In order to reduce redundant empty bin capacity arrangement mechanism for mean shift tracking objects in the probability representation, we present a new color feature In the proposed mechanism, the important optimal ...In order to reduce redundant empty bin capacity arrangement mechanism for mean shift tracking objects in the probability representation, we present a new color feature In the proposed mechanism, the important optimal color, or we call it optimal color vector, is clustered by closing Euclidean distance which happens inside the original RGB color 3-D spatial domain. After obtaining clustering colors from the reference image RGB spatial domain, novel clustering groups substitute for original color data. So the new color substitution distribution is as similar as the original one. And then target region in the candidate frame is mapped by the constructed optimal clustering colors and the cluster Indices. In the final, mean shift algorithm gives a performance in the new optimal color distribution. Comparison under the same circumstance between the proposed algorithm and conventional mean shift algorithm shows that the former has a certain advantage in computation cost.展开更多
基金The MKE(the Ministry of Knowledge Economy),Korea,under the ITRC(Information Technology Research Center)support program supervised by the NIPA(National IT Industry Promotion Agency) (NIPA-2012-C1090-1121-0010)The Brain Korea21Project in 2012
文摘In order to reduce redundant empty bin capacity arrangement mechanism for mean shift tracking objects in the probability representation, we present a new color feature In the proposed mechanism, the important optimal color, or we call it optimal color vector, is clustered by closing Euclidean distance which happens inside the original RGB color 3-D spatial domain. After obtaining clustering colors from the reference image RGB spatial domain, novel clustering groups substitute for original color data. So the new color substitution distribution is as similar as the original one. And then target region in the candidate frame is mapped by the constructed optimal clustering colors and the cluster Indices. In the final, mean shift algorithm gives a performance in the new optimal color distribution. Comparison under the same circumstance between the proposed algorithm and conventional mean shift algorithm shows that the former has a certain advantage in computation cost.
