Efficient Real-Time Quadcopter Propeller Detection and Attribute Estimation with High-Resolution Event Camera
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F25%3A00386495" target="_blank" >RIV/68407700:21230/25:00386495 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1007/978-3-031-95911-0_16" target="_blank" >https://doi.org/10.1007/978-3-031-95911-0_16</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-031-95911-0_16" target="_blank" >10.1007/978-3-031-95911-0_16</a>
Alternative languages
Result language
angličtina
Original language name
Efficient Real-Time Quadcopter Propeller Detection and Attribute Estimation with High-Resolution Event Camera
Original language description
In this paper, we present a computationally efficient method for real-time detection and state estimation of quadcopter propellers in high-resolution event-camera streams. We model local event arrivals as Poisson processes and exploit the memoryless nature of inter-arrival times to robustly detect periodic bursts from rotating blades, even at high rotational speeds. Unlike approaches that process data in chunks, our method updates the detection metrics for each incoming event. Once a propeller is detected, we first calculate its angular speed and then fit an ellipse to the aggregated propeller events to estimate pitch and roll. We introduce a new dataset (speeds 1100–8200 RPM; tilt angles 0∘, 10∘, and 90∘) and achieve near-perfect detection accuracy at an average real-time factor of 0.94 on a single CPU core, demonstrating the suitability of the approach for onboard deployment.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
—
Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Image Analysis
ISBN
978-3-031-95911-0
ISSN
0302-9743
e-ISSN
1611-3349
Number of pages
14
Pages from-to
217-230
Publisher name
Springer, Cham
Place of publication
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Event location
Reykjavik
Event date
Jun 23, 2025
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
001553875500016