, pp. 153-158 | Datei |

Monographien

  • Huang, H. (2018): Bayesian Models for Pattern Recognition in Spatial DataDeutsche Geodätische Kommission bei der Bayerischen Akademie der Wissenschaften, Reihe C, Nr. 818 (identisch mit / identical with Wissenschaftliche Arbeiten der Fachrichtung Geodäsie und Geoinformatik der Universität Hannover ISSN 0174-1454, Nr. 341, Hannover 2018), München 2018, 100 S. Weitere Informationen
    ISBN: ISBN 978-3-7696-5229-1