Basic Approach for Depth Map from Stereo Images.

We have the basic knowledge that there are binocular disparities in stereo images, which means if the object is closer to the camera, the position difference of it in two images will be larger. (Assume the orientation of the two cameras are the same, they only differs in position)

I took 2 images from my cell phone (really low quality):

I reused the code from my image mosaic project, it loads two images, runs ANMS, extracts the features, map the features and launches RANSAC (with lose threshold, just roughly get out the ridiculous mapping) to get the match. This is the normalize map of the position difference:

Then I realized because of the ANMS, we have included too much low corner response points. So I ran it again without ANMS, and this time, the result is a little bit better:

We are still trial and error in the first step. In this step, we need to know the exact depth distance rather than the relative depth. We plan to count the length focal of the two cameras into our calculation.