I'm rewatching this lecture so this question might be addressed later in the lecture, but is using a window and directly comparing pixel values really a good way of matching points in the images? I was thinking that there might be multiple instances of similar features which happen to be on the same line, and it would be difficult to distinguish which is the correct one. For example, even in the images on this slide, the line passes through the top right corner of the top right window, and since this and the actual correct point are both window corners they might have similar pixel intensity distributions.
motoole2
You're absolutely right! There could very well be multiple instances of similar features on the epipolar line. This is a fundamental issue with stereo imaging, where there's no guarantee we can compute perfect correspondences (see this slide for examples on where stereo fails).
At the end of this lecture, we discussed a few strategies to improve correspondences. For example, we could use structured lighting to provide unique correspondences and get around this problem. An alternative solution is to enforce smoothness in the recovered depth map.
I'm rewatching this lecture so this question might be addressed later in the lecture, but is using a window and directly comparing pixel values really a good way of matching points in the images? I was thinking that there might be multiple instances of similar features which happen to be on the same line, and it would be difficult to distinguish which is the correct one. For example, even in the images on this slide, the line passes through the top right corner of the top right window, and since this and the actual correct point are both window corners they might have similar pixel intensity distributions.
You're absolutely right! There could very well be multiple instances of similar features on the epipolar line. This is a fundamental issue with stereo imaging, where there's no guarantee we can compute perfect correspondences (see this slide for examples on where stereo fails).
At the end of this lecture, we discussed a few strategies to improve correspondences. For example, we could use structured lighting to provide unique correspondences and get around this problem. An alternative solution is to enforce smoothness in the recovered depth map.