Hi all.
I am new to computer vision. Currently, I am doing a stereo vision
project. As I understand it, the two main stereo vision methods are
feature-based and area-based. I am required to use a feature-based
method, because I am restricted to a very specific edge-detection
algorithm (http://www.tfolsom.com/Research/Research.htm).
This edge-
detection algorithm returns information about the edges in a text file
(i.e, position, orientation, etc.).
Since the edge-detection part has already been done, the next step is
stereo matching. I have tried looking at a number of research papers
on the topic, but most of the information I was able to find was on
dense methods (non-feature-based).
I still do not know how a feature in a left image is matched with the
correct feature in the right image (and not other features). What is
the criterion that is used to match the features?
Would anyone be kind enough to point me in the right direction? I am
currently confused as to how to begin this project.
Thanks in advance.
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