Jul 2026· 2026 23rd International Conference on Ubiquitous Robots (UR)· pp. 554-560· 0 citations· 19 references
Computer Science
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.
Event cameras provide a high dynamic range and preserve brightness-change cues in lighting conditions where conventional RGB frames may be noisy or saturated. To benchmark event-guided restoration across a broad illumination range, we organized the SEE Challenge 2026 with the Event-Based Multimodal Vision Workshop at E...
Yun-Fan Lu, Ming-Chao Xu, Han-Yu Zhou et al.· 0 citations
An event-RGB fusion Gaussian splatting framework that integrates event information into both optimization and densification stages of the Gaussian splatting pipeline, taking advantage of novel event sensors with high frame-rate.
Xiao-Yang Bai, Zhenyang Li, Wei-Wei Xu et al.· 0 citations
Image reconstruction in nighttime dynamic scenes is challenged by low illumination, long exposure, rapid camera or object motion, and sensor noise. Conventional RGB cameras, therefore, struggle to recover both sufficient brightness and clear structural details in nighttime dynamic scenes. To address this problem, we pr...
Qing-Jiao Meng, Ji Li, Yan Jin· Journal of Imaging· 0 citations
Cyclops is proposed, a framework that translates sparse Non-Repetitive Scanning LiDAR intensity into RGB video, enabling camera-free inference for all-day perception tasks and mitigating inter-frame flickering.
Wei Gao, Jian Shu, Ming-Le Zhao et al.· 0 citations
Accurate extrinsic calibration between event-based and frame-based cameras remains a practical bottleneck for heterogeneous stereo systems. Existing approaches often require sensor or target motion, precise synchronization, or computationally expensive event-to-image reconstruction. We propose a simple, motion-free cro...
Nico Hessenthaler, Adam T. Müller, N. Stache· 0 citations
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