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EE462 MLCV 1 Lecture 3-4 Clustering (1hr) Gaussian Mixture and EM (1hr) Tae-Kyun Kim
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Lecture 3-4 Clustering (1hr) Gaussian Mixture and EM (1hr)

Jan 01, 2016

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Lecture 3-4 Clustering (1hr) Gaussian Mixture and EM (1hr). Tae-Kyun Kim. Vector Clustering. Pixel Clustering (Image Quantisation). R G B. ``. Patch Clustering. or raw pixels. …. dimension D. ……. ……. K codewords. …. Refer to Lecture 9-10 for BoW. Image Clustering. ……. - PowerPoint PPT Presentation
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Page 1: Lecture 3-4 Clustering (1hr) Gaussian Mixture and EM (1hr)

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Lecture 3-4Clustering (1hr)Gaussian Mixture and EM (1hr)

Tae-Kyun Kim

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Vector Clustering

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``

RGB

Pixel Clustering (Image Quantisation)

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dim

ensi

on

D…

……

……

or raw pixels

K codewords

Patch Clustering

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Refer to Lecture 9-10 for BoW

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……

Image Clustering

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K-means vs GMM

Hard clustering

Soft clustering

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Matrix and Vector Derivatives

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K-means Clustering

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Statistical Pattern Recognition Toolbox for Matlab

http://cmp.felk.cvut.cz/cmp/software/stprtool/

…\stprtool\probab\cmeans.m…\stprtool\probab\cmeans_tk.m

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Mixture of Gaussians

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Maximum Likelihood

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Statistical Pattern Recognition Toolbox for Matlab

http://cmp.felk.cvut.cz/cmp/software/stprtool/

…\stprtool\visual\pgmm.m…\stprtool\demos\demo_emgmm.m

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Advanced topic (optional)

http://www.iis.ee.ic.ac.uk/~tkkim/mlcv/lecture_clustering_em.pdf

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EM Algorithm in General

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