Only-Event Camera MVS via Phosphorescent Material in Darkness

Abstract

Perception in dark or texture-less environments remains a major challenge for mobile robots, where conventional photogrammetric pipelines fail due to insufficient illumination and unreliable feature correspondences. In extreme scenarios such as lunar or underground exploration, both lighting and power are severely constrained. To address this issue, we propose an event-only Structure from Motion and Multi-view Stereo (SfM-MVS) framework using ultraviolet-activated phosphorescent materials as temporary artificial features in complete darkness. An event camera captures intensity changes emitted by the phosphorescent material, and the raw event data are reconstructed into image sequences using an Event-to-Video (E2VID), which is a Recurrent Neural Network (RNN)-based method. The refined frames are then processed through SfM and MVS for three-dimensional (3D) reconstruction. Experimental results demonstrate that the proposed framework enables effective 3D reconstruction using phosphorescent materials in extremely low-light environments.