DocumentCode :
1235142
Title :
Camera geometries for image matching in 3-D machine vision
Author :
Alvertos, Nicolas ; Brzakovic, D. ; Gonzalez, Rafael C.
Author_Institution :
Dept. of Electr. & Comput. Eng., Tennessee Univ., Knoxville, TN, USA
Volume :
11
Issue :
9
fYear :
1989
fDate :
9/1/1989 12:00:00 AM
Firstpage :
897
Lastpage :
915
Abstract :
The location of a scene element can be determined from the disparity of two of its depicted entities (each in a different image). Prior to establishing disparity, however, the correspondence problem must be solved. It is shown that for the axial-motion stereo camera model the probability of determining unambiguous correspondence assignments is significantly greater than that for other stereo camera models. However, the mere geometry of the stereo camera system does not provide sufficient information for uniquely identifying correct correspondences. Therefore, additional constraints derived from justifiable assumptions about the scene domain and from the scene radiance model are utilized to reduce the number of potential matches. The measure for establishing the correct correspondence is shown to be a function of the geometrical constraints, scene constraints, and scene radiance model
Keywords :
computer vision; computerised pattern recognition; 3D machine vision; axial-motion stereo camera model; camera geometry; computer vision; geometrical constraints; image matching; pattern recognition; scene constraints; scene domain; scene radiance model; Cameras; Geometry; Humans; Image matching; Layout; Machine vision; Optical sensors; Robot vision systems; Stereo vision; Visual system;
fLanguage :
English
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher :
ieee
ISSN :
0162-8828
Type :
jour
DOI :
10.1109/34.35494
Filename :
35494
Link To Document :
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