Keywords

structure-from-motion, photogrammetry, unmanned aerial vehicles, large-scale 3D model, campus model, reality modeling, view-planning, machine learning, object recognition

Abstract

Unmanned aerial vehicles (UAV) enable detailed historical preservation of large-scale infrastructure and contribute to cultural heritage preservation, improved maintenance, public relations, and development planning. Aerial and terrestrial photo data coupled with high accuracy GPS create hyper-realistic mesh and texture models, high resolution point clouds, orthophotos, and digital elevation models (DEMs) that preserve a snapshot of history. A case study is presented of the development of a hyper-realistic 3D model that spans the complex 1.7 km2 area of the Brigham Young University campus in Provo, Utah, USA and includes over 75 significant structures. The model leverages photos obtained during the historic COVID-19 pandemic during a mandatory and rare campus closure and details a large scale modeling workflow and best practice data acquisition and processing techniques. The model utilizes 80,384 images and high accuracy GPS surveying points to create a 1.65 trillion-pixel textured structure-from-motion (SfM) model with an average ground sampling distance (GSD) near structures of 0.5 cm and maximum of 4 cm. Separate model segments (31) taken from data gathered between April and August 2020 are combined into one cohesive final model with an average absolute error of 3.3 cm and a full model absolute error of(relative accuracies from 0.25 cm to 1.03 cm). Optimized and automated UAV techniques complement the data acquisition of the large-scale model, and opportunities are explored to archive as-is building and campus information to enable historical building preservation, facility maintenance, campus planning, public outreach, 3D-printed miniatures, and the possibility of education through virtual reality (VR) and augmented reality (AR) tours.

Original Publication Citation

https://www.mdpi.com/2504-446X/5/4/136/htm

Document Type

Peer-Reviewed Article

Publication Date

2021-11-17

Permanent URL

http://hdl.lib.byu.edu/1877/8912

Publisher

MDPI

Language

English

College

Ira A. Fulton College of Engineering

Department

Chemical Engineering

University Standing at Time of Publication

Associate Professor

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