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CVPR
2009
IEEE
14 years 12 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
13 years 2 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
14 years 6 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»
13 years 4 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
14 years 6 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