Can OpenCV's mean shift implementation be used for finding local maxima in data, rather than tracking or detection?

optimization

asked 2012-09-25 16:04:04 -0600

harddrive
31 ●2

I want to use mean shift to find all of the local maxima above some threshold value. However, I'm not sure if OpenCV's implementation is adaptable in this way. So the question is simple: is it? And if it is, how can it be used for that purpose?

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answered 2012-09-26 02:38:35 -0600

elmiguelao

275 ●6

Tentatively, there is the openCV method for finding k-means for an arbitrary set of points, but you would need to know how many clusters you want to find, and there could be convergence issues depending on how the data is spread and how the algorithm (iterative) starts. So it might be of no help to you ;)

I found this image condenses completely the tons of k-means mathematical theory :) (from http://www.cs.cmu.edu/~dpelleg/kmeans.html) :

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Interesting. I am aware of the k-means implementation but I was thinking of mean-shift for determining collecting svm responses. I suppose k-means is an option too but it's tough to know beforehand how many positive responses would be made by the svm.