Abstract
In this paper, we propose an effective tracker for infrared videos based on the multi-cue fusion. Under the particle filter tracking construction, a novel feature scoring scheme is introduced to evaluate different cue tracking ability, then the multi-cue fusion is executed in a weighted sum manner. In our tracking system, the score of each feature can be adaptively updated according to the current environment. Experimental results with various Infrared Video Database and different trackers are reported to demonstrate the accuracy and robustness of our algorithm.
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© 2013 Springer-Verlag Berlin Heidelberg
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Wang, J., Chen, D., Li, S., Yang, Y. (2013). Feature-Scoring-Based Multi-cue Infrared Object Tracking. In: Yang, J., Fang, F., Sun, C. (eds) Intelligent Science and Intelligent Data Engineering. IScIDE 2012. Lecture Notes in Computer Science, vol 7751. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36669-7_4
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DOI: https://doi.org/10.1007/978-3-642-36669-7_4
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-36668-0
Online ISBN: 978-3-642-36669-7
eBook Packages: Computer ScienceComputer Science (R0)