Efficient joint surface detection and depth estimation of single-photon Lidar data using assumed density filtering

K. Drummond, D. Yao, A. Pawlikowska, Robert Lamb, S. McLaughlin, Y. Altmann

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper addresses the problem of efficient single-photon Lidar (SPL) data processing for fast 3D scene reconstruction. Traditional methods for 3D ranging from Lidar data construct a histogram of the time of arrival (ToA) values of photon detection events to obtain final depth estimates for a desired target. However processing large histogram data volumes over long temporal sequences results in undesirable costs in memory requirement and computational time. By adopting a Bayesian formalism, we combine the online estimation strategy of Assumed Density Filtering (ADF) with joint surface detection and depth estimation methods to eventually process SPL data on-chip without the need for histogram data construction. We also illustrate how the data processing efficiency can be increased by reducing the set of unknown discrete variables based on posterior distribution estimates after each detection event, reducing computational cost for future detection events.

Original languageEnglish
Title of host publication2022 Sensor Signal Processing for Defence Conference (SSPD)
PublisherIEEE
ISBN (Electronic)9781665483483
DOIs
Publication statusPublished - 23 Sep 2022
Event11th International Conference in Sensor Signal Processing for Defence: from Sensor to Decision 2022 - London, United Kingdom
Duration: 13 Sep 202214 Sep 2022

Conference

Conference11th International Conference in Sensor Signal Processing for Defence: from Sensor to Decision 2022
Abbreviated titleSSPD 2022
Country/TerritoryUnited Kingdom
CityLondon
Period13/09/2214/09/22

Keywords

  • Assumed Density Filtering
  • Bayesian estimation
  • Detection
  • Ensemble estimation
  • Single-photon Lidar

ASJC Scopus subject areas

  • Instrumentation
  • Artificial Intelligence
  • Computer Networks and Communications
  • Signal Processing
  • Safety, Risk, Reliability and Quality
  • Acoustics and Ultrasonics

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