c++ - Eye Blinking Detection -

some warnings appear in terminal during running:

opencv error: assertion failed(s>=0) in setsize, file /home/me/opencv2.4/modules/core/src/matrix.cpp, line 116

the program compiled without error , executes, problem eye roi size changes when user moves closer/farther away webcam, due changing of size, warning appears. managed solve these warnings setting eye roi size equal eye template size. however, ends program fails classify user's eyes open/close because minval obtained 0. method used opencv template matching. alternatively, fix distance webcam , fix eye template size avoid warning. every time warning appears, program fails classify open/close eyes. program doesn't work because mistakenly classifies open eyes closed , vice versa.

questions:

1. is there alternative identify open , close eyes other template matching?

2. any ideas how improve program in classification of blinking?

3. any working example know in opencv c/c++ api can classify open , close eyes , count accurately blinking times?

    static cvmemstorage* storage = 0;    // create new haar classifier    static cvhaarclassifiercascade* cascade = 0;    // function prototype detecting , drawing object image    bool detect_and_draw( iplimage* image ,cvhaarclassifiercascade* cascade);     const char *cascade_name[1]={"eyes.xml"};    cv::mat roiimg;    int threshold_value = 200;    int threshold_type = 3;;    int const max_value = 255;    int const max_type = 4;    int const max_binary_value = 255;    int hough_thr = 35;    cv::mat src_gray, dst;    using namespace cv;    mat img1; mat img2; mat templ; mat result;    const char* image_window = "source image";    const char* result_window = "result window";    int match_method=0;    int max_trackbar = 5;    int eye_open=0;    int eye_close=0;     //matching 2 images ,eye closed or open    void matchingmethod(cv::mat templ,int id )    {     /// source image display     cv::mat img_display;     roiimg.copyto( img_display );     /// create result matrix     int result_cols = roiimg.cols - templ.cols + 1;     int result_rows = roiimg.rows - templ.rows + 1;     result.create( result_cols, result_rows, cv_32fc1 );     /// matching , normalize     cv::matchtemplate( roiimg, templ, result, match_method );     cv::normalize( result, result, 0, 1, norm_minmax, -1, mat() );     /// localizing best match minmaxloc     double minval; double maxval; point minloc; point maxloc;     cv::point matchloc;     cv::minmaxloc( result, &minval, &maxval, &minloc, &maxloc, mat() );     ///justing checkin match template value reaching threashold     if(id == 0 && (minval < 0))         {         eye_open=eye_open+1;         if(eye_open == 1)              {              std::cout<<"eye open"<<std::endl;              eye_open=0;              eye_close=0;              }         }      else if(id == 1 && (minval < 0))         eye_close=eye_close+1;         if(eye_close == 1)              {              std::cout<<"eye closed"<<std::endl;              eye_close=0;              system("python send_arduino.py");              }     /// sqdiff , sqdiff_normed, best matches lower values. other methods, higher better     if( match_method == cv_tm_sqdiff || match_method == cv_tm_sqdiff_normed )      { matchloc = minloc; }     else      { matchloc = maxloc; }     /// show me got     cv::rectangle( img_display, matchloc, point( matchloc.x + templ.cols , matchloc.y + templ.rows ), scalar::all(0), 2, 8, 0 );     cv::rectangle( result, matchloc, point( matchloc.x + templ.cols , matchloc.y + templ.rows ), scalar::all(0), 2, 8, 0 );     cv::imshow( image_window, img_display );     cv::imshow( result_window, result );     return;    }    void detect_blink(cv::mat roi)    {         try         {               matchingmethod(img1,0);          matchingmethod(img2,1);         }         catch( cv::exception& e )         {              std::cout<<"an exception occued"<<std::endl;         }    }    // main function, defines entry point program.    int main( int argc, char** argv )    {      if(argc <= 1)         {         std::cout<<"\n "<<std::endl;         std::cout<<"\n ------------------------------------\n"<<std::endl;         std::cout<<"./blink_detect open_eye.jpg close_eye.jpg\n"<<std::endl;        std::cout<<"eg :: ./blink_detect 2.jpg 3.jpg\n"<<std::endl;         std::cout<<"\n ------------------------------------\n"<<std::endl;         exit(0);         }      // structure getting video camera or avi      cvcapture* capture = 0;      // images capture frame video or camera or file      iplimage *frame, *frame_copy = 0;      // used calculations      int optlen = strlen("--cascade=");      // input file name avi or image file.      const char* input_name;       img1 = imread( argv[1], 1 );       img2 = imread( argv[2], 1 );      // load haarclassifiercascade       /// create windows       cv::namedwindow( image_window, cv_window_autosize );       cv::namedwindow( result_window, cv_window_autosize );      // allocate memory storage      storage = cvcreatememstorage(0);      capture = cvcapturefromcam( 0);      // create new named window title: result      cvnamedwindow( "original_frame", 1 );      // if loaded succesfully, then:      if( capture )      {        // capture camera.        for(;;)        {          // capture frame , load in iplimage          if( !cvgrabframe( capture ))            break;          frame = cvretrieveframe( capture );          // if frame not exist, quit loop          if( !frame )            break;          // allocate framecopy same size of frame          if( !frame_copy )            frame_copy = cvcreateimage( cvsize(frame->width,frame->height),                          ipl_depth_8u, frame->nchannels );          // check origin of image. if top left, copy image frame frame_copy.           if( frame->origin == ipl_origin_tl )            cvcopy( frame, frame_copy, 0 );          // else flip , copy image              for(int i=0;i<1;i++)              {           cascade = (cvhaarclassifiercascade*)cvload( cascade_name[i], 0, 0, 0 );           // check whether cascade has loaded successfully. else report , error , quit           if( !cascade )                {                   fprintf( stderr, "error: not load classifier cascade\n" );                   return -1;                }          // call function detect , draw face               if(detect_and_draw(frame_copy,cascade))              {                   std::cout<<"detected"<<std::endl;              }                                            }          // wait while before proceeding next frame          if( cvwaitkey( 1 ) >= 0 )           break;       }        // release images, , capture memory        cvreleasehaarclassifiercascade(&cascade);        cvreleaseimage( &frame_copy );        cvreleasecapture( &capture );        cvreleasememstorage(&storage);      }     return 0;    }    // function detect , draw faces present in image    bool detect_and_draw( iplimage* img,cvhaarclassifiercascade* cascade )    {      int scale = 1;      // create new image based on input image      iplimage* temp = cvcreateimage( cvsize(img->width/scale,img->height/scale), 8, 3 );      // create 2 points represent face locations      cvpoint pt1, pt2;      int i;      // clear memory storage used before      cvclearmemstorage( storage );      // find whether cascade loaded, find faces. if yes, then:      if( cascade )      {        // there can more 1 face in image. create growable sequence of faces.        // detect objects , store them in sequence        cvseq* faces = cvhaardetectobjects( img, cascade, storage,                          1.1, 8, cv_haar_do_canny_pruning,                          cvsize(40, 40) );        // loop number of faces found.        for( = 0; < (faces ? faces->total : 0); i++ )        {          // create new rectangle drawing face          cvrect* r = (cvrect*)cvgetseqelem( faces, );          // find dimensions of face,and scale if necessary          pt1.x = r->x*scale;          pt2.x = (r->x+r->width)*scale;          pt1.y = r->y*scale;          pt2.y = (r->y+r->height)*scale;          // draw rectangle in input image          cvrectangle( img, pt1, pt2, cv_rgb(255,0,0), 3, 8, 0 );          cv::mat image(img);          cv::rect rect;          rect = cv::rect(pt1.x,pt1.y,(pt2.x-pt1.x),(pt2.y-pt1.y));          roiimg = image(rect);            cv::imshow("roi",roiimg);         ///send arduino          detect_blink(roiimg);        }      }       cvshowimage( "original_frame", img );      if(i > 0)              return 1;         else              return 0;       cvreleaseimage( &temp );    } 

reference: website referred