Question

I'm working on code that computes dense SIFT features from a set of images, based on SIFT flow: http://people.csail.mit.edu/celiu/SIFTflow/

I'd like to try building a FLANN index on these images by comparing the "energy" between each image in SIFT flow representation.

I have the code to compute the energy from here: http://richardt.name/publications/video-deanaglyph/

Is there a way to create my own distance function for the indexing?

RELATED NOTE:

I was finally able to get an alternate (but not custom) distance function working with flann::Index. The trick is you need to use flann::GenericIndex like so:

flann::GenericIndex<cvflann::ChiSquareDistance<int>> flannIndex(descriptors, cvflann::KDTreeIndexParams());

But you need to give it CV_32S descriptors.

And if you use knnSearch with custom distance function, you have to provide a CV_32S results Mat and CV_32F distances Mat.

Here's my full code in case it's helpful (not a lot of documentation out there):

    Mat samples;
    loadDescriptors(samples); // loading descriptors from .yml file

    samples *= 100000; // scaling up my descriptors to be int
    samples.convertTo(samples, CV_32S); // convert float to int

    // create flann index
    flann::GenericIndex<cvflann::ChiSquareDistance<int>> flannIndex(samples, cvflann::KDTreeIndexParams());
    // NOTE lack of distance type in constructor parameters
    // (unlike flann::index)

    // now try knnSearch 

    int k=10; // find 10 nearest neighbors

    Mat results(1,10,CV_32S), dists(1,10,CV_32F);
    // (1,10) Mats for the output, types CV_32S and CV_32F

    Mat responseHistogram;
    responseHistogram = samples.row(60); 
    // choose a random row from the descriptors Mat
    // to find nearest neighbors

    flannIndex.knnSearch(responseHist, results, dists, k, cvflann::SearchParams(200) );

    cout << results << endl;
    cout << dists << endl;

    flannIndex.save(ofToDataPath("indexChi2.txt"));

Using Chi Squared actually seems to work better for me than L2 distance. My feature vectors are BoW histograms in this case.

Using custom distance function with FLANN or Knn in OpenCv?

0 个答案: