This manuscript presents a new framework towards automated digital documentation and progress reporting of mechanical pipes in building construction projects, using smartphones. New methods were proposed to optimize video frame rate to achieve a desired image overlap; define metric scale for 3D reconstruction; extract pipes from point clouds; and classify pipes according to their planned bill of quantity radii. The effectiveness of the proposed methods in both laboratory (six pipes) and construction site (58 pipes) conditions was evaluated. It was observed that the proposed metric scale definition achieved sub-millimeter pipe radius estimation accuracy. Both laboratory and field experiments revealed that increasing the defined image overlap improved point cloud quality, pipe classification quality, and pipe radius/length estimation. Overall, it was found possible to achieve pipe classification F-measure, radius estimation accuracy, and length estimation percent error of 96.4%, 5.4 mm, and 5.0%, respectively, on construction sites using at least 95% image overlap.

该手稿提出了一个新的框架，用于使用智能手机实现自动化数字记录和建筑施工项目中机械管道的进度报告。提出了优化视频帧速率以实现所​​需图像重叠的新方法。定义用于3D重建的度量标度; 从点云中提取管道；并根据计划的工程量清单半径对管道进行分类。评价了所提出的方法在实验室（六个管道）和建筑工地（58个管道）条件下的有效性。可以看出，所提出的公制比例尺定义实现了亚毫米管半径估计精度。实验室和现场实验都表明，增加定义的图像重叠可以改善点云质量，管道分类质量以及管道半径/长度估计。全面的，