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2018-10-21 20:58:20 -0600 received badge  Enthusiast
2018-10-16 20:39:45 -0600 asked a question GPU SURF : What is the keypointsRatio parameter?

GPU SURF : What is the keypointsRatio parameter? What does the "keypointsRatio" parameter in GPU SURF mean? https://doc

2016-10-24 02:23:17 -0600 commented question OpenCV : Running FLANN on a cluster

@berak , thank you .but isnt FlannBasedMatcher use flann::Index under the hood ?

2016-10-24 01:57:16 -0600 asked a question OpenCV : Running FLANN on a cluster

I am trying to scale the "matching_to_many_images.cpp" for large set of images. (20K+ images) https://github.com/kipr/opencv/blob/m...

I use FLANN based matcher to match the images (with SURF keypoint and descriptor extractors).I try follow the method described in this paper (section "Searching on a Compute Cluster") http://www.cs.ubc.ca/research/flann/u... ,

I have a training image set C with total n number of images. C={B(1)...B(n)}. I divide the C into N number of "buckets" where each bucket contains (n/N) number of images. For each bucket I perform "detectKeyPoints" , "computeDescriptors" and "trainMAtcher" separately. This means I have a separate "DescriptorMatcher" for each image bucket.Total N number of DescriptorMatchers.

Then for the query image, I perform "detectKeyPoints","computeDescriptors" and then perform "match" against each of the N DescriptorMatchers. Finally I get list of DMatch objects from each of the "match".

My question is:

1) Am I doing the correct steps according to the paper? I am tryin to understand how the "reduce" step is done as described in the paper.

2) There are two factors I can extract from the DMatch object ; "distance" and "number of total matches per image". How can I use these two factors to find the closest matching image?