I have about 130,000 SIFT descriptors. I am building a hierarchical Kmeans-index using Opencv's flann module. After this I want to quantize these 130,000 descriptors (will quantize more later). I am using flann's knnsearch method for doing this. But the result of this method is something weird. For every descriptor the nearest index it is showing is the index of the descriptor itself. However, it should be displaying the cluster-ID of the nearest cluster which will be one of the leaves of the HIK-tree.
Should I try k=2
Here is a code snippet -
int k=1;
cv::flann::KMeansIndexParams indexParams(8,4,cvflann::FLANN_CENTERS_KMEANSPP) ;
cv::flann::Index hik_tree(cluster_data, indexParams);
Mat indices,dist;
hik_tree.knnSearch(cluster_data, indices, dist, k, cv::flann::SearchParams(64));