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- W2102383321 abstract "Hua et al. have proposed a stable and efficient tracking algorithm called ldquoK-means trackerrdquo[2, 3, 5]. This paper describes an adaptive non-target cluster center selection method that replaces the one used in k-means tracker where non-target cluster center are selected at fixed interval. Non-target cluster centers are selected from the ellipse that defines the area for searching the target object in K-means tracker by checking whether they have significant effects for the pixel classification and are dissimilar to any of the already-selected non-target cluster centers. This ensures that all important non-target cluster centers will be picked up while avoiding selecting redundant non-target clusters. Through comparative experiments of object tracking, we confirmed that both the robustness and the processing speed could be improved with our method." @default.
- W2102383321 created "2016-06-24" @default.
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- W2102383321 date "2008-12-01" @default.
- W2102383321 modified "2023-09-24" @default.
- W2102383321 title "Adaptive selection of non-target cluster centers for K-means tracker" @default.
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- W2102383321 doi "https://doi.org/10.1109/icpr.2008.4761323" @default.
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