Superquadrics for segmenting and modeling range data
Leonardis, A.
Jaklic, A.
Solina, F.
Comput. Vision Lab., Ljubljana Univ.;
This paper appears in: Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publication Date: Nov 1997
Volume: 19,
Issue: 11
On page(s): 1289-1295
ISSN: 0162-8828
References Cited: 22
CODEN: ITPIDJ
INSPEC Accession Number: 5783683
Digital Object Identifier: 10.1109/34.632988
Current Version Published: 2002-08-06
Abstract
We present an approach to reliable and efficient recovery of
part-descriptions in terms of superquadric models from range data. We
show that superquadrics can directly be recovered from unsegmented data,
thus avoiding any presegmentation steps (e.g. in terms of surfaces). The
approach is based on the recover-and-select paradigm. We present several
experiments on real and synthetic range images, where we demonstrate the
stability of the results with respect to viewpoint and noise
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