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A Comparison of Mobile Phone LiDAR Capture and Established Ground based 3D Scanning Methodologies J.S. Held LLC

SAE Technical Papers (1906-current) Available online

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Format:
Book
Conference/Event
Author/Creator:
Miller, Seth Higgins, author.
Contributor:
Gillihan, Robert
Hashemian, Alireza
Helms, Ethan
Conference Name:
WCX SAE World Congress Experience (2022-04-05 : Detroit & Online, Michigan, United States)
Language:
English
Physical Description:
1 online resource cm
Place of Publication:
Warrendale, PA SAE International 2022
Summary:
Ground-based Light Detection and Ranging (LiDAR) using FARO Focus 3D scanners (and other brands of scanners) are repeatedly shown to accurately capture the geometry of accident scenes, accident vehicles, and exemplar vehicles, as well as corresponding evidence from these sources such as roadway gouge marks, vehicle crush depth, debris fields, and burn areas. However, ground-based scanners require expensive and large equipment on-site, as well as other materials that may be required depending on the scenario, such as tripods and alignment spheres. New technologies, such as Apple's mobile phone LiDAR capture, were released recently for their newer model phones, and these devices offer a way to obtain LiDAR data but with less cumbersome and less expensive equipment. This mobile LiDAR can be captured using many different applications from the App Store which can then be exported into point cloud data. This paper will investigate the accuracy of Apple's mobile phone LiDAR when obtaining geometry from multiple exemplar vehicles. This mobile phone LiDAR data will be compared against LiDAR captured from the same exemplar vehicles using the current standard technology, the FARO Focus 3D scanner. Multiple applications will be chosen for the mobile phone LiDAR export to investigate accuracy differences between the applications, and results are compared using the software CloudCompare
Notes:
Vendor supplied data
Publisher Number:
2022-01-0832
Access Restriction:
Restricted for use by site license

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