问题
I need to do BOW (bag of words) but I only have the described keypoints of the images. For the moment, I have obtained the vocabulary using:
cv::BOWKMeansTrainer bowtrainerCN(numCenters); //num clusters
bowtrainerCN.add(allDescriptors);
cv::Mat vocabularyCN = bowtrainerCN.cluster();
So now I need to do the assignment but I can't use the compute function because it calculates the descriptors of the images and I already have that. Is there any function to do the assignment or have I to compute it manually?
回答1:
Once you have built the vocabulary (codebook) using cv::BOWKMeansTrainer::cluster()
method, you can then match a descriptor (with suitable size and type) to the codebook. You first have to choose the type of matcher you need with a norm to use. (see opencv doc)
For example, with cv::BFMatcher
and L2 norm
// init the matcher with you pre-trained codebook
cv::Ptr<cv::DescriptorMatcher > matcher = new cv::BFMatcher(cv::NORM_L2);
matcher->add(std::vector<cv::Mat>(1, vocabulary));
// matches
std::vector<cv::DMatch> matches;
matcher->match(new_descriptors,matches);
Then the index of the closest codeword in your codebook for the new_descriptors[i] will be
matches[i].trainIdx;
来源:https://stackoverflow.com/questions/15611872/bow-in-opencv-using-precomputed-features