image feature file format and mirflickr-sift-fastkmeans-1000000-new.voc file format.

Anonymous
2014-07-01
2014-07-01
  • Anonymous - 2014-07-01

    I want to use the FLANN instead of QuantiserTask class for visual word assignment. I want to know how the data is organized in image feature file xxx.jpg.fv and mirflickr-sift-fastkmeans-1000000-new.voc so that I can read them by C++. Any suggestion?

     
  • Jonathon Hare

    Jonathon Hare - 2014-07-01

    Note all binary numbers are written in Java format (i.e. Big Endian) - if you want to read them in C++ on a little endian machine (i.e. any PC with a x86/64 type processor), you'll need to swap the byte order. The FV files are lists of local features, with the following header structure:

    KPT<numfeatures|int><featureLength|int><features...>
    

    The features are actually dependent on the type of local feature extracted... For DoG/SIFT each one looks like this:

    <x|float><y|float><scale|float><orientation|float><f_1|byte>...<f_featureLength|byte>
    

    The quantiser file format depends on what clustering mode you chose and what precision (byte or int). Assuming you chose KMeans or Fast-KMeans with byte precision (the default), the .voc file has the following format:

    BCen<numClusters|int><featureLength|int><centroid_1_dim_1|byte>...<centroid_1_dim_featureLength|byte><centroid_2_dim_1|byte>...<centroid_2_dim_featureLength|byte>...
    

    I'd be interested to know whether you find FLANN any faster... In theory there shouldn't be much difference as imageterrier is using the same fundamental algorithms for cluster assignment.

     
    Last edit: Jonathon Hare 2014-07-01


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