12 search results - page 1 / 3 » Kernel Methods for Weakly Supervised Mean Shift Clustering |
ICCV
2009
IEEE
14 years 9 months ago
2009
IEEE
Mean shift clustering is a powerful unsupervised data
analysis technique which does not require prior knowledge
of the number of clusters, and does not constrain the shape
of th...
ECCV
2008
Springer
14 years 6 months ago
2008
Springer
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...
PAMI
2007
13 years 4 months ago
2007
The mean-shift algorithm, based on ideas proposed by Fukunaga and Hostetler (1975), is a hill-climbing algorithm on the density defined by a finite mixture or a kernel density e...
PR
2007
13 years 4 months ago
2007
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...
ICPR
2008
IEEE
14 years 5 months ago
2008
IEEE
In kernel density estimation methods, an approximation of the data probability density function is achieved by locating a kernel function at each data location. The smoothness of ...