Information request for object recognition papers.

[BIE...@red.rutgers.edu.uucp]

I would appreciate pointers and references to current work in object
recognition. My group is beginning work in the automation of visual
database design for real-time image generators. These databases consist
of polygonal approximations of real-world objects (everything from houses
to bushes). Currently, individual objects are constructed by hand, using
models, maps, photographs, graph paper, geometry, and lots of time and
patience. We would like to develop a modeling station which can extract
the basic geometry of objects from sets of photographs, and which can
produce good approximations to polygonal models of the regular structures,
such as buildings and other cultural features, which it recognizes in the
source photographs.

We expect that such a system will require some operator assistance for
resolving ambiguities, at least initially, but even such a system would be
of great help in the modeling task.

Although we have some papers of current work, please assume that we are
completely ignorant about who is doing what, and what the state of the
art is, and forward all references to me. I realize that there are probably
several netlists which are relevant, but I've not kept in touch with these.
Pointers to the more active and relevant of these are also appreciated.

I will summarize the responses if they are sufficiently general for this
audience, and if the volume of replies warrants it. Many thanks in advance.

Heiner BIESEL@RUTGERS

[The best collections of papers are the DARPA Image Understanding
Workshops. The February '87 proceedings have been made available
to the general public. Much of this work is oriented toward aerial
cartography (as well as target recognition). Other good papers
have appeared in recent vision conferences such as PRIP/CVPR/ICCV
and in journals such as IEEE PAMI and CVGIP.

Some of the most pertinent work is being carried out at SRI by
Pascal Fua and Andy Hanson. They have developed ways of extracting
rectilinear objects (i.e., buildings of complex shape) and are
extending their techniques to identify roads and vegetation.
One of the inputs to their system is a segmentation map derived
from my own work in computer vision. -- KIL]