12 search results - page 2 / 3 » Kernel Methods for Weakly Supervised Mean Shift Clustering |
ECCV
2002
Springer
14 years 7 months ago
2002
Springer
Abstract. Two new techniques based on nonparametric estimation of probability densities are introduced which improve on the performance of equivalent robust methods currently emplo...
CVPR
2005
IEEE
14 years 7 months ago
2005
IEEE
Nearest neighborhood consistency is an important concept in statistical pattern recognition, which underlies the well-known k-nearest neighbor method. In this paper, we combine th...
CVPR
2008
IEEE
14 years 7 months ago
2008
IEEE
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...
ICPR
2006
IEEE
14 years 6 months ago
2006
IEEE
In this paper, a novel unsupervised approach for the segmentation of unorganized 3D points sets is proposed. The method derives by the mean shift clustering paradigm devoted to se...
ICANN
2009
Springer
13 years 10 months ago
2009
Springer
Kernel density estimation (KDE) has been used in many computational intelligence and computer vision applications. In this paper we propose a Bayesian estimation method for findin...