Hi community, i am working on triangulation in stereo camera but i have a problem of pixel correspondence and i used SURF algorithm but this method imposes points that the algorithm has detected(feature points) and i need to pick any pixel that i need and get the correspondence and then the triangulation Can anybody suggest me other methods for image matching?
Hi Ahmed, it all depends on what you need. If you have a stereo image pair and the images are undistorted and rectified, you can follow the instruction at the link below
https://it.mathworks.com/matlabcentral/fileexchange/28522-stereo-matching
It is an example of stereo matching and the output is a pixel wise density disparity map.
if the images are not co-registered then you could use the keypoint matching approach. I suggest you to follow the approach at the link below:
https://it.mathworks.com/help/vision/ref/matchfeatures.html
For a more accurate study of the model representing the match between the local keypoint you can apply the ransac method (allowing a fit homography analysis).
Please let me know if any of these suggestions work for your purpose.
Have a good time.
Alessandro
If the images are rectified, the StereoSGBM algorithm in OpenCV is also popular for obtaining stereo disparity maps which can then be turned into 3D points.
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