The recently proposed color based tracking systems are unable to properly adapt the ellipse that represents an object to be tracked. This most likely leads to inaccurate descriptions of the object in the later application. This paper presents a Lagrangian based method in order to discover a regularizing component for the covariance matrix. Technically, we intend to reduce the residuals between the estimated probability distribution and the expected one. We argue that, by doing this, the shape of the ellipse can be properly adapted in the tracking stage. Experimental results show that the proposed method has favorable performance in shape adaption and object localization.

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References

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