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» Mean Shift Analysis and Applications
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ICCV
2009
IEEE
1556views Computer Vision» more  ICCV 2009»
15 years 18 days ago
Kernel Methods for Weakly Supervised Mean Shift Clustering
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...
Oncel Tuzel, Fatih Porikli, Peter Meer
ICTAI
2006
IEEE
14 years 1 months ago
An Approximation to Mean-Shift via Swarm Intelligence
Mean shift based feature space analysis has been shown to be an elegant, accurate and robust technique. The elegance in this non-parametric algorithm is mainly due to its simplici...
Mani Thomas, Chandra Kambhamettu
SDM
2009
SIAM
193views Data Mining» more  SDM 2009»
14 years 4 months ago
Agglomerative Mean-Shift Clustering via Query Set Compression.
Mean-Shift (MS) is a powerful non-parametric clustering method. Although good accuracy can be achieved, its computational cost is particularly expensive even on moderate data sets...
Xiaotong Yuan, Bao-Gang Hu, Ran He
ECCV
2008
Springer
14 years 9 months ago
Edge-Preserving Smoothing and Mean-Shift Segmentation of Video Streams
Video streams are ubiquitous in applications such as surveillance, games, and live broadcast. Processing and analyzing these data is challenging because algorithms have to be effic...
Sylvain Paris
CVPR
2010
IEEE
1790views Computer Vision» more  CVPR 2010»
14 years 3 months ago
Data Driven Mean-Shift Belief Propagation For non-Gaussian MRFs
We introduce a novel data-driven mean-shift belief propagation (DDMSBP) method for non-Gaussian MRFs, which often arise in computer vision applications. With the aid of scale sp...
Minwoo Park, S. Kashyap, R. Collins, and Y. Liu