Title:
An-Improved-Mean-Shift-Algorithm
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Description: The traditional Mean Shift tracking algorithm partitions uniformly the whole color space，leading to a great
number of void histogram bins，and is unable to represent accurately the color distribution of the object．To address
the problems，we present an improved algorithm．Firstly the object color is analyzed using a clustering algorithm，and
according to the clustering result the color space of the object is partitioned into subspaces by matrix factorization and
orthonormal transformation．Then a new color model is defined by considering the weighted number of pixels as well as
within—cluster distribution with Gaussian ．and a novel measure iS derived to evaluate the similarity between the reference
color model and the candidate mode1．Finally an improved algorithm is proposed based on the color mode1．Experiments
show that the improved algorithm has better performance than and is computationally comparable to the conventional
mean shift algorithm．
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一种改进的MEAN SHIFT跟踪算法.PDF
