The keypoints are clustered into 5,000 visual codewords ( centroids ) using k-means clustering ( Sculley , 2010 ) , and images are then quantized over the 5,000 codewords .
webscale kmeans clustering
D Sculley
We compute SURF keypoints for every image in our data set using SimpleCV3 and randomly sample 1 % of the keypoints . The keypoints are clustered into 5,000 visual codewords ( centroids ) using k-means clustering ( Sculley , 2010 ) , and images are then quantized over the 5,000 codewords . All images for a given word are summed together to provide an average representation for the word .
The keypoints are clustered into 5,000 visual codewords ( centroids ) using k-means clustering ( @@CITATION ) , and images are then quantized over the 5,000 codewords .