RESEARCH | Recon-3D

recon-3d related publications

A Comparison between Leica RTC360 and Recon-3D Scan Data in Pre- and Post-Collision Vehicle Documentation

Lim, J. and Liscio, E., SAE Technical Paper Series, January 1, 2026.

Leica Vehicle Scan vs Recon3D Vehicle Scan and Crush Measurement Comparison

Daniel Vomhof, 4N6XPRT Systems

https://www.4n6xprt.com/papers/

Assessing iPhone LiDAR & Recon-3D for determining area of origin in bloodstain pattern analysis
Stephanie Stevenson, Eugene Liscio
Journal of Forensic Science, Technical Note, Jan 4, 2024, DOI: 10.1111/1556-4029.15476

Exploring New 3D Technology
Allen Vaughan, Cat Pate and Randy Pazzaglia
Accident Reconstruction Journal, Volume 33., No. 4., July/August 2023

Validation of Recon-3D, iPhone LiDAR for bullet trajectory documentation,
Cassandra E. Chase, Eugene Liscio, Forensic Science International, Volume 350, July 2023, https://doi.org/10.1016/j.forsciint.2023.111787

Recon-3D Measurement Accuracy Study for Small Scenes.
Liscio E, Lim J. ,J Assoc Crime Scene Reconstr. 2023;27:1-10.

"Accuracy and Repeatability of Mobile Phone LiDAR Capture,"
Miller, S., Hashemian, A., Gillihan, R., and Benes, S., SAE Technical Paper 2023-01-0614, 2023,
https://doi.org/10.4271/2023-01-0614.

Using the iPhone’s LiDAR technology to capture 3D forensic data at crime and crash scenes, (2022)
Authors: Sören Kottner Michael J. Thali Dominic Gascho, Forensic Imaging Available online 10 January 2023, 200535

apple lidar publications

iPhone LiDAR to Support Documentation of Clandestine Gravesite Photogrammetry Reconstruction and Depth Measurement Accuracy, Alice R Whittingham, Masters by Coursework, Murdoch University, 2024

Assessing Vehicle Profiling Accuracy of Handheld LiDAR Compared to Terrestrial Laser Scanning for Crash Scene Reconstruction
Desai, Jairaj, Jidong Liu, Robert Hainje, Robert Oleksy, Ayman Habib, and Darcy Bullock. 2021.
Sensors 21, no. 23: 8076. https://doi.org/10.3390/s21238076

Apple LiDAR Sensor for 3D Surveying: Tests and Results in the Cultural Heritage Domain
Lorenzo Teppati Losè, Alessandra Spreafico, Filiberto Chiabrando, Fabio Giulio Tonolo, https://www.mdpi.com/1792764

Heinrichs, B. and Yang, M., "Bias and Repeatability of Measurements from 3D Scans Made Using iOS-Based Lidar," SAE Int. J. Adv. & Curr. Prac. in Mobility 3(5):2219-2226, 2021, https://doi.org/10.4271/2021-01-0891.

Miller, Hashemian, A., Gillihan, R., & Helms, E. (2022). A Comparison of Mobile Phone LiDAR Capture and Established Ground based 3D Scanning Methodologies. https://doi.org/10.4271/2022-01-0832

Luetzenburg, Kroon, A., & Bjørk, A. A. (2021). Evaluation of the Apple iPhone 12 Pro LiDAR for an Application in Geosciences. Scientific Reports, 11(1), 22221–22221. https://doi.org/10.1038/s41598-021-01763-9

Maiese, Manetti, A. C., Ciallella, C., & Fineschi, V. (2022). The Introduction of a New Diagnostic Tool in Forensic Pathology: LiDAR Sensor for 3D Autopsy Documentation. Biosensors (Basel), 12(2), 132–. https://doi.org/10.3390/bios12020132

Mikalai, Andrey, D., Hawas, H. S., Tеtiana, Н., & Oleksandr, S. (2022). Human body measurement with the iPhone 12 Pro LiDAR scanner. AIP Conference Proceedings, 2430(1). https://doi.org/10.1063/5.0078310

Spreafico, Chiabrando, F., Teppati Losè, L., & Giulio Tonolo, F. (2021). THE IPAD PRO BUILT-IN LIDAR SENSOR: 3D RAPID MAPPING TESTS AND QUALITY ASSESSMENT. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences., XLIII-B1-2021, 63–69. https://doi.org/10.5194/isprs-archives-XLIII-B1-2021-63-2021

Gillihan. (2021). Accuracy Comparisons of iPhone 12 Pro LiDAR Outputs. ProQuest Dissertations Publishing.

Sirmacek, & Lindenbergh, R. . (2014). Accuracy assessment of building point clouds automatically generated from iphone images. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences., 40(5), 547–552. https://doi.org/10.5194/isprsarchives-XL-5-547-2014

Tavani, Billi, A., Corradetti, A., Mercuri, M., Bosman, A., Cuffaro, M., Seers, T., & Carminati, E. (2022). Smartphone assisted fieldwork: Towards the digital transition of geoscience fieldwork using LiDAR-equipped iPhones. Earth-Science Reviews, 227, 103969–. https://doi.org/10.1016/j.earscirev.2022.103969