RESEARCH ARTICLE
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Metrics and methods for evaluating model-driven reality capture plans
Amir Ibrahim,
Mani Golparvar-Fard,
Khaled El-Rayes,
Amir Ibrahim
Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, IL, USA
Search for more papers by this authorCorresponding Author
Mani Golparvar-Fard
Computer Science and Tech Entrepreneurship, University of Illinois at Urbana-Champaign, IL, USA
Correspondence
Mani Golparvar-Fard, Associate Professor of Civil Engineering, Computer Science and Tech Entrepreneurship, University of Illinois at Urbana-Champaign.
Address: 205 N. Mathews Ave., MC-250, Urbana, IL 61801, USA.
Email: [email protected]
Search for more papers by this authorKhaled El-Rayes
Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, IL, USA
Search for more papers by this authorAmir Ibrahim,
Mani Golparvar-Fard,
Khaled El-Rayes,
Amir Ibrahim
Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, IL, USA
Search for more papers by this authorCorresponding Author
Mani Golparvar-Fard
Computer Science and Tech Entrepreneurship, University of Illinois at Urbana-Champaign, IL, USA
Correspondence
Mani Golparvar-Fard, Associate Professor of Civil Engineering, Computer Science and Tech Entrepreneurship, University of Illinois at Urbana-Champaign.
Address: 205 N. Mathews Ave., MC-250, Urbana, IL 61801, USA.
Email: [email protected]
Search for more papers by this authorKhaled El-Rayes
Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, IL, USA
Search for more papers by this authorPresent address: Amir Ibrahim: . 205 N. Mathews Ave., MC-250, Urbana, IL 61801, USA
Abstract
This paper presents new metrics and methods for evaluating the quality of reality capture plans—commonly used to operate camera-mounted unmanned aerial vehicles (UAVs) or ground rovers—for construction progress monitoring and inspection of as-is conditions. Using 4D building information model (BIM) or 3D reality model as a priori, these metrics provide feedback on the quality of a plan (within a few minutes), accounting for resolution, visibility, accuracy, completeness of the capture, and satisfying battery capacity and line-of-sight requirements. A cloud-based system is introduced to create and optimize UAV/rover missions in the context of prior model. Results from real-world construction data sets demonstrate that the proposed metrics offer actionable insights into the accuracy and completeness of reality capture plans. Additionally, a capture plan—with a combination of canonical and noncanonical camera views—that satisfies the introduced metrics is statistically correlated with the quality of reconstructed reality. These metrics can improve computer-vision progress monitoring and inspection methods that rely on the construction site's appearance and geometry.
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