Joint Depth and Reflectivity Estimation using Single-Photon LiDAR

TL;DR

This paper introduces SPLiDER, a novel method for simultaneous depth and reflectivity estimation in single-photon LiDAR, especially effective in dynamic scenes, by leveraging their mutual correlation for improved 3D reconstruction.

Contribution

It provides a theoretical analysis of the correlation between depth and reflectivity and proposes a joint estimation method that outperforms existing separate or sequential approaches.

Findings

SPLiDER achieves higher reconstruction accuracy in synthetic data.

The method outperforms existing approaches on real SP-LiDAR data.

Joint estimation improves results in fast-moving scenes.

Abstract

Single-Photon Light Detection and Ranging (SP-LiDAR is emerging as a leading technology for long-range, high-precision 3D vision tasks. In SP-LiDAR, timestamps encode two complementary pieces of information: pulse travel time (depth) and the number of photons reflected by the object (reflectivity). Existing SP-LiDAR reconstruction methods typically recover depth and reflectivity separately or sequentially use one modality to estimate the other. Moreover, the conventional 3D histogram construction is effective mainly for slow-moving or stationary scenes. In dynamic scenes, however, it is more efficient and effective to directly process the timestamps. In this paper, we introduce an estimation method to simultaneously recover both depth and reflectivity in fast-moving scenes. We offer two contributions: (1) A theoretical analysis demonstrating the mutual correlation between depth and reflectivity and the conditions under which joint estimation becomes beneficial. (2) A novel reconstruction method, "SPLiDER", which exploits the shared information to enhance signal recovery. On both synthetic and real SP-LiDAR data, our method outperforms existing approaches, achieving superior joint reconstruction quality.