What happens if there's not enough key points to match?

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@FooBar, can you please explain more about your c options? It sounds good for me. I looked at FlannBasedMatcher but I could not find a way to add constraints.

To use this option, you don't use the FlannBasedMatcher directly (I've never used it, so I'm not sure how it works exactly), but you use the underlying flann-class directly:

http://docs.opencv.org/modules/flann/...

You insert all of your training descriptors into the flann-structure and then you call knnsearch for each query descriptor with k=2 so that flann gives you the two most similiar descriptors. Here is a piece of code that could guide you a bit:

http://find-object.googlecode.com/svn... (but be careful, this is old c-Api code, so just get the idea and don't use the old iplImage and cv* functions)

To complete the previous answer, to retrieve the k-best matches for a query keypoints, you could either use a brute force approach or the Flann method in OpenCV. The Flann approach compared to the brute foce method will be significantly faster wehn dealing with big training / query sets (it uses an efficient structure to store the data) but it is an approximation. The two approaches:

cv::Ptr<cv::DescriptorMatcher> matcher = cv::DescriptorMatcher::create("BruteForce"); //or FlannBased
std::vector<std::vector<cv::DMatch> > matches;
matcher->knnMatch(queryDescriptors, trainDescriptors, matches, 2);