Automated as-built 3D reconstruction of civil infrastructure using computer vision: Achievements, opportunities, and challenges

被引:139
|
作者
Fathi, Habib [1 ]
Dai, Fei [2 ]
Lourakis, Manolis [3 ]
机构
[1] Pointivo Inc, CTO, Atlanta, GA USA
[2] W Virginia Univ, Dept Civil & Environm Engn, Morgantown, WV 26506 USA
[3] Fdn Res & Technol, Inst Comp Sci, Iraklion, Greece
关键词
Structure from motion; Civil infrastructure; Image-based 3D reconstruction; Spatial data collection; Point cloud; CLOSE RANGE PHOTOGRAMMETRY; ACCURACY; MOTION; REPRESENTATION; CALIBRATION; DETECTORS; CHECKING; FEATURES; VIEWS; LINES;
D O I
10.1016/j.aei.2015.01.012
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Image-based 3D reconstruction of civil infrastructure is an emerging topic that is gaining significant interest both in the scientific and commercial sectors of the construction industry. Reliable computer vision-based algorithms have become available over the last decade and they can now be applied to solve real-life problems in uncontrolled environments. While a large number of such algorithms have been developed by the computer vision and photogrammetry communities, relatively little work has been done to study their performance in the context of infrastructure. This paper aims to analyze the state-of-the-art in image-based 3D reconstruction and categorize existing algorithms according to different metrics that are important for the given purpose. An ideal solution is portrayed to show what the ultimate goal is. This will be followed by identifying gaps in knowledge and highlighting future research topics that could contribute to the widespread adoption of this technology in the construction industry. Finally, a list of practical constraints that make the 3D reconstruction of infrastructure a challenging task is presented. (C) 2015 Elsevier Ltd. All rights reserved.
引用
收藏
页码:149 / 161
页数:13
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