Abstract
In this paper, we propose a mean-shift tracking method by using the novel back-projection calculation. The traditional back-projection calculation methods have two main drawbacks: either they are prone to be disturbed by the background when calculating the histogram of target-region, or they only consider the importance of a pixel relative to other pixels when calculating the back-projection of search-region. In order to solve the two drawbacks, we carefully consider the background appearance based on two priors, i.e., texture information of background, and appearance difference between foreground-target and background. Accordingly, our method consists of two basic steps. First, we present a foreground-target histogram approximation method to effectively reduce the disturbance from background. Moreover, the foreground-target histogram is used for back-projection calculation instead of the target-region histogram. Second, a novel back-projection calculation method is proposed by emphasizing the probability that a pixel belongs to the foreground-target. Experiments show that our method is suitable for various tracking scenes and is appealing with respect to robustness.
This research is sponsored by Natural Science Foundation of China(NSFC No. 60675012)
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Wang, L., Wu, H., Pan, C. (2010). Mean-Shift Object Tracking with a Novel Back-Projection Calculation Method. In: Zha, H., Taniguchi, Ri., Maybank, S. (eds) Computer Vision – ACCV 2009. ACCV 2009. Lecture Notes in Computer Science, vol 5994. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12307-8_8
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DOI: https://doi.org/10.1007/978-3-642-12307-8_8
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