PI: Ezra Che, Oregon State University
CO-PIs: Michael Olsen, Oregon State University and Chase Simpson, Oregon State University
Summary: Thanks to the rapid evolvement of 3D sensing technologies, a wide variety of systems are accessible for “reality capture” with tremendous quality and efficiency. It is crucial to clearly report the uncertainty of various data products and subsequent models considering their use cases, which can be challenging for the conventional accuracy assessment and reporting approaches. To overcome this challenge, this project aims to develop a novel, data-driven, scale-variant QA/QC method to estimate, report, and visualize the uncertainty of the data acquired from multiple sources to guide the data fusion process and support 3D modeling and other applications.