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2016-03-18 11:42:48 -0500 commented answer Moving object classification

Thank you for the advice. I wasn't planning to recognize objects before but then I thought of extending the project to recognition of objects. My opencv folder has xml files only for full body eyes face smile license plate I couldn't find one for cars.I tried it with few other cascades available online for cars but no luck.

2016-03-18 11:35:50 -0500 commented answer Moving object classification

The aspect ratio of the object changes as the take turns around the junction the ROI works well but I am detecting car with a red bounding box and bikes with blue. Is there a way to detect contour in a region and then set the color for the entire time the object is in the frame?

2016-03-17 04:33:29 -0500 asked a question Moving object classification

My project requires me to track road traffic parameters from a stationary camera.

I have tracked moving features using optical flow farneback algorithm, created a binary image with white blob on the moving object. Now, my want to classify them as cars or motorbikes.

I tried using the blob area but the problem is the contour/blob area increases or decreases as the object comes closer or away from the camera.

Any suggestion on how can I tackle this issue?

Binary image:

Output Image:

2016-02-15 16:26:16 -0500 commented answer unresolved external symbol : xfeatures2d problem with SIFT

how to do it?

2016-02-08 23:30:19 -0500 received badge  Enthusiast
2016-01-26 00:55:37 -0500 received badge  Editor (source)
2016-01-26 00:54:18 -0500 asked a question I need to track roads and later vehicles in an aerial video[snapshot in description] how to approach the problem?
2016-01-24 00:33:59 -0500 asked a question Why does namedwindow("Original Image",CV_WINDOW_AUTOSIZE) show a debug error on running exe whilenamedwindow("Original Image",1) doesn't?

double alpha; /**< Simple contrast control */

int beta; /**< Simple brightness control */

int main( int argc, char** argv )

{ Mat image = imread( argv[1] );

Mat new_image = Mat::zeros( image.size(), image.type() );

cout<<"* Enter the alpha value [1.0-3.0]: ";cin>>alpha; cout<<"* Enter the beta value [0-100]: ";cin>>beta;

/// Do the operation new_image(i,j) = alpha*image(i,j) + beta

for( int y = 0; y < image.rows; y++ )

{ for( int x = 0; x < image.cols; x++ )

{ for( int c = 0; c < 3; c++ )
     {<vec3b>(y,x)[c] =saturate_cast<uchar>( alpha*(<vec3b>(y,x)[c] ) + beta );




namedWindow("Original Image", 1);

namedWindow("New Image", 1);

imshow("Original Image", image);

imshow("New Image", new_image);


return 0;