  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%, 5.4mm, and 5.0%, respectively, on construction sites
using at least 95% image overlap.
