What is the most efficient way to obtain the centroid of each cluster of centroids in the matrix produced by 'kmeans' cluster analysis?
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I am counting geese in large flocks in aerial photos using the 'detectSURFFeatures' function to identify individual geese. This gives me multiple feature centroids clustered at each goose image, which I analyze with 'kmeans'. I am currently sorting the resulting matrix of centroid values on cluster labels and using loops to calculate the mean centroid value for each cluster (see attached code).
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Image Analyst
2016-12-3
The most efficient way would be to get the second return argument of kmeans(). I mean, it gives you the cluster centers so why not accept them?
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