A note on the convergence of the mean shift

DOI10.1016/j.patcog.2006.10.016zbMath1111.68111OpenAlexW2102013325WikidataQ30048124 ScholiaQ30048124MaRDI QIDQ877126

Xiangru Li, Fuchao Wu, Zhanyi Hu

Publication date: 19 April 2007

Published in: Pattern Recognition (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.patcog.2006.10.016

zbMATH Keywords

convergencecomputer visionlocal structuremean shift

Mathematics Subject Classification ID

Nonnumerical algorithms (68W05) Pattern recognition, speech recognition (68T10) Machine vision and scene understanding (68T45)

Related Items (14)

A mean-shift algorithm for large-scale planar maximal covering location problems ⋮ Design of blurring mean-shift algorithms for data classification ⋮ On some convergence properties of the subspace constrained mean shift ⋮ Analyzing animal escape data with circular nonparametric multimodal regression ⋮ On the weak convergence and central limit theorem of blurring and nonblurring processes with application to robust location estimation ⋮ The mean shift algorithm and its relation to kernel regression ⋮ Mixture model modal clustering ⋮ On the convergence and consistency of the blurring mean-shift process ⋮ A sufficient condition for the convergence of the mean shift algorithm with Gaussian kernel ⋮ Unnamed Item ⋮ Modified subspace constrained mean shift algorithm ⋮ Smoothing three-dimensional manifold data, with application to tectonic fault detection ⋮ Unnamed Item ⋮ A class of nonparametric mode estimators

Cites Work

• The estimation of the gradient of a density function, with applications in pattern recognition
• Computer Vision - ECCV 2004

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