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On fast object detection using single-photon lidar data
Author(s): Julian Tachella; Yoann Altmann; Stephen McLaughlin; Jean-Yves Tourneret
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Paper Abstract

Light detection and ranging (Lidar) systems based on single-photon detection can be used to obtain range and reflectivity information from 3D scenes with high range resolution. However, reconstructing the 3D surfaces from the raw single-photon waveforms is challenging, in particular when a limited number of photons is detected and when the ratio of spurious background detection events is large. This paper reviews a set of fast detection algorithms, which can be used to assess the presence of objects/surfaces in each waveform, allowing only the histograms where the imaged surfaces are present to be further processed. The original method we recently proposed is extended here using a multiscale approach to further reduce the computational complexity of the detection process. The proposed methods are compared to state-of-the-art 3D reconstruction methods using synthetic and real single-photon data and the results illustrate their benefits for fast and robust target detection.

Paper Details

Date Published: 9 September 2019
PDF: 10 pages
Proc. SPIE 11138, Wavelets and Sparsity XVIII, 111380T (9 September 2019); doi: 10.1117/12.2527685
Show Author Affiliations
Julian Tachella, Heriot-Watt Univ. (United Kingdom)
Yoann Altmann, Heriot-Watt Univ. (United Kingdom)
Stephen McLaughlin, Heriot-Watt Univ. (United Kingdom)
Jean-Yves Tourneret, Univ. of Toulouse (France)


Published in SPIE Proceedings Vol. 11138:
Wavelets and Sparsity XVIII
Dimitri Van De Ville; Manos Papadakis; Yue M. Lu, Editor(s)

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