Abstract
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.
Supported by national key laboratory (51476010105HK0101).
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Zhang, H., Yuan, F. (2007). Vehicle Tracking Based on Image Alignment in Aerial Videos. In: Yuille, A.L., Zhu, SC., Cremers, D., Wang, Y. (eds) Energy Minimization Methods in Computer Vision and Pattern Recognition. EMMCVPR 2007. Lecture Notes in Computer Science, vol 4679. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74198-5_23
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DOI: https://doi.org/10.1007/978-3-540-74198-5_23
Publisher Name: Springer, Berlin, Heidelberg
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