Stereo correspondence through feature grouping and maximal cliques
Horaud, R.; Skordas, T.
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Volume 11, Issue 11, Nov 1989 Page(s):1168 - 1180
Digital Object Identifier 10.1109/34.42855
Summary:The authors propose a method for solving the stereo correspondence
problem. The method consists of extracting local image structures and
matching similar such structures between two images. Linear edge
segments are extracted from both the left and right images. Each segment
is characterized by its position and orientation in the image as well as
its relationships with the nearby segments. A relational graph is thus
built from each image. For each segment in one image as set of potential
assignments is represented as a set of nodes in a correspondence graph.
Arcs in the graph represent compatible assignments established on the
basis of segment relationships. Stereo matching becomes equivalent to
searching for sets of mutually compatible nodes in this graph. Sets are
found by looking for maximal cliques. The maximal clique best suited to
represent a stereo correspondence is selected using a benefit function.
Numerous results obtained with this method are shown
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