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    請使用永久網址來引用或連結此文件: http://ir.lib.ncu.edu.tw/handle/987654321/72489


    題名: 以無人飛行載具拍攝影像建置三維橋梁模型之初步研究;A Preliminary Study on Generation of 3D Bridge Models using Images Captured by Unmanned Aerial Vehicle
    作者: 吳明諺;Wu,Ming-Yen
    貢獻者: 營建管理研究所
    關鍵詞: 無人飛行載具;橋梁檢測;三維橋梁模型;UAV;bridge inspection;3D bridge model
    日期: 2016-07-21
    上傳時間: 2016-10-13 15:23:49 (UTC+8)
    出版者: 國立中央大學
    摘要: 目前臺灣橋梁管理單位已開始應用無人飛行載具(Unmanned Aerial Vehicle, UAV)協助橋梁檢測作業。因相同橋梁構件多為類似且具相同外型,檢測者單看UAV所拍攝之相片實難以辨識其劣化構件的確切位置,故本研究利用以二維相片建置三維模型之軟體,將UAV拍攝橋梁之相片建置成如同現地之三維橋梁模型,以協助檢測人員之判斷。
    因橋梁檢測需拍攝橋上與橋下之所有構件,以UAV拍攝時其飛行路徑遠較於僅須在高空拍攝之邊坡或建築物,複雜許多。此外,橋下構件如橋底版、橋墩等相片中常見之天空與雲層背景,使組成三維橋梁模型之困難度,亦遠比邊坡或建築物高出許多。經本研究實際拍攝並進行組模測試後,可建置較為優異三維橋梁模型之條件為︰(1)於光照強度較柔和、晴時多雲的天氣下拍攝, (2)相機應與橋梁構件成45°拍攝角以減少相片中天空與雲層,(3)避開UAV機體入鏡,(4)使用單一相機拍攝,(5)使用修正魚眼效果之相片,以及(6)使相片疊合率為上下達80~90%,左右達50%~60%。
    受限於目前UAV、相機硬體與三維建模軟體之效能,本研究所建立三維橋梁模型,仍無法達到十分精確之程度,故與目前橋梁檢測之實務與應用仍有相當之距離。未來在軟硬體之效能更加提升後,本研究之成果將有助於精確三維橋梁模型之建立。
    ;Using unmanned aerial vehicle (UAV) to assist bridge inspection has become a popular trend in Taiwan. However, since same type of bridge components are similar, it is very difficult to identify the correct position of a deterioration from photos or images captured by the UAVs. Thus, this study aims at generating three-dimensional (3D) models for bridges to facilitate the inspection task using those two-dimensional (2D) images.

    Since there are many types of bridge components, the flying routes of the UAV are much more complicate than those for filming land slopes or buildings. In addition, photos with sky or clouds in the background of the under-bridge components such as slabs or piers, often make it very difficult to generate 3D bridge models. The same task is much easier for land slopes or buildings. After many tests in this study, it was concluded that a better 3D bridge model can be obtained under the following conditions: (1) capturing images under soft daylight such as in cloudy days, (2) keeping the camera have a 45 degree with the component, (3) avoiding capturing images of the UAV components, (4) capturing images by a single camera, (5) correcting fish-eye effect images, and (6) overlapping of images with 80% to 90% vertically and 50% to 60% horizontally.

    Despite of numerous tests, the 3D bridge models generated in this study are not as precise as expected nor sufficient for inspection use due to the limited capabilities of current UAV, camera, and 3D generation software. However, the research results of this study still provide useful guidance for future study when capabilities of these hardware and software are significantly improved.
    顯示於類別:[營建管理研究所 ] 博碩士論文

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