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Small Moving Object Detection and Tracking Based on Event Signals

Detection and tracking small moving objects with high maneuverability, such as drones and missiles, is challenging. In order to detect and track moving objects, the cameras often need to rotate with the movement of the target. When using RGB cameras, problems of motion blur, information redundancy, and highly computational cost occur. The event camera is a new type of camera that only outputs moving target signals by judging the intensity changes of pixel values, reducing data redundancy, and is very suitable for detecting and tracking small objects with high maneuverability. However, when the event camera rotates, the texture edges of the background are also collected, which seriously affects the target object detection. To this end, this paper proposes an event-based moving object detection and tracking method based on registration and foreground enhancement models. Due to the lack of event-based small object detection datasets, we also made a dataset for small object detection. Extensive experiments show that our proposed method can effectively detect small moving object with high maneuverability.