提交 b769639f 编写于 作者: G Gary Bradski

Docs for using BRIEF in features2d

上级 d0d7ba99
......@@ -15,6 +15,16 @@ using std::cerr;
using std::endl;
using std::vector;
void help(char **av)
{
cerr << "usage: " << av[0] << " im1.jpg im2.jpg"
<< "\n"
<< "This program shows how to use brief to match points in features2d\n"
<< "It takes in two images, finds keypoints and matches them displaying matches and final homography warped results\n"
<< endl;
}
//Copy (x,y) location of descriptor matches found from KeyPoint data structures into Point2f vectors
void matches2points(const vector<DMatch>& matches, const vector<KeyPoint>& kpts_train,
const vector<KeyPoint>& kpts_query, vector<Point2f>& pts_train, vector<Point2f>& pts_query)
{
......@@ -36,15 +46,17 @@ float match(const vector<KeyPoint>& kpts_train, const vector<KeyPoint>& kpts_que
{
float t = (double)getTickCount();
matcher.match(query, train, matches);
matcher.match(query, train, matches); //Using features2d
return ((double)getTickCount() - t) / getTickFrequency();
}
int main(int ac, char ** av)
{
if (ac != 3)
{
cerr << "usage: " << av[0] << " im1.jpg im2.jpg" << endl;
help(av);
return 1;
}
string im1_name, im2_name;
......@@ -63,7 +75,7 @@ int main(int ac, char ** av)
double t = (double)getTickCount();
FastFeatureDetector detector(50);
BriefDescriptorExtractor extractor(32);
BriefDescriptorExtractor extractor(32); //this is really 32 x 8 matches since they are binary matches packed into bytes
vector<KeyPoint> kpts_1, kpts_2;
detector.detect(im1, kpts_1);
......@@ -87,6 +99,7 @@ int main(int ac, char ** av)
cout << "done computing descriptors... took " << t << " seconds" << endl;
//Do matching with 2 methods using features2d
cout << "matching with BruteForceMatcher<HammingLUT>" << endl;
BruteForceMatcher<HammingLUT> matcher;
vector<DMatch> matches_lut;
......@@ -100,7 +113,7 @@ int main(int ac, char ** av)
cout << "done BruteForceMatcher<Hamming> matching. took " << pop_time << " seconds" << endl;
vector<Point2f> mpts_1, mpts_2;
matches2points(matches_popcount, kpts_1, kpts_2, mpts_1, mpts_2);
matches2points(matches_popcount, kpts_1, kpts_2, mpts_1, mpts_2); //Extract a list of the (x,y) location of the matches
vector<uchar> outlier_mask;
Mat H = findHomography(Mat(mpts_2), Mat(mpts_1), outlier_mask, RANSAC, 1);
......
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