Viewpoint invariant recovery of visual surfaces from sparse data
Stevenson, R.L.
Delp, E.J.
Dept. of Electr. Eng., Notre Dame Univ., IN;
This paper appears in: Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publication Date: Sep 1992
Volume: 14,
Issue: 9
On page(s): 897-909
ISSN: 0162-8828
References Cited: 47
CODEN: ITPIDJ
INSPEC Accession Number: 4272222
Digital Object Identifier: 10.1109/34.161349
Current Version Published: 2002-08-06
Abstract
An algorithm for the reconstruction of visual surfaces from sparse
data is proposed. An important aspect of this algorithm is that the
surface estimated from the sparse data is approximately invariant with
respect to rigid transformation of the surface in 3D space. The
algorithm is based on casting the problem as an ill-posed inverse
problem that must be stabilized using a priori information related to
the image and constraint formation. To form a surface estimate that is
approximately invariant with respect to viewpoint, the stabilizing
information is based on invariant surface characteristics. With
appropriate approximations, this results in a convex functional to
minimize, which is then solved using finite element analysis. The
relationship of this algorithm to several previously proposed
reconstruction algorithms is discussed, and several examples that
demonstrate its effectiveness in reconstructing viewpoint-invariant
surface estimates are given
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