A spherical representation for recognition of free-form surfaces
Hebert, M.
Ikeuchi, K.
Delingette, H.
Robotics Inst., Carnegie Mellon Univ., Pittsburgh, PA;
This paper appears in: Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publication Date: Jul 1995
Volume: 17,
Issue: 7
On page(s): 681-690
ISSN: 0162-8828
References Cited: 23
CODEN: ITPIDJ
INSPEC Accession Number: 5000959
Digital Object Identifier: 10.1109/34.391410
Current Version Published: 2002-08-06
Abstract
Introduces a new surface representation for recognizing curved
objects. The authors approach begins by representing an object by a
discrete mesh of points built from range data or from a geometric model
of the object. The mesh is computed from the data by deforming a
standard shaped mesh, for example, an ellipsoid, until it fits the
surface of the object. The authors define local regularity constraints
that the mesh must satisfy. The authors then define a canonical mapping
between the mesh describing the object and a standard spherical mesh. A
surface curvature index that is pose-invariant is stored at every node
of the mesh. The authors use this object representation for recognition
by comparing the spherical model of a reference object with the model
extracted from a new observed scene. The authors show how the similarity
between reference model and observed data can be evaluated and they show
how the pose of the reference object in the observed scene can be easily
computed using this representation. The authors present results on real
range images which show that this approach to modelling and recognizing
3D objects has three main advantages: (1) it is applicable to complex
curved surfaces that cannot be handled by conventional techniques; (2)
it reduces the recognition problem to the computation of similarity
between spherical distributions; in particular, the recognition
algorithm does not require any combinatorial search; and (3) even though
it is based on a spherical mapping, the approach can handle occlusions
and partial views
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