diff --git a/example_16-02.cpp b/example_16-02.cpp
new file mode 100644
index 0000000..569af31
--- /dev/null
+++ b/example_16-02.cpp
@@ -0,0 +1,213 @@
+// Example 16-2. 2D Feature detectors and 2D Extra Features framework
+
+#include <vector>
+#include <iostream>
+#include <cstdlib>
+#include <fstream>
+#include <algorithm>
+#include <opencv2/opencv.hpp>
+#include <opencv2/objdetect.hpp>
+#include <opencv2/core/core.hpp>
+#include <opencv2/highgui/highgui.hpp>
+#include <opencv2/features2d.hpp>
+#include <opencv2/xfeatures2d.hpp>
+#include <opencv2/calib3d.hpp>
+#include <opencv2/imgproc.hpp>
+#include <opencv2/core/utility.hpp>
+#include <opencv2/core/ocl.hpp>
+
+using std::cout;
+using std::cerr;
+using std::vector;
+using std::string;
+
+using cv::Mat;
+using cv::Point2f;
+using cv::KeyPoint;
+using cv::Scalar;
+using cv::Ptr;
+
+using cv::FastFeatureDetector;
+using cv::SimpleBlobDetector;
+
+using cv::DMatch;
+using cv::BFMatcher;
+using cv::DrawMatchesFlags;
+using cv::Feature2D;
+using cv::ORB;
+using cv::BRISK;
+using cv::AKAZE;
+using cv::KAZE;
+
+using cv::xfeatures2d::BriefDescriptorExtractor;
+using cv::xfeatures2d::SURF;
+using cv::xfeatures2d::SIFT;
+using cv::xfeatures2d::DAISY;
+using cv::xfeatures2d::FREAK;
+
+const double kDistanceCoef = 4.0;
+const int kMaxMatchingSize = 50;
+
+inline void detect_and_compute(string type, Mat& img, vector<KeyPoint>& kpts, Mat& desc) {
+    if (type.find("fast") == 0) {
+        type = type.substr(4);
+        Ptr<FastFeatureDetector> detector = FastFeatureDetector::create(10, true);
+        detector->detect(img, kpts);
+    }
+    if (type.find("blob") == 0) {
+        type = type.substr(4);
+        Ptr<SimpleBlobDetector> detector = SimpleBlobDetector::create();
+        detector->detect(img, kpts);
+    }
+    if (type == "surf") {
+        Ptr<Feature2D> surf = SURF::create(800.0);
+        surf->detectAndCompute(img, Mat(), kpts, desc);
+    }
+    if (type == "sift") {
+        Ptr<Feature2D> sift = SIFT::create();
+        sift->detectAndCompute(img, Mat(), kpts, desc);
+    }
+    if (type == "orb") {
+        Ptr<ORB> orb = ORB::create();
+        orb->detectAndCompute(img, Mat(), kpts, desc);
+    }
+    if (type == "brisk") {
+        Ptr<BRISK> brisk = BRISK::create();
+        brisk->detectAndCompute(img, Mat(), kpts, desc);
+    }
+    if (type == "kaze") {
+        Ptr<KAZE> kaze = KAZE::create();
+        kaze->detectAndCompute(img, Mat(), kpts, desc);
+    }
+    if (type == "akaze") {
+        Ptr<AKAZE> akaze = AKAZE::create();
+        akaze->detectAndCompute(img, Mat(), kpts, desc);
+    }
+    if (type == "freak") {
+        Ptr<FREAK> freak = FREAK::create();
+        freak->compute(img, kpts, desc);
+    }
+    if (type == "daisy") {
+        Ptr<DAISY> daisy = DAISY::create();
+        daisy->compute(img, kpts, desc);
+    }
+    if (type == "brief") {
+        Ptr<BriefDescriptorExtractor> brief = BriefDescriptorExtractor::create(64);
+        brief->compute(img, kpts, desc);
+    }
+}
+
+inline void match(string type, Mat& desc1, Mat& desc2, vector<DMatch>& matches) {
+    matches.clear();
+    if (type == "bf") {
+        BFMatcher desc_matcher(cv::NORM_L2, true);
+        desc_matcher.match(desc1, desc2, matches, Mat());
+    }
+    if (type == "knn") {
+        BFMatcher desc_matcher(cv::NORM_L2, true);
+        vector< vector<DMatch> > vmatches;
+        desc_matcher.knnMatch(desc1, desc2, vmatches, 1);
+        for (int i = 0; i < static_cast<int>(vmatches.size()); ++i) {
+            if (!vmatches[i].size()) {
+                continue;
+            }
+            matches.push_back(vmatches[i][0]);
+        }
+    }
+    std::sort(matches.begin(), matches.end());
+    while (matches.front().distance * kDistanceCoef < matches.back().distance) {
+        matches.pop_back();
+    }
+    while (matches.size() > kMaxMatchingSize) {
+        matches.pop_back();
+    }
+}
+
+inline void findKeyPointsHomography(vector<KeyPoint>& kpts1, vector<KeyPoint>& kpts2,
+        vector<DMatch>& matches, vector<char>& match_mask) {
+    if (static_cast<int>(match_mask.size()) < 3) {
+        return;
+    }
+    vector<Point2f> pts1;
+    vector<Point2f> pts2;
+    for (int i = 0; i < static_cast<int>(matches.size()); ++i) {
+        pts1.push_back(kpts1[matches[i].queryIdx].pt);
+        pts2.push_back(kpts2[matches[i].trainIdx].pt);
+    }
+    findHomography(pts1, pts2, cv::RANSAC, 4, match_mask);
+}
+
+int main(int argc, char** argv) {
+    // Program expects at least four arguments:
+    //   - descriptors type ("surf", "sink", "orb", "brisk",
+    //          "kaze", "akaze", "freak", "daisy", "brief").
+    //          For "brief", "freak" and "daisy" you also need a prefix
+    //          that is either "blob" or "fast" (e.g. "fastbrief", "blobdaisy")
+    //   - match algorithm ("bf", "knn")
+    //   - path to the object image file
+    //   - path to the scene image file
+    //
+    if (argc < 5) {
+        cerr << "\nError: wrong number of arguments.\n";
+        cerr    << "\nExample 16-2. 2D Feature detectors and 2D Extra Features framework\n\n"
+                << "Use:\n" << argv[0] << "<descriptors_type> <matching_algirthm> "
+                << "<path/image_file1> <path/image_file2>\n"
+                << "to run this demo\n\n"
+                << "Program expects at least four arguments:\n"
+                << "  - descriptors type (\"surf\", \"sink\", \"orb\", \"brisk\",\n"
+                << "       \"kaze\", \"akaze\", \"freak\", \"daisy\", \"brief\").\n"
+                << "       For \"brief\", \"freak\" and \"daisy\" you also need a prefix\n"
+                << "       that is either \"blob\" or \"fast\" (e.g. \"fastbrief\", "
+                << "\"blobdaisy\")\n"
+                << "  - match algorithm (\"bf\", \"knn\")\n"
+                << "  - path to the object image file\n"
+                << "  - path to the scene image file\n\n"
+                << "Examples:\n"
+                << argv[0] << " surf knn box.png box_in_scene.png\n"
+                << argv[0] << " fastfreak bf box.png box_in_scene.png\n"
+                << std::endl;
+        exit(1);
+    }
+
+    string desc_type(argv[1]);
+    string match_type(argv[2]);
+
+    string img_file1(argv[3]);
+    string img_file2(argv[4]);
+
+    Mat img1 = cv::imread(img_file1, CV_LOAD_IMAGE_COLOR);
+    Mat img2 = cv::imread(img_file2, CV_LOAD_IMAGE_COLOR);
+
+    if (img1.channels() != 1) {
+        cvtColor(img1, img1, cv::COLOR_RGB2GRAY);
+    }
+
+    if (img2.channels() != 1) {
+        cvtColor(img2, img2, cv::COLOR_RGB2GRAY);
+    }
+
+    vector<KeyPoint> kpts1;
+    vector<KeyPoint> kpts2;
+
+    Mat desc1;
+    Mat desc2;
+
+    vector<DMatch> matches;
+
+    detect_and_compute(desc_type, img1, kpts1, desc1);
+    detect_and_compute(desc_type, img2, kpts2, desc2);
+
+    match(match_type, desc1, desc2, matches);
+
+    vector<char> match_mask(matches.size(), 1);
+    findKeyPointsHomography(kpts1, kpts2, matches, match_mask);
+
+    Mat res;
+    cv::drawMatches(img1, kpts1, img2, kpts2, matches, res, Scalar::all(-1),
+        Scalar::all(-1), match_mask, DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS);
+
+    cv::imshow("result", res);
+    cv::waitKey(0);
+
+    return 0;
+}
diff --git a/example_22-01.cpp b/example_22-01.cpp
index 1fa56fe..3c7ab7f 100644
--- a/example_22-01.cpp
+++ b/example_22-01.cpp
@@ -18,7 +18,7 @@ using std::string;
 //
 void detectAndDraw(
         cv::Mat& img,                               // input image
-         cv::Ptr<cv::CascadeClassifier> classifier,  // preloaded classifier
+        cv::Ptr<cv::CascadeClassifier> classifier,  // preloaded classifier
         double scale = 1.3) {                       // resize image by ...
     // Just some pretty colors to draw with
     //
@@ -69,12 +69,12 @@ int main(int argc, char** argv) {
     //
     if (argc < 3) {
         cerr << "\nError: wrong number of arguments.\n";
-        cerr 	<< "\nExample 22-1. Detecting and drawing faces\n\n"
-				<< "Use:\n" << argv[0] << " <path/image_file> <path/xml_classifier_file>\n"
-				<< "to run this demo\n\n"
-				<< "Example:\n"
-				<< argv[0] << " ../faces.png ../haarcascade_frontalface_alt.xml\n"
-				<< std::endl;
+        cerr    << "\nExample 22-1. Detecting and drawing faces\n\n"
+                << "Use:\n" << argv[0] << " <path/image_file> <path/xml_classifier_file>\n"
+                << "to run this demo\n\n"
+                << "Example:\n"
+                << argv[0] << " ../faces.png ../haarcascade_frontalface_alt.xml\n"
+                << std::endl;
         exit(1);
     }
     string image_file_name = string(argv[1]);