论文标题
基于事件的实时跟踪和海上环境的检测
Real-Time Event-Based Tracking and Detection for Maritime Environments
论文作者
论文摘要
事件摄像机是对象跟踪应用程序的理想选择，因为它们能够捕获快速移动对象的同时减轻延迟和数据冗余。在大多数情况下，现有的基于事件的聚类和特征跟踪方法可以很好地工作，但在海上环境中不足。我们对海事容器检测和跟踪的应用需要一个过程，该过程可以识别特征并输出置信分数，代表该功能是由船只生成的可能性，该功能可能触发后续警报或激活分类系统。但是，海事环境提出了独特的挑战，例如波浪趋势产生大多数事件，要求大多数计算处理并产生假阳性检测。通过过滤冗余事件并分析每个事件群集的运动，我们可以识别和跟踪血管，同时忽略较短的寿命和不稳定的特征，例如波浪产生的功能。
Event cameras are ideal for object tracking applications due to their ability to capture fast-moving objects while mitigating latency and data redundancy. Existing event-based clustering and feature tracking approaches for surveillance and object detection work well in the majority of cases, but fall short in a maritime environment. Our application of maritime vessel detection and tracking requires a process that can identify features and output a confidence score representing the likelihood that the feature was produced by a vessel, which may trigger a subsequent alert or activate a classification system. However, the maritime environment presents unique challenges such as the tendency of waves to produce the majority of events, demanding the majority of computational processing and producing false positive detections. By filtering redundant events and analyzing the movement of each event cluster, we can identify and track vessels while ignoring shorter lived and erratic features such as those produced by waves.
