Matching 3-D line segments with applications to multiple-objectmotion estimation
Chen, H.H.
Huang, T.S.
Coordinated Sci. Lab., Illinois Univ., Urbana, IL ;
This paper appears in: Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publication Date: Oct 1990
Volume: 12,
Issue: 10
On page(s): 1002-1008
ISSN: 0162-8828
References Cited: 31
CODEN: ITPIDJ
INSPEC Accession Number: 3804132
Digital Object Identifier: 10.1109/34.58872
Current Version Published: 2002-08-06
Abstract
A two-stage algorithm for matching line segments using
three-dimensional data is presented. In the first stage, a tree-search
based on the orientation of the line segments is applied to establish
potential matches. the sign ambiguity of line segments is fixed by a
simple congruency constraint. In the second stage, a Hough clustering
technique based on the position of line segments is applied to verify
potential matches. Any paired line segments of a match that cannot be
brought to overlap by the translation determined by the clustering are
removed from the match. Unlike previous methods, this algorithm combats
noise more effectively, and ensures the global consistency of a match.
While the original motivation for the algorithm is multiple-object
motion estimation from stereo image sequences, the algorithm can also be
applied to other domains, such as object recognition and object model
construction from multiple views
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