CSDL Home IEEE Transactions on Pattern Analysis & Machine Intelligence 2005 vol.27 Issue No.03 - March
Issue No.03 - March (2005 vol.27)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TPAMI.2005.59
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.
Mean shift, bound optimization, Newton's method, adaptive gradient descent, mode seeking.
Mark Fashing, "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