Tim@upenn.CSNET (Tim Finin) (06/11/86)
OBJECT RECOGNITION USING FUNCTION BASED CATEGORY MODELS
Ph. D. Thesis Proposal
Franc Solina
GRASP Laboratory
UNIVERSITY of PENNSYLVANIA
Department of Computer and Information Sciences
Philadelphia, PA 19104-6389
Phone (215) 898 8298
Net address: franc@upenn
We propose a modeling system for recognition of generic
objects. Based on the observation that fulfilling of the
same function results in similar shapes we will consider
object categories that are formed around the principle of
functionality. The representation consists of a prototypi-
cal object represented by prototypical parts and relations
between these parts. Parts are modeled by superquadric
volumetric primitives which are combined via boolean opera-
tions to form objects. Variations between objects within a
category are described by allowable changes in structure and
shape deformations of prototypical parts. Each prototypical
part and relation has a set of associated features that can
be recognized in the images. The recognition process
proceeds as follows; the input is a pair of stereo reflec-
tance images. The closed contours and sparse 3-D points,
the result of low level vision, are analyzed to find domain
specific features. These features are used for indexing the
model data base to make hypotheses. The selected hypotheses
are then verified on the geometric level by deforming the
prototype in allowable way to match the data. We base our
design of the modeling system upon the current psychological
theories of the human visual perception.
advisor: R. Bajcsy
commitee: N. Badler, H. ElGindy, J. Kender (Columbia University).
Time: Monday, June 16, 11 PM, room 216