VibES: Induced Vibration for Persistent Event-Based Sensing

TL;DR

VibES introduces a simple vibration-based method to induce persistent event generation in event cameras, enabling improved perception in static scenes without complex hardware modifications.

Contribution

The paper presents a lightweight vibration approach combined with motion compensation to sustain event generation, addressing limitations of static event cameras.

Findings

Enhanced event generation in static scenes

Improved image reconstruction and edge detection

Effective motion parameter recovery

Abstract

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.