VibES: Induced Vibration for Persistent Event-Based Sensing
About
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.
Related benchmarks
| Task | Dataset | Result | Rank | |
|---|---|---|---|---|
| Power Consumption Analysis | Hardware Power Benchmarking | Power Consumption (W)0.282 | 7 | |
| Image Quality Evaluation | AMI EV | Entropy0.24 | 2 | |
| Image Quality Evaluation | LOGO | Entropy0.52 | 2 | |
| Image Quality Evaluation | Pattern Checkerboard | Entropy0.59 | 2 | |
| Image Quality Evaluation | PATTERN | Entropy0.39 | 2 | |
| Edge extraction | AMI-EV captured scenes | Avg Num Components82.9 | 2 | |
| Edge extraction | Logo (captured scenes) | Avg Num Components175 | 2 | |
| Edge extraction | Pattern Checkerboard captured scenes | Average Number of Components140.7 | 2 | |
| Edge extraction | Pattern captured scenes | Avg Num Components116.3 | 2 | |
| Image Reconstruction | AMI EV | -- | 2 |