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» Mean shift based nonparametric motion characterization
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ICCV
2003
IEEE
14 years 7 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
13 years 12 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 14 days 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 10 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 7 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