Tutorials

doc/tutorials/features2d.tex

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+\ifCpp
+\section{Detection of planar objects}
+The goal of this tutorial is to learn how to use features2d and calib3d modules for detecting known planar objects in scenes. 
+
+\texttt{Test data}: use images in your data folder, for instance, box.png and box\_in\_scene.png. 
+
+Create a new console project. Read two input images. Example:
+\begin{lstlisting}
+Mat img1 = imread(argv[1], CV_LOAD_IMAGE_GRAYSCALE);
+\end{lstlisting}
+
+Detect keypoints in both images. Example:
+\begin{lstlisting}
+// detecting keypoints
+FastFeatureDetector detector(15);
+vector<KeyPoint> keypoints1;
+detector.detect(img1, keypoints1);
+\end{lstlisting}
+
+Compute descriptors for each of the keypoints. Example:
+\begin{lstlisting}
+// computing descriptors
+SurfDescriptorExtractor extractor;
+Mat descriptors1;
+extractor.compute(img1, keypoints1, descriptors1);
+\end{lstlisting}
+
+Now, find the closest matches between descriptors from the first image to the second:
+\begin{lstlisting}
+// matching descriptors
+BruteForceMatcher<L2<float> > matcher;
+vector<DMatch> matches;
+matcher.match(descriptors1, descriptors2, matches);
+\end{lstlisting}
+
+Visualize the results:
+\begin{lstlisting}
+// drawing the results
+namedWindow("matches", 1);
+Mat img_matches;
+drawMatches(img1, keypoints1, img2, keypoints2, matches, img_matches);
+imshow("matches", img_matches);
+waitKey(0);
+\end{lstlisting}
+
+Find the homography transformation between two sets of points:
+\begin{lstlisting}
+vector<Point2f> points1, points2;
+// fill the arrays with the points
+....
+Mat H = findHomography(Mat(points1), Mat(points2), CV_RANSAC, ransacReprojThreshold);
+\end{lstlisting}
+
+Create a set of inlier matches and draw them. Use perspectiveTransform function to map points with homography:
+\begin{lstlisting}
+Mat points1Projected;
+perspectiveTransform(Mat(points1), points1Projected, H);
+\end{lstlisting}
+Use drawMatches for drawing inliers. 
+\fi