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To recognise individual objects in a digital image, there are two
problems that need to be solved:
- given a collection of named objects, construct a computer
representation or model of each object, and
- given a digitized sensor image (intensity or range data, for
example), find either or all of the following:
- 1.
- an identity or name,
- 2.
- the location, and
- 3.
- the orientation
of each object in the scene.
An example occurs in the polyhedral world where the task is to match
predicted and observed line labelings through a graph isomorphism
or endomorphism search. We will consider this in more detail later,
but will first concentrate on some of the common modelling schemes
used in computer vision.
Figure:
From image capture of the real world to object recognition.
![\begin{figure}
\par
\centerline{
\psfig {figure=figure1.ps,width=10cm,angle=-90}
}
\par\end{figure}](img1.gif) |
Robyn Owens
10/29/1997