2010
DOI: 10.1061/(asce)co.1943-7862.0000126
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Machine Vision-Based Concrete Surface Quality Assessment

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Cited by 72 publications
(26 citation statements)
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“…80]. Examples of using videogrammetry for damage detection and safety evaluation in infrastructure projects can be found in [86][87][88][89] where the technique provided desirable accuracy in different sectors. In a similar study, an algorithm was developed to identify objects from video frames in order to detect moving equipment on construction sites [90].…”
Section: Videogrammetrymentioning
confidence: 98%
“…80]. Examples of using videogrammetry for damage detection and safety evaluation in infrastructure projects can be found in [86][87][88][89] where the technique provided desirable accuracy in different sectors. In a similar study, an algorithm was developed to identify objects from video frames in order to detect moving equipment on construction sites [90].…”
Section: Videogrammetrymentioning
confidence: 98%
“…Zhu and Brilakis [21,22] have successfully created vision-based recognition models to detect concrete columns in images and videos, and to assess the quality of concrete surfaces, respectively. Following this strategy, in this paper a recognition model for automating the detection of potholes in images is presented.…”
Section: Methodsmentioning
confidence: 99%
“…Among them, [129,5] are computationally more efficient. The missing link appears to be the material modelling, but since separate works on material modelling exist [24,133,43], including this step should be straightforward.…”
Section: Overall Analysismentioning
confidence: 99%