Commit 6b88d7a8 authored by Ana Huaman's avatar Ana Huaman

Added base tutorial for using FlannBasedMatcher with SURF detector + descriptor in rst

parent f803fc25
......@@ -368,7 +368,10 @@ extlinks = {'cvt_color': ('http://opencv.willowgarage.com/documentation/cpp/imgp
'surf_descriptor_extractor' : ( 'http://opencv.willowgarage.com/documentation/cpp/features2d_common_interfaces_of_descriptor_extractors.html#surfdescriptorextractor%s', None ),
'draw_matches' : ( 'http://opencv.willowgarage.com/documentation/cpp/features2d_drawing_function_of_keypoints_and_matches.html#cv-drawmatches%s', None ),
'find_homography' : ('http://opencv.willowgarage.com/documentation/cpp/calib3d_camera_calibration_and_3d_reconstruction.html?#findHomography%s', None),
'perspective_transform' : ('http://opencv.willowgarage.com/documentation/cpp/core_operations_on_arrays.html?#perspectiveTransform%s', None )
'perspective_transform' : ('http://opencv.willowgarage.com/documentation/cpp/core_operations_on_arrays.html?#perspectiveTransform%s', None ),
'flann_based_matcher' : ('http://opencv.willowgarage.com/documentation/cpp/features2d_common_interfaces_of_descriptor_matchers.html?#FlannBasedMatcher%s', None),
'brute_force_matcher' : ('http://opencv.willowgarage.com/documentation/cpp/features2d_common_interfaces_of_descriptor_matchers.html?#BruteForceMatcher%s', None ),
'flann' : ('http://opencv.willowgarage.com/documentation/cpp/flann_fast_approximate_nearest_neighbor_search.html?%s', None )
}
......@@ -13,6 +13,7 @@ In this tutorial you will learn how to:
* Use the :descriptor_extractor:`DescriptorExtractor<>` interface in order to find the feature vector correspondent to the keypoints. Specifically:
* Use :surf_descriptor_extractor:`SurfDescriptorExtractor<>` and its function :descriptor_extractor:`compute<>` to perform the required calculations.
* Use a :brute_force_matcher:`BruteForceMatcher<>` to match the features vector
* Use the function :draw_matches:`drawMatches<>` to draw the detected matches.
......
.. _feature_flann_matcher:
Feature Matching with FLANN
****************************
Goal
=====
In this tutorial you will learn how to:
.. container:: enumeratevisibleitemswithsquare
* Use the :flann_based_matcher:`FlannBasedMatcher<>` interface in order to perform a quick and efficient matching by using the :flann:`FLANN<>` ( *Fast Approximate Nearest Neighbor Search Library* )
Theory
======
Code
====
This tutorial code's is shown lines below. You can also download it from `here <https://code.ros.org/svn/opencv/trunk/opencv/samples/cpp/tutorial_code/features2D/SURF_FlannMatcher.cpp>`_
.. code-block:: cpp
#include <stdio.h>
#include <iostream>
#include "opencv2/core/core.hpp"
#include "opencv2/features2d/features2d.hpp"
#include "opencv2/highgui/highgui.hpp"
using namespace cv;
void readme();
/** @function main */
int main( int argc, char** argv )
{
if( argc != 3 )
{ readme(); return -1; }
Mat img_1 = imread( argv[1], CV_LOAD_IMAGE_GRAYSCALE );
Mat img_2 = imread( argv[2], CV_LOAD_IMAGE_GRAYSCALE );
if( !img_1.data || !img_2.data )
{ std::cout<< " --(!) Error reading images " << std::endl; return -1; }
//-- Step 1: Detect the keypoints using SURF Detector
int minHessian = 400;
SurfFeatureDetector detector( minHessian );
std::vector<KeyPoint> keypoints_1, keypoints_2;
detector.detect( img_1, keypoints_1 );
detector.detect( img_2, keypoints_2 );
//-- Step 2: Calculate descriptors (feature vectors)
SurfDescriptorExtractor extractor;
Mat descriptors_1, descriptors_2;
extractor.compute( img_1, keypoints_1, descriptors_1 );
extractor.compute( img_2, keypoints_2, descriptors_2 );
//-- Step 3: Matching descriptor vectors using FLANN matcher
FlannBasedMatcher matcher;
std::vector< DMatch > matches;
matcher.match( descriptors_1, descriptors_2, matches );
double max_dist = 0; double min_dist = 100;
//-- Quick calculation of max and min distances between keypoints
for( int i = 0; i < descriptors_1.rows; i++ )
{ double dist = matches[i].distance;
if( dist < min_dist ) min_dist = dist;
if( dist > max_dist ) max_dist = dist;
}
printf("-- Max dist : %f \n", max_dist );
printf("-- Min dist : %f \n", min_dist );
//-- Draw only "good" matches (i.e. whose distance is less than 2*min_dist )
//-- PS.- radiusMatch can also be used here.
std::vector< DMatch > good_matches;
for( int i = 0; i < descriptors_1.rows; i++ )
{ if( matches[i].distance < 2*min_dist )
{ good_matches.push_back( matches[i]); }
}
//-- Draw only "good" matches
Mat img_matches;
drawMatches( img_1, keypoints_1, img_2, keypoints_2,
good_matches, img_matches, Scalar::all(-1), Scalar::all(-1),
vector<char>(), DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS );
//-- Show detected matches
imshow( "Good Matches", img_matches );
for( int i = 0; i < good_matches.size(); i++ )
{ printf( "-- Good Match [%d] Keypoint 1: %d -- Keypoint 2: %d \n", i, good_matches[i].queryIdx, good_matches[i].trainIdx ); }
waitKey(0);
return 0;
}
/** @function readme */
void readme()
{ std::cout << " Usage: ./SURF_FlannMatcher <img1> <img2>" << std::endl; }
Explanation
============
Result
======
#. Here is the result of the feature detection applied to the first image:
.. image:: images/Featur_FlannMatcher_Result.jpg
:align: center
:height: 250pt
#. Additionally, we get as console output the keypoints filtered:
.. image:: images/Feature_FlannMatcher_Keypoints_Result.jpg
:align: center
:height: 250pt
......@@ -94,4 +94,4 @@ int main( int argc, char** argv )
* @function readme
*/
void readme()
{ std::cout << " Usage: ./SURF_descriptor <img1> <img2>" << std::endl; }
{ std::cout << " Usage: ./SURF_FlannMatcher <img1> <img2>" << std::endl; }
......@@ -119,4 +119,4 @@ int main( int argc, char** argv )
* @function readme
*/
void readme()
{ std::cout << " Usage: ./SURF_descriptor <img1> <img2>" << std::endl; }
{ std::cout << " Usage: ./SURF_Homography <img1> <img2>" << std::endl; }
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