Stereo correspondence through feature grouping and maximal cliques

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 p...

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Bibliographic Details
Published in:IEEE transactions on pattern analysis and machine intelligence 1989-11, Vol.11 (11), p.1168-1180
Main Authors: Horaud, R., Skordas, T.
Format: Article
Language:English
Subjects:
Applied sciences
Artificial intelligence
Computer Science
Computer science
control theory
systems
Exact sciences and technology
Extraterrestrial measurements
Geometry
Graphics
Image segmentation
Image sensors
Layout
Pattern recognition. Digital image processing. Computational geometry
Stereo vision
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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.< >
ISSN:0162-8828
1939-3539
DOI:10.1109/34.42855