TrackEye : Real-Time Tracking Of Human Eyes Using a Webcam

• Download executable - 2.51 MB
• Download source code - 199.24 KB

Introduction

Eyes are the most important features of the human face. So effective usage of eye movements as a communication technique in user-to-computer interfaces can find place in various application areas.

Eye tracking and the information provided by the eye features have the potential to become an interesting way of communicating with a computer in a human-computer interaction (HCI) system. So with this motivation, designing a real-time eye feature tracking software is the aim of this project.

The purpose of the project is to implement a real-time eye-feature tracker with the following capabilities:

• RealTime face tracking with scale and rotation invariance
• Tracking the eye areas individually
• Tracking eye features
• Eye gaze direction finding
• Remote controlling using eye movements

Instructions to Run and Rebuild TrackEye

Installation Instructions

1. Extract TrackEye_Executable.zip file. Before running TrackEye_636.exe, copy the two files SampleHUE.jpg and SampleEye.jpg to the C:\ folder. These two files are used for CAMSHIFT and Template-Matching algorithms.
2. There are no other steps to be followed by the user to run the software. There are no DLL dependencies as the software was built with the DLLs statically included.

Settings to be Done to Perform a Good Tracking

Settings for Face & Eye Detection

Under TrackEye Menu --> Tracker Settings

• Input Source: video
• Click on Select file and select ..\Avis\Sample.avi
• Face Detection Algorithm: Haar Face Detection Algorithm
• Check “Track also Eyes” checkBox
• Eye Detection Algorithm: Adaptive PCA
• Uncheck “Variance Check”
• Number of Database Images: 8
• Number of EigenEyes: 5
• Maximum allowable distance from eyespace: 1200
• Face width/eye template width ratio: 0.3
• ColorSpace type to use during PCA: CV_RGB2GRAY

Settings for Pupil Detection

Check “Track eyes in details” and then check “Detect also eye pupils”. Click “Adjust Parameters” button:

• Enter “120” as the “Threshold Value”
• Click “Save Settings” and then click “Close”

Settings for Snake

Check “Indicate eye boundary using active snakes”. Click “Settings for snake” button:

• Select ColorSpace to use: CV_RGB2GRAY
• Select Simple thresholding and enter 100 as the “Threshold value”
• Click “Save Settings” and then click “Close”

Background

So far there has been a lot of work on eye detection and before the project, the previous methods were carefully studied to determine the implemented method. We can classify studies related to eye into two main categories as listed below:

Special Equipment Based Approaches

These type of studies use the necessary equipment which will give a signal of some sort which is proportional to the position of the eye in the orbit. Various methods that are current in use are Electrooculography, Infra-Red Oculography, Scleral search coils. These methods are completely out of our project.

Image Based Approaches

Image based approaches perform eye detections on the images. Most of the image based methods try to detect the eyes using the features of the eyes. Methods used so far are knowledge-based methods, feature-based methods (color, gradient), simple template matching, appearance methods. Another interesting method is “Deformable template matching” which is based on matching a geometrical eye template on an eye image by minimizing the energy of the geometrical model.

Implementation of TrackEye

The implemented project is on three components:

1. Face detection: Performs scale invariant face detection
2. Eye detection: Both eyes are detected as a result of this step
3. Eye feature extraction: Features of eyes are extracted at the end of this step

Face Detection

Two different methods were implemented in the project. They are:

1. Continuously Adaptive Means-Shift Algorithm
2. Haar Face Detection method

Continuously Adaptive Mean-Shift Algorithm

Adaptive Mean Shift algorithm is used for tracking human faces and is based on robust non-parametric technique for climbing density gradients to find the mode (peak) of probability distributions called the mean shift algorithm. As faces are tracked in video sequences, mean shift algorithm is modified to deal with the problem of dynamically changing color probability distributions. The block diagram of the algorithm is given below:

Haar-Face Detection Method

The second face detection algorithm is based on a classifier working with Haar-Like features (namely a cascade of boosted classifiers working with Haar-like features). First of all it is trained with a few hundreds of sample views of a face. After a classifier is trained, it can be applied to a region of interest in an input image. The classifier outputs a "1" if the region is likely to show face and "0" otherwise. To search for the object in the whole image, one can move the search window across the image and check every location using the classifier. The classifier is designed so that it can be easily "resized" in order to be able to find the objects of interest at different sizes, which is more efficient than resizing the image itself.

Eye Detection

Two different methods were implemented in the project:

1. Template-Matching
2. Adaptive EigenEye Method

Template-Matching

Template-Matching is a well-known method for object detection. In our template matching method, a standard eye pattern is created manually and given an input image, the correlation values with the standard patterns are computed for the eyes. The existence of an eye is determined based on the correlation values. This approach has the advantage of being simple to implement. However, it may sometimes be inadequate for eye detection since it cannot effectively deal with variation in scale, pose and shape.

Adaptive EigenEye Method

Adaptive EigenEye Method is based on the well-known method EigenFaces. However as the method is used for eye detection we named it as “EigenEye Method”. The main idea is to decompose eye images into a small set of characteristics feature images called eigeneyes, which may be thought of as the principal components of the original images. These eigeneyes function as the orthogonal basis vectors of a subspace called eyespace. However we know that the eigenface method is not scale invariant. To provide the scale invariance we can resize the eye-database once with the information gathered by the face detection algorithm (EyeWidth / FaceWidth ? 0.35), we can provide scale-invariant detection using only one database.

OpenCV Functions for Object Tracking and Detection

OpenCV Library offers a lot of image processing and object tracking & detection libraries. The main function used in these projects and their usage are given below:

Sample Code for Haar-Face Tracking

void CTrackEyeDlg::HaarFaceDetect( IplImage* img, CvBox2D* faceBox)
{
    int scale = 2;
    IplImage* temp = cvCreateImage( cvSize(img->width/2,img->height/2), 8, 3 );
    CvPoint pt1, pt2;
    int i;

    cvPyrDown( img, temp, CV_GAUSSIAN_5x5 );
    #ifdef WIN32
        cvFlip( temp, temp, 0 );
    #endif
    cvClearMemStorage( storage );

    if( hid_cascade )
    {
        CvSeq* faces = cvHaarDetectObjects( temp, hid_cascade, storage, 1.2, 2,
                    CV_HAAR_DO_CANNY_PRUNING );

        NumOfHaarFaces = faces->total;

        if (NumOfHaarFaces > 0)
        {
                CvRect* r = (CvRect*)cvGetSeqElem( faces, 0, 0 );
                pt1.x = r->x*scale;
                pt2.x = (r->x+r->width)*scale;
        #ifdef WIN32
            pt1.y = img->height - r->y*scale;
            pt2.y = img->height - (r->y+r->height)*scale;
        #else
            pt1.y = r->y*scale;
            pt2.y = (r->y+r->height)*scale;
        #endif

        faceBox->center.x = (float)(pt1.x+pt2.x)/2.0;
        faceBox->center.y = (float)(pt1.y+pt2.y)/2;
        faceBox->size.width = (float)(pt2.x - pt1.x);
        faceBox->size.height = (float)(pt1.y - pt2.y);
            }
    }
    cvShowImage( "Tracking", img );
    cvReleaseImage( &temp );
}

Sample Code for CamShift Algorithm

// Inputs for CamShift algorithm
IplImage* HUE = cvCreateImage(cvGetSize(SampleForHUE), IPL_DEPTH_8U, 1);
extractHUE(SampleForHUE, HUE);    //    **    Extract HUE information

int hist_size      = 20;
float ranges[]      = { 0, 180 };
float* pranges[]  = {ranges};
hist = cvCreateHist( 1, &hist_size, CV_HIST_ARRAY, pranges, 1 );
cvCalcHist(&HUE, hist);    // Calculate histogram of HUE part

hueFrame = cvCreateImage(cvGetSize(CameraFrame), IPL_DEPTH_8U, 1);
backProject = cvCreateImage(cvGetSize(CameraFrame), IPL_DEPTH_8U, 1);
extractHUE(CameraFrame, hueFrame);

while (trackControl != 0)
{
    extractHUE( CameraFrame, hueFrame );
    cvCalcBackProject( &hueFrame, backProject, hist ); // Probability is formed
    //cvShowImage("Tester2", backProject);
    cvCamShift( backProject, searchWin, cvTermCriteria( CV_TERMCRIT_EPS |
            CV_TERMCRIT_ITER, 15, 0.1 ), &comp, &faceBox );
    searchWin = comp.rect;
}

Sample Code Template Matching

// Template Matching for Eye detection
void Face::findEyes_TM(IplImage* faceImage, TrackingSettings* settings)
{
    CvSize faceSize; faceSize = cvGetSize(faceImage);

    // Load Template from the eye database
    CString fileName;
    // Name of the template for left eye
    fileName.Format("%s\\eye%d.jpg", settings->params->DBdirectory, 0);
    IplImage* eyeImage_Left    = cvLoadImage(fileName, -1);
    // Name of the template for left eye
    fileName.Format("%s\\eye%d.jpg", settings->params->DBdirectory, 1);

    IplImage* eyeImage_Right = cvLoadImage(fileName, -1);

    IplImage* tempTemplateImg_Left; IplImage* tempTemplateImg_Right;
    IplImage* templateImg_Left; IplImage* templateImg_Right;

    if (eyeImage_Left == NULL || eyeImage_Right == NULL)
    {
        MessageBox(NULL, "Templates can not be loaded.\n
            Please check your eye database folder", "Error", MB_OK||MB_ICONSTOP);
        exit(1);
    }
    else
    {
        //    Change color space according to the settings entered by the user
        tempTemplateImg_Left = cvCreateImage(cvGetSize(eyeImage_Left), IPL_DEPTH_8U, 1);
        changeColorSpace(settings, eyeImage_Left, tempTemplateImg_Left);
        tempTemplateImg_Right =
                   cvCreateImage(cvGetSize(eyeImage_Right), IPL_DEPTH_8U, 1);
        changeColorSpace(settings, eyeImage_Right, tempTemplateImg_Right);

        float idealWidth = faceSize.width * settings->params->ratio;
        float conversionRatio = idealWidth/(float)tempTemplateImg_Left->width;

        CvSize newSize;
        newSize.width = (int)idealWidth;
        newSize.height = (int)(tempTemplateImg_Left->height*conversionRatio);

        templateImg_Left = cvCreateImage(newSize, IPL_DEPTH_8U, 1);
        cvResize(tempTemplateImg_Left, templateImg_Left, CV_INTER_LINEAR); // was NN
        cvReleaseImage(&eyeImage_Left);
        cvReleaseImage(&tempTemplateImg_Left);

        templateImg_Right = cvCreateImage(newSize, IPL_DEPTH_8U, 1);
        cvResize(tempTemplateImg_Right, templateImg_Right, CV_INTER_LINEAR); // was NN
        cvReleaseImage(&eyeImage_Right);
        cvReleaseImage(&tempTemplateImg_Right);
    }
    //    *************************************************************
    //    ************Search faceImage for eyes************************
    //    *************************************************************
    IplImage* GRAYfaceImage = cvCreateImage(faceSize, IPL_DEPTH_8U, 1);
    changeColorSpace(settings, faceImage, GRAYfaceImage);
    //cvCvtColor( faceImage, GRAYfaceImage, CV_RGB2GRAY);
    //GRAYfaceImage->origin = 1;
    //    **    Warning at this point image origin is bottom-left corner.

    //    **    Eye1 search area
    int x_left = 0;
    int y_left = 0;
    int width_left = (int)((float)(faceSize.width/2.0));
    int height_left = (int)((float)(faceSize.height));
    CvRect rect_Eye1 = cvRect(x_left, y_left, width_left, height_left);

    CvMat* Eye1Image = cvCreateMat(width_left, height_left, CV_8UC1);
    cvGetSubRect(GRAYfaceImage, Eye1Image, rect_Eye1 );
    cvFlip( Eye1Image, Eye1Image, 0);

    //    **    Eye2 search area
    int x_right= (int)((float)(faceSize.width/2.0));
    int y_right = 0;
    int width_right = (int)((float)(faceSize.width/2.0));
    int height_right = (int)((float)(faceSize.height));
    CvRect rect_Eye2 = cvRect(x_right, y_right, width_right, height_right);

    CvMat* Eye2Image = cvCreateMat(width_right, height_right, CV_8UC1);
    cvGetSubRect(GRAYfaceImage, Eye2Image, rect_Eye2 );
    cvFlip( Eye2Image, Eye2Image, 0);

    // OpenCV says that size of the result must be the following:
    CvSize size;
    size.height= Eye1Image->height - templateImg_Left->height + 1;
    size.width = Eye1Image->width - templateImg_Left->width + 1;
    IplImage* result1 = cvCreateImage( size,IPL_DEPTH_32F,1);
    IplImage* result2 = cvCreateImage( size,IPL_DEPTH_32F,1);

    // Left Eye
    cvMatchTemplate( Eye1Image, templateImg_Left, result1, settings->params->tempMatch);
    // Right Eye
    cvMatchTemplate( Eye2Image, templateImg_Right, result2, settings->params->tempMatch);

    // find the best match location - LEFT EYE
        double minValue1, maxValue1;
        CvPoint minLoc1, maxLoc1;
        cvMinMaxLoc( result1, &minValue1, &maxValue1, &minLoc1, &maxLoc1 );
    cvCircle( result1, maxLoc1, 5, settings->programColors.colors[2], 1 );
    // transform point back to original image
       maxLoc1.x += templateImg_Left->width / 2;
        maxLoc1.y += templateImg_Left->height / 2;
    settings->params->eye1.coords.x = maxLoc1.x;
    settings->params->eye1.coords.y = maxLoc1.y;
    settings->params->eye1.RectSize.width = templateImg_Left->width;
    settings->params->eye1.RectSize.height = templateImg_Left->height;
    settings->params->eye1.eyefound = true;

    // find the best match location - RIGHT EYE
        double minValue2, maxValue2;
        CvPoint minLoc2, maxLoc2;
        cvMinMaxLoc( result2, &minValue2, &maxValue2, &minLoc2, &maxLoc2 );
    cvCircle( result2, maxLoc2, 5, settings->programColors.colors[2], 1 );
    // transform point back to original image
        maxLoc2.x += templateImg_Left->width / 2;
        maxLoc2.y += templateImg_Left->height / 2;
    settings->params->eye2.coords.x = maxLoc2.x+(int)faceSize.width/2;
    settings->params->eye2.coords.y = maxLoc2.y;
    settings->params->eye2.RectSize.width = templateImg_Left->width;
    settings->params->eye2.RectSize.height = templateImg_Left->height;
    settings->params->eye2.eyefound = true;

    cvCircle( Eye1Image, maxLoc1, 5, settings->programColors.colors[2], 1 );
    cvCircle( Eye2Image, maxLoc2, 5, settings->programColors.colors[2], 1 );
}

Sample Code Adaptive EigenEye Method

void Face::findEyes(IplImage* faceImage, TrackingSettings* settings)
{
    IplImage** images = (IplImage**)malloc(sizeof(IplImage*)*numOfImages);
    IplImage** eigens = (IplImage**)malloc(sizeof(IplImage*)*numOfImages);

    IplImage* averageImage;
    IplImage* projection;

    CvSize faceSize; faceSize = cvGetSize(faceImage);
    eigenSize newEigenSize;

    newEigenSize.width = faceSize.width * settings->params->ratio;

    newEigenSize.conversion = ((float)newEigenSize.width) / ((float)database[0]->width);
    newEigenSize.height = ((float)database[0]->height) * newEigenSize.conversion;

    CvSize newSize;
    newSize.width = (int)newEigenSize.width;
    newSize.height = (int)newEigenSize.height;

    IplImage* tempImg = cvCreateImage( newSize, IPL_DEPTH_8U, 1);
    //    **********Initializations**********
    for (int i=0; iparams->nImages; i++)
    {
        images[i] = cvCreateImage(newSize, IPL_DEPTH_8U, 1);
        cvResize(database[i], images[i], CV_INTER_LINEAR); // was NN
    }
    cvShowImage("Eigen", images[0]);
    cvReleaseImage(&tempImg);

    //    Create space for EigenFaces
    for (i=0; iparams->nImages; i++)
        eigens[i] = cvCreateImage(cvGetSize(images[0]), IPL_DEPTH_32F, 1);

    averageImage = cvCreateImage(cvGetSize(images[0]), IPL_DEPTH_32F, 1);
    projection = cvCreateImage(cvGetSize(images[0]), IPL_DEPTH_8U, 1);

    //    *************************************************************
    //    ************Calculate EigenVectors & EigenValues*************
    //    *************************************************************
    CvTermCriteria criteria;
    criteria.type = CV_TERMCRIT_ITER|CV_TERMCRIT_EPS;
        criteria.maxIter = 13;
        criteria.epsilon = 0.1;

    //    **    n was present instead of numOfImages
    cvCalcEigenObjects( settings->params->nImages, images, eigens,
                        0, 0, 0, &criteria, averageImage, vals );

    //    *************************************************************
    //    ************Search faceImage for eyes************************
    //    *************************************************************
    IplImage* GRAYfaceImage = cvCreateImage(faceSize, IPL_DEPTH_8U, 1);
    changeColorSpace(settings,faceImage, GRAYfaceImage);
    //cvCvtColor( faceImage, GRAYfaceImage, CV_RGB2GRAY);
    //    **    Warning at this point image origin is bottom-left corner.
    GRAYfaceImage->origin = 1;

    int MARGIN = settings->params->MaxError;
    double minimum = MARGIN; double distance = MARGIN;

    //    **    Eye1 search Space
    settings->params->eye1.xlimitLeft = 0;
    settings->params->eye1.xlimitRight = faceSize.width/2.0 - images[0]->width - 1;
    settings->params->eye1.ylimitUp =
             (int)( ((float)faceSize.height)*0.75 - images[0]->height - 1);
    settings->params->eye1.ylimitDown = faceSize.height/2;

    //    **    Eye2 search Space
    settings->params->eye2.xlimitLeft = faceSize.width/2.0;
    settings->params->eye2.xlimitRight = faceSize.width - images[0]->width - 1;
    settings->params->eye2.ylimitUp =
         (int)( ((float)faceSize.height)*0.75 - images[0]->height - 1);
    settings->params->eye2.ylimitDown = faceSize.height/2;

    settings->params->eye1.initializeEyeParameters();
    settings->params->eye2.initializeEyeParameters();
    settings->params->eye1.RectSize.width = images[0]->width;
    settings->params->eye1.RectSize.height = images[0]->height;
    settings->params->eye2.RectSize.width = images[0]->width;
    settings->params->eye2.RectSize.height = images[0]->height;

    IplImage* Image2Comp = cvCreateImage(cvGetSize(images[0]), IPL_DEPTH_8U, 1);
    int x,y;
    //    **    Search left eye i.e eye1
    for (y=settings->params->eye1.ylimitDown; yparams->eye1.ylimitUp; y+=2)
    {
        for (x=settings->params->eye1.xlimitLeft; xparams->eye1.xlimitRight; x+=2)
        {
            cvSetImageROI(GRAYfaceImage, cvRect
                 (x, y, images[0]->width, images[0]->height));
            if (settings->params->varianceCheck == 1 )
            {
                if (calculateSTD(GRAYfaceImage) <= (double)(settings->params->variance))
                {
                    cvResetImageROI(GRAYfaceImage);
                    continue;
                }
            }
            cvFlip( GRAYfaceImage, Image2Comp, 0);
            cvResetImageROI(GRAYfaceImage);
            //    Decide whether it is an eye or not
            cvEigenDecomposite( Image2Comp, settings->params->nEigens,
                                eigens, 0, 0, averageImage, weights );
            cvEigenProjection( eigens, settings->params->nEigens,
                       CV_EIGOBJ_NO_CALLBACK, 0, weights, averageImage, projection );
            distance = cvNorm(Image2Comp, projection, CV_L2, 0);

            if (distance < minimum && distance > 0)
            {
                settings->params->eye1.eyefound = true;
                minimum = distance;
                settings->params->eye1.distance = distance;
                settings->params->eye1.coords.x = x;
                settings->params->eye1.coords.y = y;
            }
        }
    }

    minimum = MARGIN; distance = MARGIN;

    //    **    Search right eye i.e eye2
    for (y=settings->params->eye2.ylimitDown; yparams->eye2.ylimitUp; y+=2)
    {
        for (x=settings->params->eye2.xlimitLeft; xparams->eye2.xlimitRight; x+=2)
        {
            cvSetImageROI(GRAYfaceImage,
                  cvRect(x, y, images[0]->width, images[0]->height));
            if (settings->params->varianceCheck == 1)
            {
                if (calculateSTD(GRAYfaceImage) <= (double)(settings->params->variance))
                {
                    cvResetImageROI(GRAYfaceImage);
                    continue;
                }
            }
            cvFlip( GRAYfaceImage, Image2Comp, 0);
            cvResetImageROI(GRAYfaceImage);
            //    **    Decide whether it is an eye or not
            cvEigenDecomposite( Image2Comp, settings->params->nEigens,
                                eigens, 0, 0, averageImage, weights );
            cvEigenProjection( eigens, settings->params->nEigens,
                               0, 0, weights, averageImage, projection );
            distance = cvNorm(Image2Comp, projection, CV_L2, 0);

            if (distance < minimum && distance > 0)
            {
                settings->params->eye2.eyefound = true;
                minimum = distance;
                settings->params->eye2.distance = distance;
                settings->params->eye2.coords.x = x;
                settings->params->eye2.coords.y = y;
            }
        }
    }
    cvReleaseImage(&Image2Comp);

    //    **    Cleanup
    cvReleaseImage(&GRAYfaceImage);
    for (i=0; iparams->nImages; i++)
        cvReleaseImage(&images[i]);

    for (i=0; iparams->nImages; i++)
        cvReleaseImage(&eigens[i]);

    cvReleaseImage(&averageImage);
    cvReleaseImage(&projection);

    free(images);
    free(eigens);
}

History

• v 1.0 : First version of TrackEye
• v 2.0 : Second version of TrackEye
• TrackEye v2.0 now supports:
• Two different face detection algorithms:
1. Haar Face Tracking
2. CAMSHIFT
• Two different eye detection algorithms:
1. Adaptive Principal Components Analysis
2. Template matching
• Tracking algorithms can be selected by the user at the beginning of the process via GUI.
• Selectable input source:
1. Webcam
2. Video file

* Please note that TrackEye was written with OpenCV Library v3.1, so make sure to use it during rebuild.

You must Sign In to use this message board.

FAQ    Noise Tolerance Very HighHighMediumLowVery Low   Layout Expand Posts & RepliesThread ViewNo JavascriptNo JS + Preview   Per page 102550

Msgs 1 to 25 of 126 (Total in Forum: 126) (Refresh) FirstPrevNext

How to increase the tracking video resolution namlitw 9:39 2 Nov '09   I want to track eye in bigger windows for example 640x480. But I look your code carefully but I can not find out how to adjust it, as you use CVnamedwindows , and CVcapturefromcam with parameters that I think will give any default resolution of cam. But I can't change the resolution when I use Logitech camera with 640x480 size Sign In·View Thread·PermaLink Re: How to increase the tracking video resolution zafersavas 12:11 3 Nov '09   First of all the video frame, whatever the resolution is, is fitted to the program window. So you can not change the window size. However resizing to this fixed size window does not mean that you can not use different resolutions. By using "Trackeye Menu --> Adjust Capture Device Settings" you can increase your cameras resolution which will probably give better results in tracking and feature extraction. Good luck zafer Sign In·View Thread·PermaLink Problem with MFC and vista dSolariuM 22:54 30 Oct '09   Hi all, I am new to opencv and I want to use it. But Before the application starts an error appears: "The application was unable to start correctly (0x0150002).Click OK to close the application" Please help me(I am using opencv2.0 and running windows vista) Thanks. Every new thing you learn,Gives you a new personality. Sign In·View Thread·PermaLink Re: Problem with MFC and vista zafersavas 12:06 3 Nov '09   I dont think Trackeye will run with opencv v2.0. There have been various changes in opencv libraries after version vb3.1. Vista OS may not be the source of error. Godd luck. Sign In·View Thread·PermaLink shape extraction from images raju_Code 19:02 9 Oct '09   .i am great fan of this article ... Thanks for submitting .... currently i have developing one application , I dont know whether your program Extract shapes from images ...? if ("YES" == TRUE) MessageBox("please tell me which function can i use ?") else MessageBox("How to solve this problem") return "Please Guide me !! and Help Me" Thanks Sign In·View Thread·PermaLink Re: shape extraction from images zafersavas 12:14 3 Nov '09   It performs the following for eye feature extraction 1) Circle Detection for pupil detection 2) Snake energy minimization for eye border detection. 3) Ellipse fitting for eye border detection. Good luck zafer Sign In·View Thread·PermaLink Error in Debug mode Charles Song 16:56 7 Oct '09   Hello Thank you for your serving this code. this is very helpful for me. but I have a problem. If I compile it in release mode, It works well. If I do it in release mode, there are so many errors. ------------------------------------------------------- Compiling... Calibration4Pupil.cpp c:\program files\microsoft visual studio\vc98\include\new(35) : error C2061: syntax error : identifier 'THIS_FILE' c:\program files\microsoft visual studio\vc98\include\new(35) : error C2091: function returns function . . . . . --------------------------------------------------------- Success in release mode shows that there is no miss in configuration, I think. What can be a solution for me? I'm trying to optimize this code. Thanks. Sign In·View Thread·PermaLink Re: Error in Debug mode zafersavas 6:47 8 Oct '09   Compilation in Release Mode - OK. Compilation in Debug Mode - FAIL. So the only reason can be: the project settings are different. Please make sure the project settings in debug configuration are the same as the settings in release configuration. "Project-->Settings" Good luck zafer Sign In·View Thread·PermaLink Can't compile project [modified] Roman Tarasov 22:14 17 Sep '09   Hi, nice work. I use VC++ 6.0 and OpenCV3.1b. Everithing compiles without errors, but... when linker tries to build an EXE file from OBJ files... There are a lot of errors. All errors linked with Haar face detection algorithms. It looks like theese functions are absent in LIB files of OpenCV. The only solution I have found - don't use Haar face detection, comment all calls of them in source code and use only CAMSHIFT method whily program is running. May be I configured something wrong in project settings? ________________________ I've found a reason already. cvaux.lib wasn't placed in project settings modified on Friday, September 18, 2009 6:23 AM Sign In·View Thread·PermaLink Re: Can't compile project zafersavas 11:59 18 Sep '09   As you are using the correct opencv version, the only missing thing seems to be the project settings. Please make sure that your project settings are compatible with your opencv directories. Good luck zafer Sign In·View Thread·PermaLink 4.00/5 (1 vote) unable to remove the error of missing xcore.h and highgui.h Member 2954681 20:57 27 Aug '09   i am unable to make the program error free coz it shows problem in above 2 header files Sign In·View Thread·PermaLink Re: unable to remove the error of missing xcore.h and highgui.h zafersavas 7:59 28 Aug '09   Make sure you are using opencv b3.1 version. Sign In·View Thread·PermaLink 2.00/5 (1 vote) IplImage Display bubuzzz 22:02 8 Jul '09   I saw that you can display the capture on the window form. Can you show me the way to do that, please? I m not familiar with MFC so i used window form application with C++ and tried to display the capture from Cam on the picture box. However, everytime i change the image of the picture box, i have to refresh the control and it makes the application hang. Sign In·View Thread·PermaLink Re: IplImage Display zafersavas 8:08 9 Jul '09   This is the way: cvNamedWindow("MYWINDOW", CV_WINDOW_AUTOSIZE); HWND hWndHT = (HWND) cvGetWindowHandle("MYWINDOW"); HWND hParentHT = ::GetParent(hWndHT); ::SetParent(hWndHT, GetDlgItem(ID_MyLabel)->m_hWnd); // Here ID_Mylabel is a text label on your dialog ::ShowWindow(hParentHT, SW_HIDE); Good luck zafer Sign In·View Thread·PermaLink Re: IplImage Display bubuzzz 22:53 9 Jul '09   thank you very much Sign In·View Thread·PermaLink Re: IplImage Display st.trombetta@tiscali.it 23:03 28 Jul '09   Hi zafersavas, i'm not an expert programmer in VC++ so i understand the first part of the reply but i have the problems to understand what is ID_Mylabel. I saw, in your application, that you build the User interface with the code and not with the Microsoft tool. Is there a simple way to insert the video opened with the opencv in a window in the VC form (without building the interface manually)? Thank you for your help, Stefano Sign In·View Thread·PermaLink Re: IplImage Display zafersavas 10:29 29 Jul '09   Unfortunately there is no way to insert it without writing code. What opencv does is; it gives you a window with image displayed in it and what you have to do is to set the parent of that opencv window to a label on the form. Than instead of a separate window the opencv form is displayed on the user form. Good luck zafer Sign In·View Thread·PermaLink Re: IplImage Display st.trombetta@tiscali.it 21:26 29 Jul '09   Thank you for your answer but my problem is: if i insert a label in the form i don't have the ID (i have the name). How i can refer to the ID_label in the function GetDlgItem(???????)->m_hWnd. I don't know the ID label. If i use the name instead the ID the system gives me the error message: "the element to the left ->m_hWnd has to point to the class type, structure, union or generic". Thank you for your help, Stefano Sign In·View Thread·PermaLink Re: IplImage Display zafersavas 9:29 30 Jul '09   I dont know your c++ IDE version but in Microsoft Visual C++ 6.0 follow these steps: - you insert a static text from the control box to your dialog - right click on the text and --> properties. - Change the ID of the text from IDC_STATIC to IDC_MyLabel Thats all Hope it helps. zafer Sign In·View Thread·PermaLink Re: IplImage Display st.trombetta@tiscali.it 23:15 23 Aug '09   Hi, i use VC++ 2008 Express Edition. I'm not able to find the static text control in the tool box so i'm not able to chenge the ID and to use your procedure. Can you help me with this IDE version? Thank you, Stefano Sign In·View Thread·PermaLink A gift for me k09tranhoan 3:35 5 Jun '09   I have no words to express my gratitude. Thanks to this article I could build some simple face and eye tracing programs with video4linux. When I encountered with a problem about pupil tracking, I almost stumbled over because I'm a beginner and learning everything by myself. Once again, thank you so much. I will study your article more carefully and look forward to reading your articles in the future! God bless you! Sign In·View Thread·PermaLink Re: A gift for me zafersavas 12:16 3 Nov '09   I am glad that it's helping you. Good luck in your studies zafer Sign In·View Thread·PermaLink Error in Cvaux.hpp [modified] ablf4000 11:41 15 May '09   Hi When I got OpenCV beta 3.1 and setup and made my first Project I got many errors from cvaux.hpp file Can you describe me how you set up opencv for yourself ? I added : (compiler microsoft VS 2008 - mfc Dialog base Project ) C:\Program Files\OpenCV\cv\include C:\Program Files\OpenCV\cxcore\include C:\Program Files\OpenCV\otherlibs\highgu C:\Program Files\OpenCV\filters\ProxyTrans to tool/option /VC++ Directories /Include files and C:\Program Files\OpenCV\lib to library files and cv.lib cvaux.lib highgui.lib to my Project Propertises Linker/Input/Additional Dependencies thanks abolfazl Abolfazl Seyed Javadein modified on Saturday, May 16, 2009 8:00 AM Sign In·View Thread·PermaLink 2.00/5 (1 vote) Re: Error in Cvaux.hpp zafersavas 7:25 18 May '09   Please be sure about the version of Opencv you are using. Because Opencv b3.1 version doesn't have a directory called cxcore. You can download the b3.1 version from the following link: http://sourceforge.net/project/downloading.php?group_id=22870&filename=OpenCV_b3.1.exe&a=84416236[^] Good luck zafer Sign In·View Thread·PermaLink Unable to initialize capture problem... helloworldandpeople 0:08 5 May '09   Hi i'm new here, just want to ask whether is this software compatabile with internal USB webcam (internal webcam inside labtops)? Sign In·View Thread·PermaLink 2.25/5 (4 votes)

Last Visit: 17:59 7 Nov '09     Last Update: 17:59 7 Nov '09 123456 Next »