Real-time 3D reconstruction using single-photon Lidar data

Within the university, the signal/image processing and photonics research groups ( are working together to push the frontiers of single-photon imaging. In particular, single-photon technology offers important advantages in the field of light detection and ranging (Lidar) 3D imaging. As many key applications of depth imaging require real-time processing, e.g. self-driving cars [1] or underwater imaging [2], there has been recent attention to new fast 3D reconstruction algorithms. Preliminary results have demonstrated the benefits of massively parallelisable algorithms allowing unprecedented frame rates (below 10Hz). Nonetheless, these results are still far from requirements for industrial deployment as such methods have been implemented on desktop machines. Thus, this project will be devoted to design and build a new light and portable, GPU-based embedded system, that can embed the processing methods developed in our group and that can be easily interfaced with several single-photon Lidar system.

The Msc project involves advanced concepts in signal processing, parallel programming and embedded systems. The module developed during the project can be a game changer to accelerate the deployment of advances of single-photon Lidar technologies for autonomous vehicles and maximise its impact rapidly.

[1] Hecht, J. (2018). Lidar for Self-Driving Cars. Optics and Photonics News.
[2] Maccarone et al. (2015). Underwater depth imaging using time-correlated single-photon counting. Optics express.

Supervisor name: 
Dr. Yoann Altmann
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