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15 November 2024 Event-based real-time detection and tracking of UAVs
Rikard Fridsén Skogsberg, Jens Grundmark, Matts Björck
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Proceedings Volume 13204, Emerging Imaging and Sensing Technologies for Security and Defence IX; 1320404 (2024) https://doi.org/10.1117/12.3031306
Event: Security + Defence, 2024, Edinburgh, United Kingdom
Abstract
High-performance visual detection and tracking of small unmanned aerial vehicles (UAVs) at a distance is crucial for laser-based countermeasures, which require precise and accurate aiming to be effective. Achieving robust and accurate real-time tracking while dealing with dynamic non-cooperative targets and challenging lighting conditions poses significant difficulties for tracking solutions. Event cameras represent a new perception paradigm to overcome these hurdles by registering changes in illumination asynchronously with low latency, high temporal resolution and large dynamic range. The cameras yield a sparse stream of event information which encodes changes in the scene. Accumulating events into frames and using traditional computer vision techniques can be applied, but sacrifice some of the information contained in the event stream. Asynchronous methods have shown promise in utilizing the event stream more efficiently, but are not yet at the same technical maturity as frame-based alternatives. This work introduces and evaluates two event-based end-to-end detection and tracking systems suitable for real-time applications. One asynchronous and one accumulating method were studied. The different methods are evaluated using an annotated event-dataset containing recordings of multi-rotor UAVs operating in an outdoor setting to compare the performance.
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(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
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Rikard Fridsén Skogsberg, Jens Grundmark, and Matts Björck "Event-based real-time detection and tracking of UAVs", Proc. SPIE 13204, Emerging Imaging and Sensing Technologies for Security and Defence IX, 1320404 (15 November 2024); https://doi.org/10.1117/12.3031306
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KEYWORDS
Unmanned aerial vehicles
Object detection
Sensors
Detection and tracking algorithms
Temporal resolution
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