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\title{Scientific Computing in Computer Vision}

\author{C. W. Gear \\
NEC Research Institute \\
4, Independence Way Princeton, NJ 08540}
\date{}
\maketitle


If a numerical analysts wishes to be an effective computational
scientist it is ofetn necessary to ``get inside'' another discipline
to understand the problem.  It is often not sufficient to simply ask
what computational problem is being solved (for example, differential
or linear equations), the source of the problem must be understood so
that a variety of tools can be brought to bear on it.

\vskip 2truemm

The advantage of looking at another field is that it can be a rich
source of new and interesting problems whose effective solution needs
to integrate techniques and ideas from diverse sub-areas of scientific
computing.

\vskip 2truemm

I am going to discuss a few problems from computer vision.  These
examples come from work at the NEC Research Institute.  They present
challenging tasks for someone with a background in numerical software
because thay are ill-posed in a very different manner from that we
usually teach students: in many cases there is no ``correct''
solution, it all depends on your point of view (pun intended).  Since
an objective of computer vision is to simulate the process that we
think occurs in the mind and the mind can be fooled by pictures
(optical illusions), we have to expect our algorithms to be fooled
also.  I will look in some detail at problems in ``segmentation'' of
moving scenes (the association of points in the image to to groujps
corresponding to the same object) and in ``illusory contours'' (the
completion of missing contours in scenes in which objects are
partially obscured).
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