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Department of Aerospace and Geodesy
TUM School of Engineering and Design

List of bib items [BibTeX] : 21

 

  • Albrecht CR, Kraus S, Stilla U (2020) Concept on landmark detection in road scene images taken from a top-view camera system. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLIII-B1-2020: 205–209
    [doi: 10.5194/isprs-archives-XLIII-B1-2020-205-2020] [Paper]
  • 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. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, V-2-2020: 187–194
    [doi: 10.5194/isprs-annals-V-2-2020-187-2020] [Paper]
  • Braun A, Tuttas S, Borrmann A, Stilla 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. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, V-2-2020: 687–693
    [doi: 10.5194/isprs-annals-V-2-2020-687-2020] [Paper] [Presentation] [YouTube]
  • 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. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, V-2-2020: 703–710
    [doi: 10.5194/isprs-annals-V-2-2020-703-2020] [Paper]
  • Huang R, Hong D, Xu Y, Yao W, Stilla U (2020) Multi-scale local context embedding for LiDAR point cloud classification. IEEE Geoscience and Remote Sensing Letters, 17(4): 721-725
    [doi: 10.1109/LGRS.2019.2927779]
  • Huang R, Xu Y, Hoegner L, Stilla U (2020) Efficient estimation of 3D shifts between point clouds using low-frequency components of phase correlation. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, V-2-2020: 227–234
    [doi: 10.5194/isprs-annals-V-2-2020-227-2020] [Paper] [Presentation] [YouTube]
  • 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]
  • 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, Yao W, Ye Z, Xu Y, Stilla U (2020) RIDF: A robust rotation invariant descriptor for 3d point cloud registration in the frequency domain. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, V-2-2020: 235–242
    [doi: 10.5194/isprs-annals-V-2-2020-235-2020] [Paper]
  • Shan J, Michaelsen E, Stilla U, Su F (2020) Foreword for the Special Issue on Advances in Pattern Recognition in Remote Sensing. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 13: 6164-6165
    [doi: 10.1109/JSTARS.2020.3028483]
  • 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. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, V-2-2020: 933–940
    [doi: 10.5194/isprs-annals-V-2-2020-933-2020] [Paper] [Presentation] [YouTube]
  • 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. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, V-1-2020: 157–163
    [doi: 10.5194/isprs-annals-V-1-2020-157-2020] [Paper]
  • 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 an optical remote sensing satellite based on a time-frequency analysis. Optics Express 28(11): 15805
    [doi:10.1364/OE.392194]
  • 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 between TIR and RGB images. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLIII-B2-2020: 111–118
    [doi: 10.5194/isprs-archives-XLIII-B2-2020-111-2020] [Paper] [Presentation] [YouTube]

 

Professur für Photogrammetrie und Fernerkundung

Prof. Dr.-Ing. Christoph Holst (komm.)

Technische Universität München
Arcisstr. 21
80333 München

Tel.: +49.89.289.22876
Fax: +49.89.289.23202

 

Leonhard Obermeyer Center
Department of Aerospace and Geodesy
TUM School of Engineering and Design

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