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» Mean shift based nonparametric motion characterization
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ICCV
2003
IEEE
14 years 8 months ago
Mean Shift Based Clustering in High Dimensions: A Texture Classification Example
Feature space analysis is the main module in many computer vision tasks. The most popular technique, k-means clustering, however, has two inherent limitations: the clusters are co...
Bogdan Georgescu, Ilan Shimshoni, Peter Meer
ACCV
2009
Springer
14 years 1 months ago
Evolving Mean Shift with Adaptive Bandwidth: A Fast and Noise Robust Approach
Abstract. This paper presents a novel nonparametric clustering algorithm called evolving mean shift (EMS) algorithm. The algorithm iteratively shrinks a dataset and generates well ...
Qi Zhao, Zhi Yang, Hai Tao, Wentai Liu
CVPR
2009
IEEE
15 years 2 months ago
Intrinsic Mean Shift for Clustering on Stiefel and Grassmann Manifolds
The mean shift algorithm, which is a nonparametric density estimator for detecting the modes of a distribution on a Euclidean space, was recently extended to operate on analytic ...
Hasan Ertan Çetingül, René Vida...
ICCV
2009
IEEE
14 years 12 months ago
Subspace Constrained Mean-Shift
Deformable model fitting has been actively pursued in the computer vision community for over a decade. As a result, numerous approaches have been proposed with varying degrees of...
Jason M. Saragih, Simon Lucey, Jeffrey F. Cohn
CVPR
2005
IEEE
14 years 9 months ago
Efficient Mean-Shift Tracking via a New Similarity Measure
The mean shift algorithm has achieved considerable success in object tracking due to its simplicity and robustness. It finds local minima of a similarity measure between the color...
Changjiang Yang, Ramani Duraiswami, Larry S. Davis