Fast Surface Detection Using Single-Photon Detection Events

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

5 Citations (Scopus)
128 Downloads (Pure)


This paper presents a fast object detection algorithm for 3D single-photon Lidar data. Lidar imaging acquires time-of-flight (ToFs) events in different spatial locations to build a 3D image of the observed objects. However, high ambient light or obscurants, might affect the reconstruction quality of the 3D scene. This paper proposes a solution by first detecting the pixels containing photons reflected from a object/surface, allowing a higher level processing of the data while only accounting for informative pixels. In contrast to histogram based approaches, the proposed algorithm operates on the detected photon events allowing a reduction in memory requirements and computational times. A Bayesian approach is considered leading to analytical estimates that can be computed efficiently. Results on simulated and real data highlight the benefit of the proposed approach when compared to a state-of-the-art algorithm based on histogram of counts.
Original languageEnglish
Title of host publication2020 Sensor Signal Processing for Defence Conference (SSPD)
ISBN (Electronic)978-1-7281-3810-7
Publication statusPublished - 30 Nov 2020
Event9th Sensor Signal Processing for Defence 2020: from Sensor to Decision -
Duration: 15 Sept 202016 Sept 2020


Conference9th Sensor Signal Processing for Defence 2020
Abbreviated titleSSPD 2020


  • 3D Lidar imaging
  • Bayesian approach
  • single-photon events
  • sparse photon regime
  • target detection

ASJC Scopus subject areas

  • Artificial Intelligence
  • Signal Processing


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