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Event cameras are ideal for object tracking applications due to their abilityto capture fast-moving objects while mitigating latency and data redundancy.Existing event-based clustering and feature tracking approaches forsurveillance and object detection work well in the majority of cases, but fallshort in a maritime environment. Our application of maritime vessel detectionand tracking requires a process that can identify features and output aconfidence score representing the likelihood that the feature was produced by avessel, which may trigger a subsequent alert or activate a classificationsystem. However, the maritime environment presents unique challenges such asthe tendency of waves to produce the majority of events, demanding the majorityof computational processing and producing false positive detections. Byfiltering redundant events and analyzing the movement of each event cluster, wecan identify and track vessels while ignoring shorter lived and erraticfeatures such as those produced by waves.

Real-Time Event-Based Tracking and Detection for Maritime Environments