Abstract
Automatic detecting and tracking the objects from UAV videos is very important and challenging for both tactical and security applications. We present a robust object tracking system that is able to track multiple objects robustly in UAV videos. The main characteristics of the proposed system include: (1)A novel feature clustering based multiple objects tracking framework is proposed, which performs much better than the traditional foreground-blob-tracking-based methods. (2)Optical flow features are clustered both in spatial and temporal dimension to track multiple objects robustly even in the case of multiple objects cross moving. Extensive experimental results with quantitative and qualitative analysis demonstrate the robustness and effectiveness of our algorithm.
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Tong, X., Zhang, Y., Yang, T., Ma, W. (2013). Automatic Object Tracking in Aerial Videos via Spatial-temporal Feature Clustering. In: Sun, C., Fang, F., Zhou, ZH., Yang, W., Liu, ZY. (eds) Intelligence Science and Big Data Engineering. IScIDE 2013. Lecture Notes in Computer Science, vol 8261. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-42057-3_11
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DOI: https://doi.org/10.1007/978-3-642-42057-3_11
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-42056-6
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