EEPPR: Event-based Estimation of Periodic Phenomena Rate using Correlation in 3D

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F25%3A00379232" target="_blank" >RIV/68407700:21230/25:00379232 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1117/12.3055033" target="_blank" >http://dx.doi.org/10.1117/12.3055033</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1117/12.3055033" target="_blank" >10.1117/12.3055033</a>

Jazyk výsledku

angličtina

Název v původním jazyce

EEPPR: Event-based Estimation of Periodic Phenomena Rate using Correlation in 3D

Popis výsledku v původním jazyce

We present a novel method for measuring the rate of periodic phenomena (e.g., rotation, flicker, and vibration), by an event camera, a device asynchronously reporting brightness changes at independently operating pixels with high temporal resolution. The approach assumes that for a periodic phenomenon, a highly similar set of events is generated within a spatio-temporal window at a time difference corresponding to its period. The sets of similar events are detected by a correlation in the spatio-temporal event stream space. The proposed method, EEPPR, is evaluated on a dataset of 12 sequences of periodic phenomena, i.e. flashing light and vibration, and periodic motion, e.g., rotation, ranging from 3.2 Hz to 2 kHz (equivalent to 192-120 000 RPM). EEPPR significantly outperforms published methods on this dataset, achieving a mean relative error of 0.1% setting new state of the art. The dataset and codes are publicly available on GitHub.

Název v anglickém jazyce

EEPPR: Event-based Estimation of Periodic Phenomena Rate using Correlation in 3D

Popis výsledku anglicky

We present a novel method for measuring the rate of periodic phenomena (e.g., rotation, flicker, and vibration), by an event camera, a device asynchronously reporting brightness changes at independently operating pixels with high temporal resolution. The approach assumes that for a periodic phenomenon, a highly similar set of events is generated within a spatio-temporal window at a time difference corresponding to its period. The sets of similar events are detected by a correlation in the spatio-temporal event stream space. The proposed method, EEPPR, is evaluated on a dataset of 12 sequences of periodic phenomena, i.e. flashing light and vibration, and periodic motion, e.g., rotation, ranging from 3.2 Hz to 2 kHz (equivalent to 192-120 000 RPM). EEPPR significantly outperforms published methods on this dataset, achieving a mean relative error of 0.1% setting new state of the art. The dataset and codes are publicly available on GitHub.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2025

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of SPIE - The International Society for Optical Engineering

ISBN

9781510688285

ISSN

0277-786X

e-ISSN

1996-756X

Počet stran výsledku

7

Strana od-do

—

Název nakladatele

SPIE

Místo vydání

Bellingham (stát Washington)

Místo konání akce

Edinburg

Datum konání akce

10. 10. 2024

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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