Abstract
A simple and elegant tracking algorithm called Centroid Iteration algorithm is proposed. It employs a new Background-Weighted similarity measure which can greatly reduce the influence from the pixels shared by the target template and background on localization. Experiments demonstrated the Background-Weighted measure performs much better than the other similarity measures like Kullback–Leibler divergence, Bhattacharyya coefficient and so on. It has been proved that this measure can compute the similarity value contribution of each pixel in the target candidate, based on which, a new target search method called Centroid Iteration is constructed. The convergence of the method has been demonstrated. Theory analysis and visual experiments both validated the new algorithm.
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Acknowledgments
The paper is supported by National Natural Science Foundation of China under Grant Nos. 61105034 and 60905044, Research Fund for the Doctoral Program of Higher Education of China under Grant No. 20100201120040.
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Lu, N., Feng, Z. Centroid Iteration algorithm for image tracking. Pattern Anal Applic 15, 163–174 (2012). https://doi.org/10.1007/s10044-011-0252-8
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DOI: https://doi.org/10.1007/s10044-011-0252-8