How to use flann based matcher, or generally flann in opencv?

Question

http://opencv.willowgarage.com/documentation/cpp/features2d_common_interfaces_of_descriptor_matchers.html#flannbasedmatcher

Please can somebody show me sample code o

Answer 1

Here's untested sample code

using namespace std;
using namespace cv;

Mat query; //the query image
vector<Mat> images;   //set of images in your db

/* ... get the images from somewhere   ... */

vector<vector<KeyPoint> > dbKeypoints;
vector<Mat> dbDescriptors;

vector<KeyPoint> queryKeypoints;
Mat queryDescriptors;

/* ... Extract the descriptors ... */

FlannBasedMatcher flannmatcher;

//train with descriptors from your db
 flannmatcher.add(dbDescriptors);
 flannmatcher.train();

vector<DMatch > matches;

flannmatcher.match(queryDescriptors, matches);

/* for kk=0 to matches.size()

       the best match for queryKeypoints[matches[kk].queryIdx].pt 
       is dbKeypoints[matches[kk].imgIdx][matches[kk].trainIdx].pt

 */

Finding the most 'similar' image to the query image depends on your application. Perhaps the number of matched keypoints is adequate. Or you may need a more complex measure of similarity.

Answer 2

To reduce the number of false positives, you can compare the first most nearest neighbor to the second most nearest neighbor by taking the ratio of there distances. distance(query,mostnearestneighbor)/distance(query,secondnearestneighbor) < T, the smaller the ratio is, the higher the distance of the second nearest neighbor to the query descriptor. This thus is a translation of high distinctiveness. Used in many computer vision papers that envision registration.