feature-descriptor

I'm trying to calculate the distance (Euclidean or hamming) between two descriptors already calculated. The problem is I don't want to use a matcher, I just want to calculate the distance between two descriptors. I'm using OpenCV 2.4.9 and i have mine descriptors stored in a Mat type: Mat descriptors1; Mat descriptors2; and now i just want to calculate the distance (preferably the Hamming distance since I'm using binary descriptors) between row1 of descriptors1 and row1 of descriptors2 (for example). I have tried to use bitwise_xor() function but then I got not an effective way of doing the

I'm trying the assess the correctness of my SURF descriptor implementation with the de facto standard framework by Mikolajczyk et. al . I'm using OpenCV to detect and describe SURF features, and use the same feature positions as input to my descriptor implementation. To evaluate descriptor performance, the framework requires to evaluate detector repeatability first. Unfortunately, the repeatability test expects a list of feature positions along with ellipse parameters defining the size and orientation of an image region around each feature. However, OpenCV's SURF detector only provides feature

I've implement a Robust matcher found on the internet based on differents tests : symmetry test, Ratio Test and RANSAC test. It works well. I used then findHomography in order to have good matches. Here the code : RobustMatcher::RobustMatcher() : ratio(0.65f), refineF(true),confidence(0.99), distance(3.0) { detector = new cv::SurfFeatureDetector(400); //Better than ORB //detector = new cv::SiftFeatureDetector; //Better than ORB //extractor= new cv::OrbDescriptorExtractor(); //extractor= new cv::SiftDescriptorExtractor; extractor= new cv::SurfDescriptorExtractor; // matcher= new cv:

I am trying to understand how to get the descriptor for a given KeyPoint in OpenCV. So far my code looks like follows: #include <iostream> #include "opencv2/opencv.hpp" typedef cv::Mat Image; int main(int argc, const char * argv[]) { Image imgA = cv::imread("images/buddhamulticam_total100.png", CV_LOAD_IMAGE_GRAYSCALE); Image imgB = cv::imread("images/buddhamulticam_total101.png", CV_LOAD_IMAGE_GRAYSCALE); cv::Ptr<cv::FeatureDetector> detector = cv::FeatureDetector::create("ORB"); cv::Ptr<cv::DescriptorExtractor> descriptor = cv::DescriptorExtractor::create("ORB"); std::vector<cv::KeyPoint>

I'm currently using OpenCV's ORB features extractor and I did notice the strange (at least for me) way the ORB-descriptor is stored (it is basically a BRIEF-32 with a modification that is not relevant to my question). As some of you know ORB takes the keypoints extracted using a modified FAST-9 (circle radius = 9 pixels; also stores orientation of the keypoint) and uses those with a modified BRIEF-32 descriptor to store the feature that the keypoint represents. BRIEF (ORB version) works as follows: we take a 31x31 pixels patch (represents a feature) and create a bunch of random 5x5 pixels test