Convergence Analysis of Blurring Mean Shift

arXiv:2402.15146v1 Announce Type: new
Abstract: Blurring mean shift (BMS) algorithm, a variant of the mean shift algorithm, is a kernel-based iterative method for data clustering, where data points are clustered according to their convergent points via iterative blurring. In this paper, we analyze convergence properties of the BMS algorithm by leveraging its interpretation as an optimization procedure, which is known but has been underutilized in existing convergence studies. Whereas existing results on convergence properties applicable to multi-dimensional data only cover …

abstract algorithm analysis analyze arxiv bms clustering convergence cs.cv cs.lg data interpretation iterative kernel mean paper shift type via