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Issue No.03 - March (2005 vol.27)
pp: 471-474
ABSTRACT
We build on the current understanding of mean shift as an optimization procedure. We demonstrate that, in the case of piecewise constant kernels, mean shift is equivalent to Newton's method. Further, we prove that, for all kernels, the mean shift procedure is a quadratic bound maximization.
INDEX TERMS
Mean shift, bound optimization, Newton's method, adaptive gradient descent, mode seeking.
CITATION
Mark Fashing, Carlo Tomasi, "Mean Shift Is a Bound Optimization", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol.27, no. 3, pp. 471-474, March 2005, doi:10.1109/TPAMI.2005.59
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