This paper describes the continuing development of a system for tracking multiple man made objects, (typically vehicles) moving in a natural open world scene, where the detected motion is used to construct a structural representation of the scene. The system assumes no a priori knowledge of any structure within the image, but begins building a map of the scene on a frame by frame basis. The map shows regions in the image where vehicles are likely to be detected and regions where they are likely to become occluded. Tracking is complicated by the fact that the vehicles to be tracked are expected to be a large distance from the camera and as such will only occupy a small number of image pixels. The system has been tested using an input sequence of vehicles moving in a complex outdoor scene, where the vehicles undergo both full and partial occlusion.
This paper describes part of an imaging system to indicate possible collision situations between maritime vessels. History shows us that any collision involving a marine craft can have a devastating effect both on human life and the environment. Presented here is a method for the statistical characterization of the sea present in an image and the subsequent segmentation of the image into two regions, sea and object. The characterization process uses statistical measures on histogram data collectedfrom various regions of the image. This leads to a characteristic grey-level range that represents the 'sea ' . The grey-level statistics are then used to segment the image into regions that contain sea. The methods introduced here have been shown to work well with images containing difering sized objects with differing sea conditions and levels of illumination.
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