Fast Multiscale 3D Reconstruction Using Single-Photon LiDaR Data

Single-photon technology is emerging as a key approach to 3D Imaging. This paper presents a reconstruction algorithm that exploits data statistics and multiscale information to deliver clean depth and reflectivity images together with associated uncertainty maps. The statistical method has been implemented to run on graphics processing units (GPUs) that enable real-time reconstruction of moving scenes at more than 1000 depth frames per second on the 32x64 pixels real Quantic4x4 sensor data. Comparisons with state-of-the-art algorithms on simulated and real data demonstrate the robust and efficient performance of the proposed method.