Projects per year
Abstract / Description of output
Single-photon light detection and ranging (lidar) captures depth and intensity information of a 3D scene. Reconstructing a scene from observed photons is a challenging task due to spurious detections associated with background illumination sources. To tackle this problem, there is a plethora of 3D reconstruction algorithms which exploit spatial regularity of natural scenes to provide stable reconstructions. However, most existing algorithms have computational and memory complexity proportional to the number of recorded photons. This complexity hinders their real-time deployment on modern lidar arrays which acquire billions of photons per second. Leveraging a recent lidar sketching framework, we show that it is possible to modify existing reconstruction algorithms such that they only require a small sketch of the photon information. In particular, we propose a sketched version of a recent state-of-the-art algorithm which uses point cloud denoisers to provide spatially regularized reconstructions. A series of experiments performed on real lidar datasets demonstrates a significant reduction of execution time and memory requirements, while achieving the same reconstruction performance than in the full data case.
Original language | English |
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Title of host publication | 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) |
Publisher | Institute of Electrical and Electronics Engineers |
Pages | 1566-1570 |
Number of pages | 5 |
ISBN (Electronic) | 978-1-6654-0540-9 |
ISBN (Print) | 978-1-6654-0541-6 |
DOIs | |
Publication status | E-pub ahead of print - 27 Apr 2022 |
Event | ICASSP 2022: IEEE International Conference on Acoustics, Speech and Signal Processing - Singapore Duration: 7 May 2022 → … https://2022.ieeeicassp.org |
Publication series
Name | International Conference on Acoustics, Speech, and Signal Processing (ICASSP) |
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Publisher | IEEE |
ISSN (Print) | 1520-6149 |
ISSN (Electronic) | 2379-190X |
Conference
Conference | ICASSP 2022 |
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Abbreviated title | ICASSP 2022 |
Period | 7/05/22 → … |
Internet address |
Keywords / Materials (for Non-textual outputs)
- 3D reconstruction
- Inverse problems
- compressive learning
- single-photon lidar
Fingerprint
Dive into the research topics of 'Sketched RT3D: How to Reconstruct Billions of Photons Per Second'. Together they form a unique fingerprint.Projects
- 1 Finished
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C-SENSE: Exploiting low dimensional models in sensing, computation and signal processing
1/09/16 → 31/08/22
Project: Research
Research output
- 1 Article
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Spline Sketches: An Efficient Approach for Photon Counting Lidar
Sheehan, M. P., Tachella, J. & Davies, M. E., 23 May 2024, (E-pub ahead of print) In: IEEE Transactions on Computational Imaging. 10, p. 863-875 13 p.Research output: Contribution to journal › Article › peer-review
Open AccessFile
Prizes
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Best Student Paper ICASSP 2022
Tachella, Julián (Recipient), Sheehan, Mikey (Recipient) & Davies, Michael (Recipient), 27 May 2022
Prize: Prize (including medals and awards)