Detecting independently moving objects and their interactions in georeferenced airborne video

In airborne video, objects are tracked from a moving camera and often imaged at very low resolution. The camera movement makes it difficult to determine whether or not an object is in motion; the low-resolution imagery makes it difficult to classify the objects and their activities. When comparable, the object's georeferenced trajectory contains useful information for the solution of both of these problems. We describe a novel technique for detecting independent movement by analyzing georeferenced object motion relative to the trajectory of the camera. The method is demonstrated on over a hundred objects and parallax artifacts, and its performance is analyzed relative to difficult object behavior and camera model errors. We also describe a new method for classifying objects and events using features of georeferenced trajectories, such as duration of acceleration, measured at key phases of the events. These features, combined with the periodicity of the image motion, are successfully used classify events in the domain of person-vehicle interactions.