Moving object verification from airborne video

This paper presents an end-to-end verification system for moving objects in airborne video. Lacking prior training data, the object information is collected on the fly from a short real-time learning sequence. Using a sample selection module, the system selects samples from the learning sequence and stores them in an exemplar database. To handle appearance change due to potentially large aspect angle variations, a homography-based view synthesis method is used to generate a novel view of each image in the exemplar database at the same pose as the query object in each frame of a query sequence. A spatial match score is obtained using a Distance Transform to compare the novel view and query object. After looping over all query frames, the set of match scores is passed to a temporal analysis module to examine the behavior of the query object, and calculate a final likelihood. Very good verification performance is achieved over thousands of trials for both color and infrared video sequences using the proposed system.