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    Generating Absolute-Scale Point Cloud Data of Built Infrastructure Scenes Using a Monocular Camera Setting

    Source: Journal of Computing in Civil Engineering:;2015:;Volume ( 029 ):;issue: 006
    Author:
    Abbas Rashidi
    ,
    Ioannis Brilakis
    ,
    Patricio Vela
    DOI: 10.1061/(ASCE)CP.1943-5487.0000414
    Publisher: American Society of Civil Engineers
    Abstract: The global scale of point cloud data (PCD) generated through monocular photography and videogrammetry is unknown and can be calculated using at least one known dimension of the scene. Measuring one or more dimensions for this purpose induces a manual step in the three-dimensional reconstruction process; this increases the effort and reduces the speed of reconstructing scenes, and induces substantial human error in the process due to the high level of measurement accuracy needed. Other ways of measuring such dimensions are based on acquiring additional information by either using extra sensors or specific classes of objects existing in the scene; it was found that these solutions are not simple, cost effective, or general enough to be considered practical for reconstructing both indoor and outdoor built infrastructure scenes. To address the issue, this paper proposes a novel method for automatically calculating the absolute scale of built infrastructure PCD. A premeasured cube for outdoor scenes and a sheet of paper for indoor environments are used as the calibration patterns. Assuming that the dimensions of these objects are known, the proposed method extracts the objects’ corner points in two-dimensional video frames using a novel algorithm. The extracted corner points are then matched between the consecutive frames. Finally, the corresponding corner points are reconstructed along with other features of the scenes to determine the real-world scale. To evaluate the performance of the method, 10 indoor and 10 outdoor cases were selected and the absolute-scale PCD for each case was computed. Results illustrated the proposed algorithm is able to reconstruct the predefined objects with a high success rate, while the generated absolute-scale PCD is sufficiently accurate.
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      Generating Absolute-Scale Point Cloud Data of Built Infrastructure Scenes Using a Monocular Camera Setting

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    contributor authorAbbas Rashidi
    contributor authorIoannis Brilakis
    contributor authorPatricio Vela
    date accessioned2017-05-08T22:34:14Z
    date available2017-05-08T22:34:14Z
    date copyrightNovember 2015
    date issued2015
    identifier other49926933.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/82821
    description abstractThe global scale of point cloud data (PCD) generated through monocular photography and videogrammetry is unknown and can be calculated using at least one known dimension of the scene. Measuring one or more dimensions for this purpose induces a manual step in the three-dimensional reconstruction process; this increases the effort and reduces the speed of reconstructing scenes, and induces substantial human error in the process due to the high level of measurement accuracy needed. Other ways of measuring such dimensions are based on acquiring additional information by either using extra sensors or specific classes of objects existing in the scene; it was found that these solutions are not simple, cost effective, or general enough to be considered practical for reconstructing both indoor and outdoor built infrastructure scenes. To address the issue, this paper proposes a novel method for automatically calculating the absolute scale of built infrastructure PCD. A premeasured cube for outdoor scenes and a sheet of paper for indoor environments are used as the calibration patterns. Assuming that the dimensions of these objects are known, the proposed method extracts the objects’ corner points in two-dimensional video frames using a novel algorithm. The extracted corner points are then matched between the consecutive frames. Finally, the corresponding corner points are reconstructed along with other features of the scenes to determine the real-world scale. To evaluate the performance of the method, 10 indoor and 10 outdoor cases were selected and the absolute-scale PCD for each case was computed. Results illustrated the proposed algorithm is able to reconstruct the predefined objects with a high success rate, while the generated absolute-scale PCD is sufficiently accurate.
    publisherAmerican Society of Civil Engineers
    titleGenerating Absolute-Scale Point Cloud Data of Built Infrastructure Scenes Using a Monocular Camera Setting
    typeJournal Paper
    journal volume29
    journal issue6
    journal titleJournal of Computing in Civil Engineering
    identifier doi10.1061/(ASCE)CP.1943-5487.0000414
    treeJournal of Computing in Civil Engineering:;2015:;Volume ( 029 ):;issue: 006
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian