3D Euclidean versus 2D non-Euclidean: two approaches to 3D recoveryfrom images
Kanatani, K.-I.
Dept. of Comput. Sci., Gunma Univ.;
This paper appears in: Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publication Date: Mar 1989
Volume: 11,
Issue: 3
On page(s): 329-332
ISSN: 0162-8828
References Cited: 23
CODEN: ITPIDJ
INSPEC Accession Number: 3383959
Digital Object Identifier: 10.1109/34.21802
Current Version Published: 2002-08-06
Abstract
Methods of 3D recovery in computer vision for computing the shape
and motion of an object from projected images when an object model is
available are classified into two types: the 3D Euclidean approach,
which is based on geometrical constraints in 3D Euclidean space, and the
2D non-Euclidean space. Implications of these two approaches are
discussed, and some illustrating examples are presented
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