Real-Time Non-Line-of-Sight Imaging Using
Single-Photon LiDAR
Name
tsao-ntsao-meng-eecs-2025-thesis.pdf
Description
Thesis PDF
Size
56.56 MB
Format
Adobe PDF
Checksum (MD5)
5bba4b58c9fd6fab59e36a671a4a3a42
Author(s)
Tsao, Nicholas
Advisor(s)
Raskar, Ramesh
Date Issued
May 2025
Publisher
Massachusetts Institute of Technology
Abstract
Robust real-time imaging systems have allowed for many advances in robotics and autonomous navigation, though limited visibility in many real-world settings remains a significant challenge. Non-Line-of-Sight (NLOS) sensing allows for imaging systems to “see around corners", expanding their range of perception, providing access information for realtime decision-making. A promising approach to NLOS sensing is through single-photon LiDAR, which is commonly used for range-finding in many imaging systems. In addition to range-finding, single-photon LiDAR systems can provide a deeply rich data source in the form of photon count histograms after reflecting off scene geometry, capturing detailed information from multiple bounces. NLOS imaging can be achieved by parsing third-bounce light from such single-photon LiDAR sensors, which can be used for a variety of detection and localization tasks, and recent work has demonstrated capabilities in a wide range of applications. This work aims to further develop the NLOS imaging system by demonstrating a fully functional NLOS system using low-cost, consumer-grade SPAD hardware for real-time NLOS imaging, detection, and localization. We lay the ground work for NLOS imaging systems by developing infrastructure for NLOS processing in real-time, and we examine the potential for NLOS systems to operate on cheap hardware using data-driven approaches. Our work implements and demonstrates full end-to-end capacity for these NLOS imaging systems in a number of applications including person detection and localization, facilitating future research in this field and paving the way for NLOS integration into consumer devices.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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