# Probabilistic Approach for Detection of High-Frequency Periodic Signals using an Event Camera

arXiv: https://arxiv.org/abs/2205.04691 · HTML: https://mlsanity.com/paper/2205.04691/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 7 of its 21 references that are in the map.
- First posted on arXiv 10 May 2022.

## Builds on (most cited first, 7 of 7)

- [Event-based Vision: A Survey](https://mlsanity.com/paper/1904.08405/) (2019)
- [HATS: Histograms of Averaged Time Surfaces for Robust Event-based Object Classification](https://mlsanity.com/paper/1803.07913/) (2018)
- [Event-based Moving Object Detection and Tracking](https://mlsanity.com/paper/1803.04523/) (2018)
- [Semi-Dense 3D Reconstruction with a Stereo Event Camera](https://mlsanity.com/paper/1807.07429/) (2018)
- [Speed Invariant Time Surface for Learning to Detect Corner Points with Event-Based Cameras](https://mlsanity.com/paper/1903.11332/) (2019)
- [FA-Harris: A Fast and Asynchronous Corner Detector for Event Cameras](https://mlsanity.com/paper/1906.10925/) (2019)
- [Asynchronous Tracking-by-Detection on Adaptive Time Surfaces for Event-based Object Tracking](https://mlsanity.com/paper/2002.05583/) (2020)

## Built on by (most cited first, 3 of 3)

- [On the Theory of Bias Tuning in Event Cameras](https://mlsanity.com/paper/2501.18788/) (2025)
- [Event Driven Clustering Algorithm](https://mlsanity.com/paper/2602.00115/) (2026)
- [EventRadar: Long-Range Visual UAV Discovery through Spatiotemporal Event Sensing](https://mlsanity.com/paper/2606.11285/) (2026)

## Abstract (arXiv)

Being inspired by the biological eye, event camera is a novel asynchronous technology that pose a paradigm shift in acquisition of visual information. This paradigm enables event cameras to capture pixel-size fast motions much more naturally compared to classical cameras. In this paper we present a new asynchronous event-driven algorithm for detection of high-frequency pixel-size periodic signals using an event camera. Development of such new algorithms, to efficiently process the asynchronous information of event cameras, is essential and being a main challenge in the research community, in order to utilize its special properties and potential. It turns out that this algorithm, that was developed in order to satisfy the new paradigm, is related to an untreated theoretical problem in probability: let 0≤τ1≤τ2≤cdots≤τm≤1, originated from an unknown distribution. Let also ε,δ∈ℝ, and d∈mathbbN. What can be said about the probability Phi(m,d) of having more than d adjacent τi-s pairs that the distance between them is δ, up to an error ε ? This problem, that reminds the area of order statistic, shows how the new visualization paradigm is also an opportunity to develop new areas and problems in mathematics.