Date of Award
12-2025
Degree Type
Honors College Thesis
Academic Program
Forensics BS
Department
Criminal Justice
First Advisor
Kristi Johnson, M.S.
Second Advisor
George Raber, Ph.D.
Advisor Department
Criminal Justice; Geography and Geology
Abstract
While terrestrial LiDAR scanners are increasingly used by law enforcement agencies to document crime scenes, newer iPhone and iPad Pro devices possess a small LiDAR sensor that can perform similar tasks. Our research attempts to assess and compare the accuracy and precision of crime scene measurements collected from Recon‑3D and SiteScape on an iPhone 13 Pro Max against a FARO Focus S 350 as the control. Our experiment was conducted in a well-lit indoor mock crime scene measuring approximately 8.4 m x 11.8 m containing 41 labeled points. Each method was used to scan the scene three times, resulting in triplicates of 820 measurements that range from 0 to 15 m. While the SiteScape datasets underwent automatic and manual registration, the Recon‑3D datasets were processed with and without target detection, resulting in four tested methods. Recon‑3D with target detection showed the smallest random error with a mean (SD) of 1.53 (1.11) cm and the smallest systematic error at −0.72 (1.39) cm. Conversely, without target detection, Recon‑3D showed a significantly greater random error at 2.19 (1.26) cm and the greatest systematic error at −9.33 (6.35) cm. In other words, for Recon‑3D, target detection significantly increases both accuracy and precision and should always be used when possible. Our analysis showed that regardless of distance, the error of an individual measurement collected using Recon‑3D with target detection should fall between −7.04 and 5.02 cm. The automatically registered SiteScape dataset showed the greatest random error at 3.81 (2.36) cm and a reasonable systematic error at −2.32 (3.53) cm. In comparison, when manually registered, the SiteScape dataset showed a lower random error at 3.15 (1.82) cm but a greater systematic error at −4.56 (3.76) cm. In other words, manually registering the SiteScape dataset slightly increases precision but decreases accuracy. Given this minimal improvement, manual registration undermines SiteScape’s practicality and time efficiency, which are its key advantages over Recon‑3D. Therefore, automatic registration is recommended. Overall, compared to SiteScape, Recon‑3D can collect crime scene measurements with higher precision and accuracy and should be the method of choice when time and resources permit. Future research should include more replicates with varying scene sizes and without labels. Additionally, Apple LiDAR should be compared against other mobile LiDAR scanners.
Copyright
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Recommended Citation
Ang, Jason, "Assessing the Accuracy and Precision of Crime Scene Measurements Obtained from Apple LiDAR Scans" (2025). Honors Theses. 1000.
https://aquila.usm.edu/honors_theses/1000