EVALUATION OF THE POTENTIAL OF AERIAL THERMAL IMAGERY TO GENERATE 3D POINT CLOUDS

被引:0
|
作者
Alebooye, S. [1 ]
Samadzadegan, F. [1 ]
Javan, F. Dadrass [1 ]
机构
[1] Univ Tehran, Sch Surveying & Geospatial Engn, Coll Engn, Tehran, Iran
关键词
Aerial Thermal Imagery; 3D Point Clouds; UAV; SGM; Key Frame Extraction; Camera Calibration;
D O I
10.5194/isprs-annals-X-4-W1-2022-57-2023
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This research evaluates the ability of thermal images obtained from aerial platforms to produce 3D point clouds. In this study, the thermal camera is first calibrated. Then, in order to avoid data redundancy, the key frames of the obtained thermal video are separated from other frames. Afterwards, the point clouds are generated and then the thermal ortho image is created from the key frames. The evaluation is done using visible orthophoto, ground control points and the linearity of the edges of buildings extracted from thermal images. The results of this study show that the thermal ortho image matches the visible ortho image with a good accuracy in the study area. Moreover, the standard deviation of the edges of the buildings has been calculated for a number of reconstructed buildings in thermal ortho with proper dispersion. 77% of the measurements taken from the edges of the buildings coincide with a straight line with an accuracy of better than two pixels, and about half of these values are extracted with an accuracy of better than a pixel.
引用
收藏
页码:57 / 62
页数:6
相关论文
共 50 条
  • [1] Classification of Aerial Photogrammetric 3D Point Clouds
    Becker, C.
    Rosinskaya, E.
    Hani, N.
    d'Angelo, E.
    Strecha, C.
    [J]. PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING, 2018, 84 (05): : 287 - 295
  • [2] 3D SURFACE GENERATION FROM AERIAL THERMAL IMAGERY
    Khodaei, Behshid
    Samadzadegan, Farhad
    Javan, Farzaneh Dadras
    Hasani, Hadiseh
    [J]. INTERNATIONAL CONFERENCE ON SENSORS & MODELS IN REMOTE SENSING & PHOTOGRAMMETRY, 2015, 41 (W5): : 401 - 405
  • [3] Leaf Area Index evaluation in vineyards using 3D point clouds from UAV imagery
    L. Comba
    A. Biglia
    D. Ricauda Aimonino
    C. Tortia
    E. Mania
    S. Guidoni
    P. Gay
    [J]. Precision Agriculture, 2020, 21 : 881 - 896
  • [4] Leaf Area Index evaluation in vineyards using 3D point clouds from UAV imagery
    Comba, L.
    Biglia, A.
    Aimonino, D. Ricauda
    Tortia, C.
    Mania, E.
    Guidoni, S.
    Gay, P.
    [J]. PRECISION AGRICULTURE, 2020, 21 (04) : 881 - 896
  • [5] QUALITY OF 3D POINT CLOUDS FROM HIGHLY OVERLAPPING UAV IMAGERY
    Haala, Norbert
    Cramer, Michael
    Rothermel, Mathias
    [J]. UAV-G2013, 2013, : 183 - 188
  • [6] Generation of TIR-attributed 3D Point Clouds from UAV-based Thermal Imagery
    Westfeld, Patrick
    Mader, David
    Maas, Hans-Gerd
    [J]. PHOTOGRAMMETRIE FERNERKUNDUNG GEOINFORMATION, 2015, (05): : 381 - 393
  • [7] GPU-BASED MAPPING OF THERMAL IMAGERY FOR GENERATING 3D OCCLUSION-AWARE POINT CLOUDS
    Lopez, Alfonso
    Jurado, Juan M.
    Ogayar, Carlos J.
    Feito, Francisco R.
    [J]. 2022 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2022), 2022, : 1460 - 1463
  • [8] Learning-Based Shadow Detection in Aerial Imagery Using Automatic Training Supervision from 3D Point Clouds
    Ufuktepe, Deniz Kavzak
    Collins, Jaired
    Ufuktepe, Ekincan
    Fraser, Joshua
    Krock, Timothy
    Palaniappan, Kannappan
    [J]. 2021 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION WORKSHOPS (ICCVW 2021), 2021, : 3919 - 3928
  • [9] On Performance Evaluation of Registration Algorithms for 3D Point Clouds
    Attia, Mouna
    Slama, Yosr
    Kamoun, Mohamed Amine
    [J]. 2016 13TH INTERNATIONAL CONFERENCE ON COMPUTER GRAPHICS, IMAGING AND VISUALIZATION (CGIV), 2016, : 45 - 50
  • [10] Evaluation of Denoising and Voxelization Algorithms on 3D Point Clouds
    Gonizzi Barsanti, Sara
    Marini, Marco Raoul
    Malatesta, Saverio Giulio
    Rossi, Adriana
    [J]. REMOTE SENSING, 2024, 16 (14)