Vehicle Tracking Based on Image Alignment in Aerial Videos

Ground vehicle tracking is an important component of Aerial Video Surveillance System (AVS). We address the problem of real-time and precise vehicle tracking from a single moving airborne camera which faces the challenges of congestion, occlusion and so on. We track a set of point features of the selected vehicle by the technique of image alignment. An edge feature-based outlier rejection criterion is proposed to eliminate the outlier caused by congestion and occlusion. Large motion and total occlusion is handled by a Kalman filter. Furthermore, a reappearance verification program is used to ensure the tracker gets back the right object. Experimental results on real aerial videos show the algorithm is reliable and robust.

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