How to draw detected object with SIFT features on OpenCV 3.1? - c++

Question

Using this code to find matches between images:
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/xfeatures2d/nonfree.hpp>
#include <opencv2/xfeatures2d.hpp>
#include <vector>
using namespace std;
using namespace cv;
int main(int argc, char *argv[]) {
//cv::initModule_nonfree();
//initModule_features2d();
Mat img_1 = imread("C:/Users/Dan/Desktop/0.jpg", 1);
Mat img_2 = imread("C:/Users/Dan/Desktop/0.jpg", 1);
cv::Ptr<Feature2D> f2d = xfeatures2d::SIFT::create();
//-- Step 1: Detect the keypoints:
std::vector<KeyPoint> keypoints_1, keypoints_2;
f2d->detect(img_1, keypoints_1);
f2d->detect(img_2, keypoints_2);
//-- Step 2: Calculate descriptors (feature vectors)
Mat descriptors_1, descriptors_2;
f2d->compute(img_1, keypoints_1, descriptors_1);
f2d->compute(img_2, keypoints_2, descriptors_2);
Mat out0;
drawKeypoints(img_1, keypoints_1, out0);
imshow("KeyPoint0.jpg", out0);
//-- Step 3: Matching descriptor vectors using BFMatcher :
BFMatcher matcher;
std::vector< DMatch > matches;
matcher.match(descriptors_1, descriptors_2, matches);
Mat img_matches = Mat::zeros( img_1.size(), CV_8UC3 );
drawMatches(img_1,keypoints_1,img_2,keypoints_2,matches,img_matches);
imshow("matches", img_matches);
waitKey(0); // Keep window there until user presses 'q' to quit.
return 0;
}
Since OpenCV 3.1 functions were changed, I looked for example code using SURF or SIFT, but could not find any.
How to modify this code so it will draw contours around detected objects similar to OpenCV version?

Answer 1

You will need to use findHomography to get the transformation that relates your training image (img_1) to the image to be detected (img_2)
Then you can simply do a perspectiveTransform on a bounding box of your training image (at origin) using the homography obtained, to place the correct bounding box on the detected image
Related code taken from ORB detection example
Mat inlier_mask, homography;
vector<KeyPoint> inliers1, inliers2;
vector<DMatch> inlier_matches;
if(matched1.size() >= 4) {
homography = findHomography(Points(matched1), Points(matched2),
RANSAC, ransac_thresh, inlier_mask);
}
for(unsigned i = 0; i < matched1.size(); i++) {
if(inlier_mask.at<uchar>(i)) {
int new_i = static_cast<int>(inliers1.size());
inliers1.push_back(matched1[i]);
inliers2.push_back(matched2[i]);
inlier_matches.push_back(DMatch(new_i, new_i, 0));
}
}
stats.inliers = (int)inliers1.size();
stats.ratio = stats.inliers * 1.0 / stats.matches;
vector<Point2f> new_bb;
perspectiveTransform(object_bb, new_bb, homography);
Mat frame_with_bb = frame.clone();
if(stats.inliers >= bb_min_inliers) {
drawBoundingBox(frame_with_bb, new_bb);
}
Mat res;
drawMatches(first_frame, inliers1, frame_with_bb, inliers2,
inlier_matches, res,
Scalar(255, 0, 0), Scalar(255, 0, 0));