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VibES: Induced Vibration for Persistent Event-Based Sensing

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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.

Vincenzo Polizzi, Stephen Yang, Quentin Clark, Jonathan Kelly, Igor Gilitschenski, David B. Lindell• 2025

Related benchmarks

TaskDatasetResultRank
Power Consumption AnalysisHardware Power Benchmarking
Power Consumption (W)0.282
7
Image Quality EvaluationAMI EV
Entropy0.24
2
Image Quality EvaluationLOGO
Entropy0.52
2
Image Quality EvaluationPattern Checkerboard
Entropy0.59
2
Image Quality EvaluationPATTERN
Entropy0.39
2
Edge extractionAMI-EV captured scenes
Avg Num Components82.9
2
Edge extractionLogo (captured scenes)
Avg Num Components175
2
Edge extractionPattern Checkerboard captured scenes
Average Number of Components140.7
2
Edge extractionPattern captured scenes
Avg Num Components116.3
2
Image ReconstructionAMI EV--
2
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