@inproceedings{b6e4c5e3c1fd4a4aad2d014019e095cd,
title = "Material Recognition Using Time of Flight Lidar Surface Analysis",
abstract = "We are investigating a method for identifying materials from a distance, even when they are obscured, using a technique called Quantum Parametric Mode Sorting and single photons detection. By scanning a segment of the material, we are able to capture data on the relationships between the peak count of photons reflected at each position and the location of that reflection. This information allows us to measure the relative reflectance of the material and the texture of its surface, which enables us to achieve a material recognition accuracy of 99%, even maintaining 89.17% when materials are obscured by a lossy and multi-scattering obscurant that causes up to 15.2 round-trip optical depth.",
keywords = "Lidar, Machine Learning, Material Recognition",
author = "Daniel Tafone and Luke McEvoy and Sua, {Yong Meng} and Patrick Rehain and Yuping Huang",
note = "Publisher Copyright: {\textcopyright} 2023 SPIE.; Quantum Sensing, Imaging, and Precision Metrology 2023 ; Conference date: 28-01-2023 Through 02-02-2023",
year = "2023",
doi = "10.1117/12.2652945",
language = "English",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Jacob Scheuer and Shahriar, {Selim M.}",
booktitle = "Quantum Sensing, Imaging, and Precision Metrology",
}