Aerial monitoring of ground sites using video cameras is playing an increasingly important role in autonomous surveillance applications. In such tasks it is important to be able to relate the activities detected in the video sequence to the 3D world, typically represented by a map, orthoimage or site model. Traditional image positioning approaches are generally not applicable to the real-time processing of (typically) low-resolution aerial video. The paper presents an approach to the automatic registration of aerial video to a site model. Low precision metadata are used to initialize the registration, and the resulting registration error is modeled as a simple translational shift. An operator-selected site feature is automatically tracked using frame stabilization parameters, and in each frame the registration error is corrected using the discrepancy between the metadata-predicted and tracked feature locations. This system runs on a PC in real time using less than 2% of the CPU. It has been demonstrated on real data obtained live during several flight experiments.
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