Exploiting Alternating DVS Shot Noise Event Pair Statistics to Reduce Background Activity
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Abstract (arXiv)
Dynamic Vision Sensors (DVS) record "events" corresponding to pixel-level brightness changes, resulting in data-efficient representation of a dynamic visual scene. As DVS expand into increasingly diverse applications, non-ideal behaviors in their output under extreme sensing conditions are important to consider. Under low illumination (below ~10 lux) their output begins to be dominated by shot noise events (SNEs) which increase the data output and obscure true signal. SNE rates can be controlled to some degree by tuning circuit parameters to reduce sensitivity or temporal response bandwidth at the cost of signal loss. Alternatively, an improved understanding of SNE statistics can be leveraged to develop novel techniques for minimizing uninformative sensor output. We first explain a fundamental observation about sequential pairing of opposite polarity SNEs based on pixel circuit logic and validate our theory using DVS recordings and simulations. Finally, we derive a practical result from this new understanding and demonstrate two novel biasing techniques to reduce SNEs by 50% and 80% respectively while still retaining sensitivity and/or temporal resolution.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 7 Apr 2023.
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Citing papers per year: 2023: 1; 2024: 2; 2025: 0; 2026: 1.
4 papers.
- 2023Robust e-NeRF: NeRF from Sparse & Noisy Events under Non-Uniform Motioncited by 44
- 2024Enhancing Visual Place Recognition via Fast and Slow Adaptive Biasing in Event Camerascited by 10
- 2024Monte Carlo Path Tracing and Statistical Event Detection for Event Camera Simulationcited by 1
- 2026Optical Linear Systems Framework for Event Sensing and Computational Neuromorphic Imagingcited by 1
- 2026Optical Linear Systems Framework for Event Sensing and Computational Neuromorphic Imaging20 Jan 2026
- 2024Monte Carlo Path Tracing and Statistical Event Detection for Event Camera Simulation15 Aug 2024
- 2024Enhancing Visual Place Recognition via Fast and Slow Adaptive Biasing in Event Cameras25 Mar 2024
- 2023Robust e-NeRF: NeRF from Sparse & Noisy Events under Non-Uniform Motion15 Sep 2023