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Fakultät für Luftfahrt, Raumfahrt und Geodäsie
Technische Universität München

List of bib items [BibTeX] : 19

 

  • Albrecht CR, Kraus S, Stilla U (2020) Detection of lane markings in road scene images taken from a top-view camera system. (in press)
  • Borgmann B, Hebel M, Arens M, Stilla U (2020) Pedestrian detection and tracking in sparse MLS point clouds using a neural network and voting-based approach. (in press)
  • Braun A, Tuttas S, Borrmann A, Stila U (2020) Improving progress monitoring by fusing point clouds, semantic data and computer vision. Automation in Construction, 116: 103210
    [doi: 10.1016/j.autcon.2020.103210]
  • Dinkel R, Hoegner L, Emmert A, Raffl L, Stilla U (2020) Änderungsdetektion in photogrammetrischen Punktwolken für das Monitoring hochalpiner, gravitativer Massenbewegungen – Beispiel Hochvogel. 40. Wissenschaftlich-Technische Jahrestagung der DGPF, 29: 381-390
    [Paper]
  • Dinkel A, Hoegner L, Emmert A, Raffl L, Stilla U (2020) Change detection in photogrammetric point clouds for monitoring of alpine, gravitational mass movement. (in press)
  • Dong Z, Liang F, Yang B, Xu Y, Zang Y, Li J, Wang Y, Dai W, Fan H, Hyyppä J, Stilla U (2020) Registration of large-scale terrestrial laser scanner point clouds: A review and benchmark. ISPRS Journal of Photogrammetry and Remote Sensing, 163(2020): 327-342
    [doi: 10.1016/j.isprsjprs.2020.03.013]
  • Gehrung J, Hebel M, Arens M, Stilla U (2020) Change detection and deformation analysis based on mobile laser scanning data of urban areas. (in press)
  • Huang R, Xu Y, Hoegner L, Stilla U (2020) Efficient estimation of 3D shifts between point clouds using low-frequency components of phase correlation. (in press)
  • Huang R, Xu Y, Hong D, Yao W, Ghamisi P, Stilla U (2020) Deep point embedding for urban classification using ALS point clouds: A new perspective from local to global. ISPRS Journal of Photogrammetry and Remote Sensing, 163(2020): 62-81
    [doi: 10.1016/j.isprsjprs.2020.02.020]
  • Huang R, Xu Y Hoegner L, Stilla U (2020) Temporal comparison of construction sites using photogrammetric point cloud sequences and robust phase correlation. Automation in Construction, 117: 103247
    [doi: 10.1016/j.autcon.2020.103247]
  • Xia Y, Liu W, Luo Z, Xu Y, Stilla U (2020) Completion of sparse and partial point clouds of vehicles using a novel end-to-end network. (in press)
  • Xu Y, Ye Z, Huang R, Hoegner L, Stilla U (2020) Robust segmentation and localization of structural planes from photogrammetric point clouds in construction sites. Automation in Construction, 117: 103206
    [doi: 10.1016/j.autcon.2020.103206]
  • Xu Y, Ye Z, Yao W, Huang R, Tong X, Hoegner L, Stilla U (2020) Classification of LiDAR point clouds using supervoxel-based detrended feature and perception-weighted graphical model. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 13: 72-88
    [doi:10.1109/JSTARS.2019.2951293]
  • Ye Z, Xu Y, Chen H, Zhu J, Tong X, Stilla U (2020) Area-based dense image matching with subpixel accuracy for remote sensing applications: Practical analysis and comparative study. Remote Sensing, 12(4): 696
    [doi:10.3390/rs12040696]
  • Ye Z, Xu Y, Wei C, Tong X, Stilla U (2020) Influence of image interpolation on imagery-based detection and compensation of satellite jitter. (in press)
  • Ye Z, Xu Y, Huang R, Tong X, Li X, Liu X, Luan K, Hoegner L, Stilla U (2020) LASDU: A large-scale aerial LiDAR dataset for semantic labeling in dense urban areas. ISPRS International Journal of Geo-Information, 9(7): 450
    [doi: 10.3390/ijgi9070450] [PDF]
  • Ye Z, Xu Y, Zheng S, Tong X, XuX, Liu S, Xie H, Liu S, Wei C, Stilla U (2020) Resolving time-varying attitude jitter of anoptical remote sensing satellite based on atime-frequency analysis. Optics Express 28(11): 15805
    [doi:10.1364/OE.39219]
  • Zhu J, Gehrung J, Huang R, Borgmann B, Sun Z, Hoegner L, Hebel M, Xu Y, Stilla U (2020) TUM-MLS-2016: An annotated mobile LiDAR dataset of the TUM city campus for semantic point-cloud interpretation in urban areas. Remote Sensing, 12(11): 1875
    [doi: 10.3390/rs12111875] [PDF]
  • Zhu J, Ye Z, Xu Y, Hoegner L, Stilla U (2020) MINDflow based dense matching of TIR and RGB images. (in press)

 

Professur für Photogrammetrie und Fernerkundung

Prof. Dr.-Ing. Uwe Stilla

Technische Universität München
Arcisstr. 21
80333 München

Tel.: +49.89.289.22671
Fax: +49.89.289.23202

pf.bgu@tum.de

Leonhard Obermeyer Center
Fakultät für Luftfahrt, Raumfahrt und Geodäsie

© 2020 PF TUM | Technische Universität München