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CVPR
2009
IEEE
16 years 4 months ago
Stochastic Gradient Kernel Density Mode-Seeking
As a well known fixed-point iteration algorithm for kernel density mode-seeking, Mean-Shift has attracted wide attention in pattern recognition field. To date, Mean-Shift algorit...
Xiaotong Yuan, Stan Z. Li
ICIP
2009
IEEE
14 years 7 months ago
A novel two-tier Bayesian based method for hair segmentation
In this paper, a novel two-tier Bayesian based method is proposed for hair segmentation. In the first tier, we construct a Bayesian model by integrating hair occurrence prior prob...
Dan Wang, Shiguang Shan, Wei Zeng, Hongming Zhang,...
ECCV
2008
Springer
15 years 11 months ago
Quick Shift and Kernel Methods for Mode Seeking
We show that the complexity of the recently introduced medoid-shift algorithm in clustering N points is O(N2 ), with a small constant, if the underlying distance is Euclidean. This...
Andrea Vedaldi, Stefano Soatto
PR
2007
293views more  PR 2007»
14 years 9 months ago
Mean shift-based clustering
In this paper, a mean shift-based clustering algorithm is proposed. The mean shift is a kernel-type weighted mean procedure. Herein, we first discuss three classes of Gaussian, C...
Kuo-Lung Wu, Miin-Shen Yang
CVPR
2008
IEEE
15 years 11 months ago
Generalised blurring mean-shift algorithms for nonparametric clustering
Gaussian blurring mean-shift (GBMS) is a nonparametric clustering algorithm, having a single bandwidth parameter that controls the number of clusters. The algorithm iteratively sh...
Miguel Á. Carreira-Perpiñán