Event cameras are a bio-inspired class of sensors that asynchronously measure per-pixel intensity changes. Under fixed illumination conditions in static or low-motion scenes, rigidly mounted event cameras are unable to generate any events and become unsuitable for most computer vision tasks. To address this limitation, recent work has investigated motion-induced event stimulation, which often requires complex hardware or additional optical components. In contrast, we introduce a lightweight approach to sustain persistent event generation by employing a simple rotating unbalanced mass to induce periodic vibrational motion. This is combined with a motion-compensation pipeline that removes the injected motion and yields clean, motion-corrected events for downstream perception tasks. We develop a hardware prototype to demonstrate our approach and evaluate it on real-world datasets. Our method reliably recovers motion parameters and improves both image reconstruction and edge detection compared to event-based sensing without motion induction.
@article{arxiv.2508.19094,
title = {VibES: Induced Vibration for Persistent Event-Based Sensing},
author = {Vincenzo Polizzi and Stephen Yang and Quentin Clark and Jonathan Kelly and Igor Gilitschenski and David B. Lindell},
journal= {arXiv preprint arXiv:2508.19094},
year = {2026}
}
Comments
Accepted to the IEEE International Conference on 3D Vision (3DV), Vancouver, BC, Canada, Mar 20-23, 2026