In a roofing project, acquiring the underlying as-built 3D geometry and visualizing the roof structure is needed in different phases of the project life-cycle. Architectural drawings, building information model (BIM) files, or aerial photogrammetry are used to estimate the roofing area in the bidding process. However, as a roof structure is never built to the exact drawing dimensions, as-built dimensions of boundaries of every roof plane have to be obtained several times during the course of its build. There are a number of surveying methods that can be used for this purpose: tape measuring, total station surveying, aerial photogrammetry, and laser scanning. However, obtaining measurements using these methods could be costly in terms of equipment, labor, and/or worker exposure to safety hazards. Aiming to address this limitation and provide roofing practitioners with an alternative roof surveying and visualization method that is simple to use, automated, inexpensive, and safe, a close-range videogrammetric roof 3D reconstruction framework is presented in this research. When using this method, a roofing contractor will simply collect stereo video streams of a target roof. The captured data is processed to generate a 3D wire-diagram for every roof plane. In this process, distinctive visual features of the scene (e.g., 2D points and lines) are first automatically detected and matched between video frames. Matched features and the camera calibration information are used to compute an initial estimation of the 3D structure. Then, a hybrid bundle adjustment algorithm is used to refine the result and acquire the geometry that has the maximum likelihood. Afterwards, different roof planes are found and a measurable 3D wire-diagram is generated for each plane.
| Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/52972 |
| Date | 12 January 2015 |
| Creators | Fathi, Habib |
| Contributors | DesRoches, Reginald |
| Publisher | Georgia Institute of Technology |
| Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
| Language | en_US |
| Detected Language | English |
| Type | Dissertation |
| Format | application/pdf |
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