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Maritime Vessels Real-time Tracking-by-detection in UAV Videos
Background/Objectives: This paper presents a fast real-time multi-object tracking algorithm adopted for maritime vessels tracking in UAV videos. Methods/Statistical Analysis: This research applies extended multi-object tracking-bydetection framework in highly dynamic UAV-captured maritime environment. Propagation is performed using particle filter whose particle weights are updated using modified observation model that incorporates a term based upon trackers affinity. The latter is also used for trackers grouping, that handles detector inaccuracies, and preventing identity switches by means of special propagation mode that is enabled when targets approach each other and start to overlap. Findings: Our research has shown that state-of-art multi-tracking algorithm is applicable to maritime vessels real-time tracking in UAV videos, provided the use of weak and fast online classifiers, which weakness is compensated by algorithm features based on trackers affinity matrix. Improvements/Applications: This paper presents an approach to maritime vessels tracking that allows to use fast, but less accurate, simple detectors and classifiers, enabling real-time processing on board of small-sized UAVs, while keeping decent precision and accuracy.
Maritime Vessels Tracking, Multi-object Tracking, Particle Filter, Online Learning, Trackers Affinity, Trackingby- detection, UAV Surveillance.
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