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2013-01-09 10:39:03 -0500 commented answer Calculating distance from the pixel value of a disparity map

I suppose that is possible, but I only need to find the distance of, say, a single pixel, and can ignore the rest of the image. It would be a bit inefficient to calculate the 3D position of all of the image..

2013-01-09 08:44:10 -0500 asked a question Calculating distance from the pixel value of a disparity map


I have been looking for a simple solution for a while, but haven't come across anything so..

I have generated a disparity map using the OpenCV StereoBM and StereoSGBM functions and a pair of cameras. I have all of the camera parameters generated by stereo_calib. Is there a fairly straightforward way to calculate the distance using all of this information given the grayscale value of the pixel?


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2012-07-16 04:42:56 -0500 asked a question Sobel derivatives in the 45 and 135 degree direction

Hi, From the documentation, the Sobel edge detector seems to work only for horizontal and vertical direction edges (by specifying 0,1 or 1,0). Is there any way to get diagonal edges (i.e. 45deg and 135deg) with cvSobel (not cvCanny)?


UPDATE: Thanks for the suggestions! I can get what I need by rotating the image beforehand, but it is quite inefficient. I need to access the pixels for both the x-yand diagonal45-diagonal135 matrices, so by rotating the image, I incur the penalty of an extra pass over the pixels.

I've come across : sqrt((Ysin(alpha))^2 + (Xcos(alpha))^2) (where Y and X are derivatives in the y and x direction) which supposedly allows the calculation of the derivative in any direction given by alpha. However, when I try this, the results are different to when rotating the image by 45 degrees before hand. Is that expression correct? If not, how can I go about calculating the derivatives I need without rotating the image beforehand?

Many thanks.