A stereo vision technique using curve-segments and relaxationmatching
Nasrabadi, N.M.
Dept. of Electr. Eng., Worcester Polytech. Inst., MA;
This paper appears in: Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publication Date: May 1992
Volume: 14,
Issue: 5
On page(s): 566-572
ISSN: 0162-8828
References Cited: 10
CODEN: ITPIDJ
INSPEC Accession Number: 4185379
Digital Object Identifier: 10.1109/34.134060
Current Version Published: 2002-08-06
Abstract
A multichannel feature-based stereo vision technique where curve
segments are used as feature primitives in the matching process is
described. The left image and the right image are filtered by using
several Laplacian-of-Gaussian operators of different widths (channels).
Curve segments are extracted by a tracking algorithm, and their
centroids are obtained. At each channel, the generalized Hough transform
of each curve segment in the left and the right image is evaluated. The
epipolar constraint on the centroids of the curve segment and the
channel size is used to limit the searching space in the right image. To
resolve the ambiguity of the false targets (multiple matches), a
relaxation technique is used where the initial scores of the node
assignments are updated by the compatibility measures between the
centroids of the curve segments. The node assignments with the highest
score are chosen as the matching curve segments
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