ошибка в miniflann.cpp с использованием дескрипторов SURF

Я работал с Opencv в течение такого времени. На этот раз я столкнулся с проблемой, которая так сильно меня раздражала.
На самом деле у меня есть шаблон изображения, и я хочу использовать сопоставление, чтобы распознать его в потоке камеры, но я сталкиваюсь с такой консольной ошибкой:

   OpenCV Error: Unsupported format or combination of formats (type=0
) in unknown function, file ..\..\..\opencv\modules\flann\src\miniflann.cpp, lin
e 299

На самом деле это код, и он хорошо компилируется, но ошибка появляется при выполнении.

#include "stdafx.h"#include <stdio.h>
#include <iostream>
#include <fstream>
#include <string>
#include "opencv2/core/core.hpp"#include "opencv2/nonfree/features2d.hpp"#include "opencv2/features2d/features2d.hpp"//#include "opencv2/legacy/legacy.hpp"#include "opencv2/highgui/highgui.hpp"#include "opencv2/imgproc/imgproc.hpp"#include "opencv2/calib3d/calib3d.hpp"using namespace cv;
using namespace std;

int main()
{
//reference image
Mat object = imread( "tel_tmpl.jpg", CV_LOAD_IMAGE_GRAYSCALE );

if( !object.data )
{
std::cout<< "Error reading object " << std::endl;
return -1;
}

char key = 'a';
int framecount = 0;

SurfFeatureDetector detector( 500 );
SurfDescriptorExtractor extractor;
FlannBasedMatcher matcher;

Mat frame, des_object, image;
Mat des_image, img_matches, H;

std::vector<KeyPoint> kp_object;
std::vector<Point2f> obj_corners(4);
std::vector<KeyPoint> kp_image;
std::vector<vector<DMatch > > matches;
std::vector<DMatch > good_matches;
std::vector<Point2f> obj;
std::vector<Point2f> scene;
std::vector<Point2f> scene_corners(4);

//compute detectors and descriptors of reference image
detector.detect( object, kp_object );
extractor.compute( object, kp_object, des_object );

//create video capture object
VideoCapture cap(0);

//Get the corners from the object
obj_corners[0] = cvPoint(0,0);
obj_corners[1] = cvPoint( object.cols, 0 );
obj_corners[2] = cvPoint( object.cols, object.rows );
obj_corners[3] = cvPoint( 0, object.rows );

//wile loop for real time detection
while (key != 27)
{
//capture one frame from video and store it into image object name 'frame'
cap >> frame;

if (framecount < 5)
{
framecount++;
continue;
}

//converting captured frame into gray scale
cvtColor(frame, image, CV_RGB2GRAY);

//extract detectors and descriptors of captured frame
detector.detect( image, kp_image );
extractor.compute( image, kp_image, des_image );

//find matching descriptors of reference and captured image
matcher.knnMatch(des_object, des_image, matches, 2);

//finding matching keypoints with Euclidean distance 0.6 times the distance of next keypoint
//used to find right matches
for(int i = 0; i < min(des_image.rows-1,(int) matches.size()); i++)
{
if((matches[i][0].distance < 0.6*(matches[i][1].distance)) && ((int) matches[i].size()<=2 && (int) matches[i].size()>0))
{
good_matches.push_back(matches[i][0]);
}
}

//Draw only "good" matches
drawMatches( object, kp_object, frame, kp_image, good_matches, img_matches,
Scalar::all(-1), Scalar::all(-1), vector<char>(), DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS );

//3 good matches are enough to describe an object as a right match.
if (good_matches.size() >= 3)
{

for( int i = 0; i < good_matches.size(); i++ )
{
//Get the keypoints from the good matches
obj.push_back( kp_object[ good_matches[i].queryIdx ].pt );
scene.push_back( kp_image[ good_matches[i].trainIdx ].pt );
}
try
{
H = findHomography( obj, scene, CV_RANSAC );
}
catch(Exception e){}

perspectiveTransform( obj_corners, scene_corners, H);

//Draw lines between the corners (the mapped object in the scene image )
line( img_matches, scene_corners[0] + Point2f( object.cols, 0), scene_corners[1] + Point2f( object.cols, 0), Scalar(0, 255, 0), 4 );
line( img_matches, scene_corners[1] + Point2f( object.cols, 0), scene_corners[2] + Point2f( object.cols, 0), Scalar( 0, 255, 0), 4 );
line( img_matches, scene_corners[2] + Point2f( object.cols, 0), scene_corners[3] + Point2f( object.cols, 0), Scalar( 0, 255, 0), 4 );
line( img_matches, scene_corners[3] + Point2f( object.cols, 0), scene_corners[0] + Point2f( object.cols, 0), Scalar( 0, 255, 0), 4 );
}

//Show detected matches
imshow( "Good Matches", img_matches );

//clear array
good_matches.clear();

key = waitKey(1);
}
return 0;
}

заранее спасибо