Stereo matching as a nearest-neighbor problem
Tomasi, C.
Manduchi, R.
Dept. of Comput. Sci., Stanford Univ., CA;
This paper appears in: Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publication Date: Mar 1998
Volume: 20,
Issue: 3
On page(s): 333-340
ISSN: 0162-8828
References Cited: 31
CODEN: ITPIDJ
INSPEC Accession Number: 5903435
Digital Object Identifier: 10.1109/34.667890
Current Version Published: 2002-08-06
Abstract
We propose a representation of images, called intrinsic curves,
that transforms stereo matching from a search problem into a
nearest-neighbor problem. Intrinsic curves are the paths that a set of
local image descriptors trace as an image scanline is traversed from
left to right. Intrinsic curves are ideally invariant with respect to
disparity. Stereo correspondence then becomes a trivial lookup problem
in the ideal case. We also show how to use intrinsic curves to match
real images in the presence of noise, brightness bias, contrast
fluctuations, moderate geometric distortion, image ambiguity, and
occlusions. In this case, matching becomes a nearest-neighbor problem,
even for very large disparity values
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