Resource Garage

Thursday, September 18, 2014

Matlab marker size color

plot(xini(1),xini(2),'ko','MarkerSize',10, 'MarkerFaceColor',[0,0,0])

plot(tgt(1),tgt(2),'rd','MarkerSize',10, 'MarkerFaceColor',[1,0,0])

Tuesday, September 16, 2014

Skip items in Matlab legend

You can specify a vector of plot handles to use in the legend. For example:

h1 = plot(rand(1,10));      % Blue line
hold on;
h2 = plot(rand(1,10),'r');  % Red line
h3 = plot(rand(1,10),'g');  % Green line
legend([h1 h3],{'hello','world'});  % Only the blue and green lines appear
                                    %   in the legend

Thursday, August 28, 2014

Wednesday, July 30, 2014

Ubuntu 12.04 – The System is running in low-graphics mode

How do we fix it?

There is simple fix for this issue. Once you get the error on your screen press ALT+CTRL+F1, once in new screen type/run these commands

sudo apt-get update
sudo apt-get purge flglrx
sudo reboot

The message should be gone, if not there is good chnage that you have also trouble with gdm and you can fix it in these steps:

Again press ALT+CTRL+F1 and run these commands

sudo apt-get install gdm
sudo service gdm restart

Thursday, December 26, 2013

SURF and BRISK in OpenCV

Today I spent half a day to compare the two feature detector and descriptor SURF and BRISK.

The conclusion is

SURF is more accurate but takes much longer
BRISK is 10 times faster with comparable accuracy.

One thing to notice:

when using Brute-force matcher, mind the normType. See HERE

C++: BFMatcher::BFMatcher(int normType=NORM_L2, bool crossCheck=false )

Parameters:

* normType – One of NORM_L1, NORM_L2, NORM_HAMMING,NORM_HAMMING2. L1 and L2 norms are preferable choices for SIFT and SURF descriptors,

* NORM_HAMMING should be used with ORB, BRISK and BRIEF, NORM_HAMMING2 should be used with ORB when WTA_K==3 or 4.

The other thing to notice is the threshold used to select good matches. Maybe RANSAC should be used.

SURF feature

BRISK feature

	#include <iostream>
	#include <stdio.h>
	#include <stdlib.h>
	#include <vector>

	#include "opencv2\opencv.hpp"
	#include <opencv2\nonfree\features2d.hpp>

	using namespace std;
	using namespace cv;

	void useSurfDetector(Mat img_1, Mat img_2, vector<DMatch> good_matches);
	void useBriskDetector(Mat img_1, Mat img_2, vector<DMatch> good_matches);
	int main()
	{
	Mat img_1, img_2;
	//image = imread("lena.jpg",1);
	img_1= imread("img1.ppm", CV_LOAD_IMAGE_GRAYSCALE );
	img_2= imread("img12.jpg",CV_LOAD_IMAGE_GRAYSCALE );
	if(img_1.empty()\|\|img_2.empty())
	{
	cout << "Could not open or find the image" << std::endl ;
	return -1;
	}

	vector<DMatch> good_matches ;
	useSurfDetector(img_1, img_2, good_matches);

	useBriskDetector(img_1, img_2, good_matches);

	// imwrite("Lena SURF Matches.jpg",img_matches);
	waitKey(0);
	return 0;
	}


	void useSurfDetector(Mat img_1, Mat img_2, vector<DMatch> good_matches)
	{
	good_matches.clear();
	double t = (double)getTickCount();

	vector<KeyPoint> keypoints_1, keypoints_2;
	Mat descriptor_1, descriptor_2;

	int minHessian = 400;
	SurfFeatureDetector detector(minHessian);
	// Step -1, Detect keypoints using SURF detector
	detector.detect(img_1, keypoints_1);
	detector.detect(img_2, keypoints_2);
	// Step -2, Calculate descriptors (feature vector)
	SurfDescriptorExtractor extractor;
	extractor.compute(img_1,keypoints_1,descriptor_1);
	extractor.compute(img_2,keypoints_2,descriptor_2);

	//step - 3, Matching descriptor vectors with a brute force mathcher

	BFMatcher matcher(NORM_L2);

	vector<DMatch> matches;
	matcher.match(descriptor_1, descriptor_2,matches);
	// quick calcualation of max and min distances between keypoints
	t = ((double)getTickCount() - t)/getTickFrequency();

	double max_dist=0; double min_dist = 1000;
	for (int i =0; i < descriptor_1.rows;i++)
	{
	double dist = matches[i].distance;
	if(max_dist<dist) max_dist = dist;
	if(min_dist>dist) min_dist = dist;
	}
	cout << "SURF " << endl;
	cout << " max dist " << max_dist << endl;
	cout <<" max dist " << min_dist << endl;
	cout << " SURF Time (senconds): " << t<<endl;
	for (int i=0;i<descriptor_1.rows;i++)
	{
	if( matches[i].distance<3*min_dist)
	good_matches.push_back(matches[i]);
	}

	// Draw Good Matches
	Mat img_goodmatches;
	drawMatches(img_1,keypoints_1,img_2,keypoints_2,good_matches,img_goodmatches,Scalar::all(-1),Scalar::all(-1),vector<char>(),DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS);
	imshow( "Good Matches SURF", img_goodmatches );
	/* 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 );
	}*/

	};

	void useBriskDetector(Mat img_1, Mat img_2, vector<DMatch> good_matches)
	{
	good_matches.clear();
	double t = (double)getTickCount();
	vector<KeyPoint> keypoints_1, keypoints_2;
	Mat descriptor_1, descriptor_2;

	int Thresh = 60;
	int Octave = 4;
	float PatternScales=1.0f;
	cv::BRISK briskDetector(Thresh, Octave,PatternScales);

	briskDetector.create("Feature2D.BRISK");

	// Step -1, Detect keypoints using SURF detector
	briskDetector.detect(img_1, keypoints_1);
	briskDetector.detect(img_2, keypoints_2);
	// Step -2, Calculate descriptors (feature vector)
	briskDetector.compute(img_1,keypoints_1,descriptor_1);
	briskDetector.compute(img_2,keypoints_2,descriptor_2);
	//step - 3, Matching descriptor vectors with a brute force mathcher
	BFMatcher matcher(NORM_HAMMING);
	vector<DMatch> matches;
	matcher.match(descriptor_1, descriptor_2,matches);

	t = ((double)getTickCount() - t)/getTickFrequency();


	// quick calcualation of max and min distances between keypoints
	double max_dist=0; double min_dist = 1000;
	for (int i =0; i < descriptor_1.rows;i++)
	{
	double dist = matches[i].distance;
	if(max_dist<dist) max_dist = dist;
	if(min_dist>dist) min_dist = dist;
	}
	cout << "BRISK " << endl;
	cout << " max dist " << max_dist << endl;
	cout <<" max dist " << min_dist << endl;
	cout << " Brisk Time (senconds): " << t<<endl;
	min_dist = min_dist + (max_dist- min_dist)* 0.3;
	for (int i=0;i<descriptor_1.rows;i++)
	{
	if( matches[i].distance< min_dist)
	good_matches.push_back(matches[i]);
	}
	// Draw Good Matches
	Mat img_goodmatches;
	drawMatches(img_1,keypoints_1,img_2,keypoints_2,good_matches,img_goodmatches,Scalar::all(-1),Scalar::all(-1),vector<char>(),DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS);
	imshow( "Good Matches BRISK", img_goodmatches );
	/* 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 );
	}*/

	}

view raw gistfile1.cpp hosted with ❤ by GitHub

Saturday, November 16, 2013

Das ist eine brilliante Idee

Teil 4 Lektion 1

Gibt es schon Reaktionen auf den Sprachkurse?
Ja, wir haben viele Hörerbriefe bekommen.
Und was steht in den Briefen?
Die kann ich doch nicht alle vorlesen. Das dauert viel zu lange.
Nicht alle, aber einige - bitte!
Ja, das interessiert mich auch.
Na gut.
Aber bitte, machen Sie es kurz!
Hier habe ich einen Brief von Herrn Card aus Amerika - Moment. Mir gefallen die Abenteuer von Andreas - asl Portier im Hotel Europa.
Mir auch
s
Und hier ist ein Brief von Angela aus Kolumbien. Sie schreibt, ' Ich bin so glücklick, weil ich die Grammatik studiert habe. Jetzt verstehe ich den Akkusativ - der war immer ...'
Grammatik, Grammatik, Akkusativ - das ist ja langweilig! Schreiben die Hörer den nichts über mich?! Wie finden die Hörer mich, das will ich wissen!
Kein Problem, Ex. Hier ist ein Brief aus England - da steht etwas über dich! ' The intruduction of Ex is a brilliant idea. '
Das verstehe ich doch nicht! Was heißt das denn auf deutsch?
Du bist eine brillante Idee!
Idee? Wieso bin ich eine Idee? Ich bin ich!
s
Das hier ist noch ganz wichtig: Manche Hörer schreiben, daß sie Ex nicht so gut verstehen.
Wir können ihr ja eine andere Stimme geben.
Probieren wir es doch mal! Ex, sprich mal etwas!
Ben dem Zauberwort sollte ich das Buch verlassen und ...
Okay! Stop! Und noch einmal bitte!
Ben dem Zauberwort sollte ich das Buch verlassen und ...
Kann ihre Stimme nicht ganz normal bleiben?
Nein - Ex ist ja eine besondere Person, ein weiblicher kobold, da braucht sie auch eine besondere Stimme.
Das finde ich auch!
Aber das ist ein technisches Problem. Das lösen wir später.

Saturday, November 2, 2013

Finds an object pose from 3D-2D point correspondences

C++: bool solvePnP(InputArray objectPoints, InputArray imagePoints, InputArray cameraMatrix, InputArray distCoeffs, OutputArray rvec, OutputArray tvec, bool useExtrinsicGuess=false, int flags=ITERATIVE )