From: Vision-List-Request@ADS.COM (Vision-List moderator Phil Kahn)
Newsgroups: comp.ai.vision
Subject: VISION-LIST digest 11.43
Date: 15 Dec 92 21:55:20 GMT
Reply-To: Vision-List@ads.com
Distribution: inet
Organization: The Internet

VISION-LIST Digest    Tue Dec 15 13:55:20 PDT 92     Volume 11 : Issue 43

 - ***** The List is moving sites soon: you will be notified ****
 - Send submissions to Vision-List@ADS.COM
 - Vision List Digest available via COMP.AI.VISION newsgroup
 - If you don't have access to COMP.AI.VISION, request list 
   membership to Vision-List-Request@ADS.COM
 - Access Vision List Archives via anonymous ftp to FTP.ADS.COM

Today's Topics:

 Re: Request for Road Images
 request for Kanji characters
 Non-Rigid Recognition
 Signal to Noise ratio Question
 Plausible pattern recognition (Info needed)
 Help!  Energy Reduction Algorithm for SP
 Optical Music Recognition - Bibliography aviable
 LaboImage 4.0: new X11 version
 Studentships
 Doctoral Program in Philosophy-Psychology-Neuroscience
 Special issue of the machine vision and applications
 AAAI '93 : Call for Papers
 CFP: Geometric Methods in Computer Vision
 Sun Pix (long)
 References on automatic face recognition (long)
 Snakes: summary of responses (long)

----------------------------------------------------------------------

Date: Fri, 04 Dec 92 09:20:27 +1100
Subject: Re: Request for Road Images
From: stevea@vast.unsw.edu.au

>From Vision-List digest 11.42:

I am interested to get sequence of road images (24 bits color) taken
from a mo ving car. Road sign of any type should be visible along the
road.

	There are several places you can get this sort of imagery.
Probably the best site though is cicero.cs.umass.edu, which is the home
site of Allen R. Hanson and Edward M. Riseman (of image segmentation
fame). They have a great liking for roadside images in their
experimental results, and there are many samples there. Please note
though, that not all of them have road signs in them. The directories
you probably want most are area_road_scenes and amherst_roads.
	Another site that has a set of images that may be helpful is
isy.liu.se, which has a video sequence taken from inside a car. This
sequence contains one prominent road sign, and possibly one or two more
further away from the camera involving road works.
	I hope this info is useful for you.

	cheers
	-steve

Steve Avery                   | VLSI and Systems Technology Laboratory,
(PhD type student person)     | School of Computer Science & Engineering,
                              | University of New South Wales,
stevea@vast.unsw.edu.au       | P.O. Box 1, Kensington, 2033, Australia.

     "Why have you two eyes and just one mouth?"  -Ryuchi Sakamoto

Here is the content of the file README.image_files that is located
in the home directory at this site:


This directory contains the image library of the VISIONS group at
UMass/Amherst.  Each sub-directory contains a specific sort of image: 
Typically the name of the directory suggests the sort of images in the
directory.

There is also an interactive DB of image descriptions available.  Telneting
in as 'visimgdb' to cicero.cs.umass.edu will place you in an interactive
program which will allow you to search a data base of image descriptions.
The data base and the program to access are also available for FTP'ing
in the directory imdb (the data base is vis-imagedb.ilb* and the program
source is in image_db.tar.Z).

Most of the image data is in what we call "Universal Plane File
Format" - this is a variation of our LLVS plane file format.  The
directory 'universal_plane_file_format' contains documentation
describing this format as well as code to read these files on several
different platforms.  These plane files always have an extension of
'.plane'.  Plane files should always be transfered in binary mode.

If you have questions or can't find a particular sort of image, let us
know by sending E-Mail to me Robert Heller (systems programmer)
<heller@cs.umass.edu> or Val Conti (Lab Manager) <conti@cs.umass.edu>.

Jan-15-1991 - by popular request, some of the motion data files have been
collected into tar files and compressed.  Also, all of the files in
'universal_plane_file_format' have also been collected into a tar file
and compressed.  This has been done to make FTP'ing easier.  RPH.

------------------------------

Date: Mon, 14 Dec 92 09:31 JST
From: SHARONE%HADASSAH@VMS.HUJI.AC.IL
Subject: request for Kanji characters

A friend of mine needs for his research in Pattern Recognition
a set of contours from KANJI characters.
Email or pointers to a FTP site are welcomed.

Thanks in Advance.
Haim Karger
Dept of Nuclear Medecine

------------------------------

From: brian@ai.mit.edu (Brian Subirana)
Date: Mon, 14 Dec 92 09:23:35 EST
Subject: Non-Rigid Recognition

I am interested in collecting references on non-rigid objects for a
survey that I am writing.  Particularly, but not exclusively, recent
ones on the recognition of non-rigid objects.

Pointers are most welcomed,

Brian Subirana
MIT AI Lab
Email: brian@ai.mit.edu

------------------------------

Date: Sat, 12 Dec 1992 19:19:51 -0500
From: kwon lim <lim@silver.ucs.indiana.edu>
Subject: Signal to Noise ratio Question

Could someone tell me if the following phrase make sense ?

"A signal to noise ratio of a SAR image is 1 or 2".

My question is: Is it possible to assert the signal to noise ratio
of a two dimension signal(say grey scale image) without considering
some noise model.  It seems like there is some way of obtaining the
signal to noise ratio as a measure of how good or bad the signal is.
In other words, my question boils down to the one of how to separate
signal and noise component.  Any ideas or references will be
appreciated.
Thanks in advance.

------------------------------

Date: Fri, 4 Dec 1992 02:44:31 GMT
From: yang@dante.cs.uiuc.edu (Der-Shung Yang)
Organization: University of Illinois, Dept. of Comp. Sci., Urbana, IL
Subject: Plausible pattern recognition (Info needed)
Keywords: plausible pattern recognition

Hi, I'm doing some research on pattern recognition.  The domain I'm working
on has a special feature that seems interesting (at least to me:-) in general.
I'm looking for any special technique that handles this situation or any
opinions on whether this feature exists in any other domains.

I'm trying to develop a system to recognize what a user is drawing on a CAD
(Computer-Aided Design) screen.  This looks like a very general pattern 
recognition problem.  However, in this domain, there's no need for "perfect
recognition."  That is, my system only needs to suggest a fixed number of
objects that look similar to what the user is drawing, possibly ranked by
the "similarity" between the suggested object and the user's input, with the
most similar one output first.  So, a good system should output the target
object as soon as possible, but not necessarily get it right at the first place.
I call this type of problem "plausible pattern recognition," meaning that the 
recognition only needs to make plausible suggestions, not the perfect one.

To me, this type of problem seems to reduce the difficulty of recognition
and is more doable than trying to find a "perfect" system.  If you came
across something similar to this type of problem or have some opinions on 
whether "plausible PR" is important theoretically or practically, please let
me know.  Both emails and followups are welcome.  Comments, references, and/or
critics are all greatly appreciated.

DerShung Yang    
yang@cs.uiuc.edu 
Beckman Institute
Univ. of Illinois at Urbana-Champaign

------------------------------

Date: Fri, 11 Dec 92 19:30:52 EST
From: ge@acsu.buffalo.edu (Wang Ge)
Subject: Help!  Energy Reduction Algorithm for SP

Dear Colleagues,

I once heard of the energy reduction algorithm
for recovering a signal on an interval from
its known values on other intervals.
Would you please give me some pointers to
recent papers and public software (C is preferred).
Thank you very much!

Ge
 
------------------------------

Date: Mon, 14 Dec 1992 13:05:12 GMT
From: roth@sitter.ips.id.ethz.ch (Martin Roth)
Organization: ETH Zurich (Swiss Federal Institute of Technology)
Subject: Optical Music Recognition - Bibliography aviable

I compiled a bibliography for Optical Music Recognition (automatic
reading a scanned-in page of music, pattern recognition).

PostScript and BibTeX files are aviable via ftp from maggia.ethz.ch
(129.132.17.1), login ftp, directory /pub/roth/omrbib.

If you can't use ftp or can't uncompress *.Z files, drop me a mail.

Comments, additions about new publications are welcome!

      _   Martin Roth                Martin Roth      ETHZ, ips, RZ F16
|\  /|_)  Mail: roth@ips.id.ethz.ch  Sandacker 14   ETHZ, ti, IFW B45.2
| \/ | \  Dipl. Eng. Comp. Sci. ETH  CH-8154 Oberglatt   g 01/256 55 68
          (F-)emails welcome!        Switzerland         p 01/850 32 75

------------------------------

Date: Wed, 9 Dec 1992 14:39:01 +0100
From: Alain Jacot-Descombes <jacot@cui.unige.ch>
Subject: LaboImage 4.0: new X11 version

[ A new version of LaboImage was just installed in the Vision List Archive
SHAREWARE subdirectory. Thanks to the unige group!
				phil...		]

LABOIMAGE

Original notice

March 8th, 1989: LaboImage 2.0 (SunView)
August 24th, 1990: LaboImage 3.0 (SunView)
March 19th, 1991: LaboImage 3.1 (SunView)
December 1st, 1992: LaboImage 4.0 (X11 / OSF Motif)
Computer Science Center, University of Geneva, Switzerland

Thank you for your interest in LaboImage!


GENERAL DESCRIPTION
Labo Image is a window based software for image processing and analysis. It
contains a comprehensive set of operators as well as general utilities. It
is designed to be open-ended; new modules can easily be added. The software,
written in C, is now based on X11 / OSF Motif. The current version has been
developped and tested on a Sun SPARC station, with X11r4 and Motif 1.1.
LaboImage has been extensively used by students as well as researchers from
various domains: computer science (image analysis), medicine, biology, physics.
It is distributed free of charge (source code).

STATUS

Version 4.0, 1st December 1992:

    - hosts: Sun SPARC station;
    - OS: 4.1.1;
    - window system: X11r4 / Motif 1.1;
    - language: C;
    - approx. code size: source 2.5MB (80'000 lines), executable 2.5MB;
    - documentation: interactive help (english)

MEANS OF DISTRIBUTIONS

LaboImage source code is available by anonymous ftp at:
1) ftp.ads.com, login name anonymous, in pub/VISION-LIST-ARCHIVE/SHAREWARE.
2) peipa.essex.ac.uk, login name anonymous, in ipa/proc-src.
If you have no access to ftp, please contact the author.
If you wish to be kept current with update, error reports, ..., please send
us a mail with your full name, regular and electronic addresses.

DISTRIBUTION POLICY

In essence:
    - this is a non-profit software, but it is our property and the copyright
      notice must appear;
    - the reference to cite in case of published results obtained with Labo
      Image is: "A. Jacot-Descombes, M. Rupp, T. Pun: `LaboImage: A portable
      window-based environment for research in image processing and analysis',
      SPIE Symposium on Electronic Imaging Science and Technology, Image
      Processing: Implementation and Systems, San Jose, California, USA,
      Feb. 9-14, 1992.
    - no responsibility is assumed;
    - not to be used for profit making purposes;
    - bugs will usually be corrected since we use the software intensively ;
    - modifications should be communicated to us, with (normally) allowance
      for redistribution.

PAYMENT

Athough LaboImage has undergone many upgrades and suffered in the hands of 
many users, the current version is certainly not bug free. For the time being,
we require NO prepayment, return postage or anything. 
We may however change this policy in the future, and ask for nominal fees to
cover material expenditures. HOWEVER, if you are satisfied with the product,
why not send us some "souvenir" (post card, drink, etc.)) from your country...??!!

CAPABILITIES

Labo Image is an interactive software, whose interface is menu, mouse and 
window based. Its main features are:
    - input-output: LaboImage format file, SUN raster file; postscript;
    - display: mono, RGB, dithering, color table editor;
    - preprocessing: filters (median, high pass, low pass: hamming, gauss, etc),
	    background subtraction, histogram equalization;
    - processing: thresholding, Fourier transforms, edge extractions: various
	    operators, ridge-riding, zero-crossing; segmentation into regions,
	    binary and gray tone mathematical morphology;
    - measures: histograms, image statistics, power, region outlining, 
	    object counting;
    - auxiliary: conversions, arithmetic & logical operations, noise addition,
	    image generation, magnification, convolution/correlation with
	    masks, image; padding;
    - elementary interactive operations: region outlining, statistics and
	    histogram computation, etc.;
    - special tools: 
	    - modify image at pixel level interactively,
	    - one-dimensional gel analysis,
	    - expert system for image segmentation (not implemented in LaboImage 4.0);
    - macros definitions, save and replay (not implemented in LaboImage 4.0);
    - on line documentation.

IMAGE FORMATS

Own format: descriptor file + data file (binary, byte, int, float, complex;
mono or RGB). Supports also Sun raster format. Conversions to various other 
formats.
Data structures:
    - iconic (pixel-based), with each image having its own parameter list;
    - vectors (histograms, look-up tables);

MISCELLANEOUS REMARKS (answers to commonly asked questions)


 - FILE FORMAT: we decided to go for: 1) a machine independant format; 2) a
   simple, data (ie. signal) oriented format. At the beginning of the
   development (summer 1987), we were not aware of any image format used by
   the whole community. There seems now to be some progress on the matter
   (TIFF, etc.), but they are still not that widely used in the community.
   Also, due to development priorities we consider conversion routines a more
   secondary issue as long as our format is simple. 
   In addition, the menu "ACQUISITION=>free byte format" is fairly versatile.
   Also, the SUN raster images can now be read into LaboImage and likewise
   images on system may be stored in SUN raster format.
   However.. we would welcome any software contribution!

 - 3D IMAGE PROCESSING: nothing special for such images.

 - ON LINE HELP: available.

ACKNOWLEDGEMENTS

More than 10 people have so far participated in this project, and their
contribution is gratefully acknowledged.
Staff: Pierre-Yves Burgi, Claudia Coiteux-Rosu, Ziping Hu, Alain Jacot-
Descombes, Rene Lutz, Christian Pellegrini, Thierry Pun, Marianne Logean-
Rupp, Krassimir Todorov.
Students: Anne Bobillier, Alain Brunner, Markus Buchi, Christian Girard,
Rene Perrier, Vrinda Shukla. 
Amongst them, A. Jacot-Descombes is responsible for general design issues, 
and is the keystone for implementation; R. Lutz is responsible for display
manipulations (Color Table Editor,etc.); T. Pun is responsible for the 
original layout and general design issues;
V. Shukla is responsible for the upgrade from LaboImage 2.0 to LaboImage 3.0;
Marianne Logean-Rupp is responsible for the portability of LaboImage to X11
(LaboImage 4.0).
We are particularly grateful to Drs. D. F. Hochstrasser and O. Ratib, Digital
Imaging Unit, Computer Center, University Hospital of Geneva, for their
extended support. LaboImage 4.0 could not have been without their help.

CONTACTS

Particular problems will be redirected to relevant persons, but we prefer
that all communications be made to the same address:
e-mail: "pun@uni2a.unige.ch" or pun@cgeuge51.bitnet (if this fails,
	"pun@cui.unige.ch").
tel.: +(4122) 705 76 27 (T. Pun), 705 76 30 (A. Jacot-Descombes).
fax:  +(4122) 320 29 27.
postal address: Thierry Pun
                LaboImage
                Computing Science Center, University of Geneva
                24, rue du General-Dufour
                CH - 1211 Geneva 4
		SWITZERLAND

------------------------------

Date: Fri, 4 Dec 92 14:22:34 GMT
From: M.Petrou@ee.surrey.ac.uk
Subject: studentships

                          UNIVERSITY OF SURREY 

          Research Studentships - Image Processing/Computer Vision 

Three research studentships are available from 15 January 1993 to carry out PhD research 
in the Vision Speech and Signal
Processing Research Group of  the Department of Electronic  and Electrical 
Engineering with extensive computing resources including SUN sparc stations
as well as speciliased image processing facilities.  

The studentships are in the following areas:
         - 3D object recognition with emphasis on active vision 
         - Image processing for remote sensing to study contextual multispectral
             image classification.
         - Automatic inspection of colour texture surfaces.

Succesfull applicants will have a very good degree in Computer
Science, Physics, Electrical Engineering or Mathematics with
dedication to and apptitude for research.  The value of the
studentships will be set at or above the SERC rates depending on the
circumstances.

Further information and application forms may be obtained from Professor 
J Kittler on +44 483 509294, email: J.Kittler@ee.surrey.ac.uk,  or at
the  Department of Electronic and Electrical Engineering,
University of Surrey, Guildford, Surrey
GU2 5XH United Kingdom.  

------------------------------

Date: Tue, 15 Dec 92 16:43:25 GMT
From: Andy Clark <andycl@syma.sussex.ac.uk>
Subject: Doctoral Program in Philosophy-Psychology-Neuroscience

       First Announcement of a New Doctoral Programme in

             PHILOSOPHY-NEUROSCIENCE-PSYCHOLOGY
                             at
             Washington University in St. Louis

The Philosophy-Neuroscience-Psychology (PNP) program
offers a unique opportunity to combine advanced
philosophical studies with in-depth work in Neuroscience
or Psychology. In addition to meeting the usual requirements for
a Doctorate in Philosophy, students will spend one year working in
Neuroscience or Psychology. The Neuroscience option will draw
on the resources of the Washington University
School of Medicine which is an internationally acknowledged
center of excellence in neuroscientific research. The
initiative will also employ several new PNP related Philosophy faculty
and post-doctoral fellows.


Students admitted to the PNP program will embark
upon a five-year course of study designed to fulfill all the
requirements for the Ph.D. in philosophy, including an
academic year studying neuroscience at Washington
University's School of Medicine or psychology in the
Department of Psychology.  Finally, each PNP student will
write a dissertation jointly directed by a philosopher and a
faculty member from either the medical school or the
psychology department.

THE FACULTY

Roger F. Gibson, Ph.D., Missouri, Professor and Chair:
  Philosophy of Language, Epistemology, Quine

Robert B. Barrett, Ph.D., Johns Hopkins, Professor:
  Pragmatism, Renaissance Science, Philosophy of Social
  Science, Analytic Philosophy.

Andy Clark, Ph.D., Stirling, Visiting Professor (1993-6) and
Acting Director of PNP:
  Philosophy of Cognitive Science, Philosophy of Mind,
  Philosophy of Language, Connectionism.

J. Claude Evans, Ph.D., SUNY-Stony Brook, Associate Pro-
  fessor:  Modern Philosophy, Contemporary Continental
  Philosophy, Phenomenology, Analytic Philosophy, Social and
  Political Theory.

Marilyn A. Friedman, Ph.D., Western Ontario, Associate
  Professor:  Ethics, Social Philosophy, Feminist Theory.

William H. Gass, Ph.D., Cornell, Distinguished University
  Professor of the Humanities:  Philosophy of Literature,
  Photography, Architecture.

Lucian W. Krukowski, Ph.D., Washington University, Pro-
  fessor:  20th Century Aesthetics, Philosophy of Art,
  18th and 19th Century Philosophy, Kant, Hegel,
  Schopenhauer.

Josefa Toribio Mateas, Ph.D., Complutense University,
  Assistant Professor:  Philosophy of Language, Philosophy
  of Mind.

Larry May, Ph.D., New School for Social Research, Pro-
  fessor:  Social and Political Philosophy, Philosophy of
  Law, Moral and Legal Responsibility.

Stanley L. Paulson, Ph.D., Wisconsin, J.D., Harvard, Pro-
  fessor:  Philosophy of Law.

Mark Rollins, Ph.D., Columbia, Assistant Professor:
  Philosophy of Mind, Epistemology, Philosophy of Science,
  Neuroscience.

Jerome P. Schiller, Ph.D., Harvard, Professor:  Ancient
  Philosophy, Plato, Aristotle.

Joyce Trebilcot, Ph.D., California at Santa Barbara, Associ-
  ate Professor:  Feminist Philosophy.

Joseph S. Ullian, Ph.D., Harvard, Professor:  Logic, Philos-
  ophy of Mathematics, Philosophy of Language.

Richard A. Watson, Ph.D., Iowa, Professor:  Modern Philoso-
  phy, Descartes, Historical Sciences.

Carl P. Wellman, Ph.D., Harvard, Hortense and Tobias Lewin
  Professor in the Humanities:  Ethics, Philosophy of Law,
  Legal and Moral Rights.

EMERITI

Richard H. Popkin, Ph.D., Columbia:  History of Ideas,
  Jewish Intellectual History.

Alfred J. Stenner, Ph.D., Michigan State:  Philosophy of
  Science, Epistemology, Philosophy of Language.

FINANCIAL SUPPORT

Students admitted to the Philosophy-Neuroscience-Psychology
(PNP) program are eligible for five years of full financial
support at competitive rates in the presence of satisfactory
academic progress.

APPLICATIONS

Application for admission to the Graduate School should be
made to:
                    Chair, Graduate Admissions
                    Department of Philosophy
                    Washington University
                    Campus Box 1073
                    One Brookings Drive
                    St. Louis, MO 63130-4899

Washington University encourages and gives full
consideration to all applicants for admission and financial
aid without regard to race, color, national origin,
handicap, sex, or religious creed.  Services for students
with hearing, visual, orthopedic, learning, or other
disabilities are coordinated through the office of the
Assistant Dean for Special Services.

------------------------------

Date: Tue, 15 Dec 1992 17:59:45 GMT
From: sethi@usha.cs.wayne.edu (Ishwar K. Sethi)
Organization: Wayne State University, Detroit
Subject: special issue of the machine vision and applications
Keywords: machine vision, neural networks

CALL FOR PAPERS

Special Issue of the Machine Vision and Applications on Neural
Networks for Machine Vision

The developments in the artificial neural network technology in
recent years have provided machine vision researchers and developers
with new tools and techniques to build machine vision algorithms and
systems that exhibit human-like visual perception capabilities.
The goal of the special issue is to capture these developments in
neural network theory and its applications to machine vision and to
provide the readers with an overview of the state-of-the-art. To meet
this goal, papers are solicited for the special issue which is scheduled
to appear in early 1995. Possible topics for the special issue, but not
limited to, include the followings:

*  Learning and Self-Organization for Segmentation, Feature Extraction,
   and Recognition.
*  Motion Detection, Tracking, and Characterization using Neural Networks.
*  Hardware Implementations including Smart Vision Chips.
*  Neural Networks for Multisensory Processing.
*  Automated Visual Monitoring and Inspection using Neural Networks.
*  Reverse Engineering for Machine Vision using Neural Networks.

Papers emphasizing technical details and theoretical background of machine
vision systems having strong neural network components and currently in use
are especially welcome.

The papers should be prepared following the Machine Vision and Applications
guidelines. All papers will be reviewed according to the guidelines of the
Machine Vision and Applications . Please submit four copies of your manuscript
to:

  Professor Ishwar K. Sethi
  Department of Computer Science
  Wayne State University
  Detroit, MI 48202
  U.S.A.

The deadline for submission is July 31, 1993. For enquiries, send E-mail to
sethi@cs.wayne.edu or fax to 313-577-6868.

------------------------------

Date: Mon, 7 Dec 92 14:37:42 -0500
From: carlson@titanic.cs.umass.edu (Adam Carlson)
Subject: AAAI '93 : Call for Papers

Call for Papers
AAAI-93

AAAI-93 is the eleventh national conference. The purpose 
of the conference is to promote research in artificial 
intelligence (AI) and scientific interchange among AI 
researchers and practitioners.
    Papers may represent significant contributions to all 
aspects of AI: 
a)   the principles underlying cognition, perception, and 
action in humans and machines; 
b)   the design, application, and evaluation of AI 
algorithms and intelligent systems; and 
c)   the analysis of tasks and domains in which 
intelligent systems perform.
    In recognition of the wide range of methodologies and 
research activities legitimately associated with AI, we 
invite authors to submit papers describing both 
experimental and theoretical results from all stages of 
AI research.  In particular, we encourage submission of 
papers that present promising research directions by 
describing innovative concepts, techniques, perspectives, 
or observations that are not yet supported by mature 
results.  To be accepted, such submissions must include 
substantial analysis of the ideas, the technology needed 
to realize them, and their potential impact.  In addition, 
because of the essential interdisciplinary nature of AI 
and the need to maintain effective communication across 
sub-specialties, we encourage authors to position and 
motivate their work in the larger context of the general 
AI community. While papers concerned with applications 
of AI are invited, those that describe working 
commercial systems should be submitted to the IAAI 
conference.


Requirements for Submission

Authors must submit six (6) complete printed copies of 
their papers to the AAAI office by January 13, 1993.  
Papers received after that date will be returned 
unopened.  Notification of receipt will be mailed to the 
first author (or designated author) soon after receipt.  
All inquiries regarding lost papers must be made by 
January 27, 1993.  Authors are also requested to send 
their paperUs title page in an electronic mail message to 
abstract@aaai.org by January 13, 1993. Notification of 
acceptance or rejection of submitted papers will be 
mailed to the first author (or designated author) by 
March 3, 1993.  Camera-ready copy of accepted papers 
will be due about one month later.
 
Paper Format for Review
All six (6) copies of a submitted paper must be clearly 
legible. Neither computer files nor fax submissions are 
acceptable.  Submissions must be printed on 8 1/2" x 11" 
or A4 paper using 12 point type (10 characters per inch 
for typewriters).  Each page must have a maximum of 38 
lines and an average of 75 characters per line 
(corresponding to the LaTeX article-style, 12 point).  
Double-sided printing is strongly encouraged. 
 
Length
The body of submitted papers must be at most 11 pages, 
including figures, tables, and diagrams, but excluding the 
title page and bibliography.  Papers exceeding the 
specified length and formatting requirements are subject 
to rejection without review.

Title page
Each copy of the paper must have a title page (separate 
from the body of the paper) containing the title of the 
paper, the names and addresses of all authors, a short 
(less than 200 word) abstract, and a descriptive content 
area or areas. The title page sent via electronic mail to 
the AAAI office must be in plain ASCII text with each 
section of the title page preceded by the name of that 
section as follows:
title: <title>
author: <name of first author>
address: <address of first author> author: <name of last 
author>
address: <address of last author>
abstract: <abstract>
content areas: <first area>, I, 
<last area>
    To facilitate the reviewing process, authors are 
requested to select appropriate content areas from the 
list below. Authors are invited to add additional content 
area descriptors to their title page as needed.
   Artificial Life, Automated Reasoning, Behavior-Based 
Control, Belief Revision, Case-Based Reasoning, 
Cognitive Modeling, Common Sense Reasoning, 
Communication and Cooperation, Constraint-Based 
Reasoning, Computer-Aided Education, Connectionist 
Models, Corpus-Based Language Analysis, Deduction, 
Diagnosis, Discourse Analysis, Distributed Problem 
Solving, Expert Systems, Geometrical Reasoning, 
Information Extraction, Knowledge Acquisition, 
Knowledge Representation, Knowledge Sharing 
Technology, Large Scale Knowledge Engineering, 
Learning/Adaptation, Machine Learning, Machine 
Translation, Mathematical Foundations, Multi-Agent 
Planning, Natural Language Processing, Neural Networks, 
Nonmonotonic Reasoning, Perception, Planning, 
Probabilistic Reasoning, Qualitative Reasoning, 
Reasoning about Action, Reasoning about Physical 
Systems, Reactivity, Robot Navigation, Robotics, Rule-
Based Reasoning, Scheduling, Search, Sensor 
Interpretation, Sensory Fusion/Fission, Simulation, 
Situated Cognition, Spatial Reasoning, Speech 
Recognition, System Architectures, Temporal Reasoning, 
Terminological Reasoning, Theorem Proving, Truth 
Maintenance, User Interfaces, Virtual Reality, Vision, 3-
D Model Acquisition.


Submissions to Multiple Conferences

Papers that are being submitted to other conferences, 
whether verbatim or in essence, must state this fact on 
the title page. If a paper appears at another conference 
(with the exception of specialized workshops), it must 
be withdrawn from AAAI-93. Papers that violate these 
requirements are subject to rejection without review.
 

Review Criteria

Each paper will be carefully reviewed by experts 
specializing in the content areas on the paperUs title 
page.  Questions that will appear on the review form have 
been reproduced below.  Authors are  advised to bear 
these questions in mind while writing their papers:
Significance
How important is the work reported?  Does it attack an 
important/difficult problem or a peripheral/simple one?  
Does the approach offered advance the state of the art?

Originality
Has this or similar work been previously reported?  Are 
the problems and approaches completely new?  Is this a 
novel combination of familiar techniques?  Does the 
paper point out differences from related research?  Is it 
re-inventing the wheel using new terminology?   

Quality
Is the paper technically sound?  Does it carefully 
evaluate the strengths and limitations of its 
contribution?  How are its claims backed up?

Clarity
Is the paper clearly written?  Does it motivate the 
research?  Does it describe the inputs, outputs and basic 
algorithms employed?  Does the paper describe previous 
work?  Are the results described and evaluated? Is the 
paper organized in a logical fashion?
 
Publication
Accepted papers will be allocated six (6) pages in the 
conference proceedings.  Up to two (2) additional pages 
may be used at a cost to the authors of $250 per page.  
Papers exceeding eight (8) pages and those violating the 
instructions to authors will not be included in the 
proceedings.
 
Copyright
Authors will be required to transfer copyright of their 
paper to AAAI.
 

Please send papers and conference registration inquiries 
to:
 
AAAI-93
American Association
for Artificial Intelligence
445 Burgess Drive
Menlo Park, CA 94025-3496
 
Registration and call clarification inquiries (ONLY) may 
be sent to the CSNET address: NCAI@aaai.org.  Please 
send program suggestions and inquiries to:
 
Richard Fikes
Knowledge Systems Laboratory
Stanford University
701 Welch Road, Building C
Palo Alto, CA 94304
fikes@ksl.stanford.edu
 
Wendy Lehnert
Department of Computer Science
University of Massachusetts
Amherst, MA 01003
lehnert@cs.umass.edu

------------------------------

Date: Thu, 10 Dec 92 16:51:41 -0500
From: "Baba Vemuri" <vemuri@scuba.cis.ufl.edu>
Status: CFP: Geometric Methods in Computer Vision

			CALL FOR PAPERS

		Geometric Methods in Computer Vision
	(Part of SPIE's Annual International Symposium on Optoelectronic
	Applied Science and Engineering; 12-13th July 1993;
			San Diego, California,
	San Diego Convention Center, Marriott Hotel and Marina)

	  Conference Chair: Baba C. Vemuri
               Dept. of Computer & Information Sciences, CSE326
               University of Florida, Gainesville, FL. 32611

Co-chairs:
Ruud M. Bolle, IBM T. J. Watson Research Center, Yorktown Heights, NY.
Demetri Terzopoulos, Department of Computer Science, Univ. of Toronto, Canada.
Richard Szeliski, Cambridge Research Labs, DEC, Cambridge, MA.
Gabriel Taubin, IBM T. J. Watson Research Center, Yorktown Heights, NY.
Alan Yuille, Division of Applied Sciences, Harvard University, MA.
Ramesh C. Jain, Dept. of EECS, Univ. of Michigan, Ann Arbor, MI.

			Key Note Address:
	
		Professor Dr. Jan Koenderink
		Physics Lab, Department of Medical and Physiological Physics
		University of Utrecht, Netherlands.



The theme of this conference is application of geometric methods in
low-level vision tasks, specifically for shape and motion estimation.
Over the past few years, there has been increased interest in the use
of differential geometry, computational physics and probability theory
for various vision tasks.  Papers describing novel contributions in all
aspects of geometric and probabilistic methods in vision are
solicited, with particular emphasis on:

Differential Geometric Methods for Shape Representation.

Energy-based Methods for Shape Estimation.

Probabilistic Techniques for Shape Estimation and Representation.

Geometry and Shape Recognition.


		    New	Deadlines

Abstract Due Date:  DECEMBER 28, 1992

Manuscript Due Date: April 19, 1993
(Proceedings will be made available at the conference)

Please FAX or airmail FOUR copies, or email ONE copy of your abstract 
by 14 DECEMBER 1992 to:

SPIE, San Diego '93
P.O. Box 10, Bellingham, WA 98227-0010
Shipping Address: 1000 20th Street, Bellingham, WA 98225
Telephone: 206/676-3290
FAX: 206/647-1445
email: abstracts@mom.spie.org (ASCII Files only)
CompuServe 71630,2177

Your submission should include the title of your abstract, the authors' names,
affiliations, mailing addresses, phone/FAX numbers, and email addresses, as well
as the abstract text of approximately 500 words. Please be sure to indicate that
your abstract is intended for the conference on Geometric Methods in Computer
Vision II (Vemuri).

Applicants will be notified of acceptance by March 1993. A manuscript due
date of 19 April 1993 must be strictly observed since the Proceedings of this
conference will be published before the meeting and available on site.

Note: Late abstract submissions may be considered, subject to program
time availability and chairs approval.

------------------------------

From: Mark Evans <mre1@it-research-institute.brighton.ac.uk>
Date: Tue, 8 Dec 92 18:08:00 GMT
Subject: Sun Pix

I have summarised some reponses I got about Sun's video pix frame grabber. It
might be of interest to others.

Regards,

Mark

# Mark Evans               mre1@itri.bton.ac.uk #
#                          itri!mre1            #
# ITRI,                                         #
# University of Brighton,                       #
# Lewes Road,                                   #
# BRIGHTON,                                     #
# E. Sussex,                                    #
# BN2 4AT.                                      #
# Tel: +44 273 642904/642900                    #
# Fax: +44 273 606653                           #

>Does anyone have any experience of using the VideoPix card
>by Sun ? It allows you to capture images and display them
>on a sparc workstation. Does anyone have a recommendation
>for a frame grabber for a sparc costing 500-700 pounds ?

Thank you for everyone that supplied me with information. Special thanks to
MS and EM of Sun Microsystems (both worked on the videopix card project) for
all the their help.

*** Users Comments ***

1. I have used the videopix here in the USA.  It seems to work OK for me.  I
don't know how high a video quality that you need but the videopix only has
7-bit analogue to digital converters.  I don't know of anything else in the
same price range but I haven't looked for about 1.5 years.

2. We have three or four VideoPix boards and are very happy with them.
They're not full-motion though, so if this is a requirement for you then the
VideoPix may not be what you want.

The boards can capture and display about 15fps of greyscale video in a small
window.  As you increase the size of the window (and hence the amount of data
which needs to be blitted through the window system) and add color, the
capture and display rate drops and eventually bottoms out at about 5fps for a
fairly large color window.

The board comes with a nice software library and a GUI interface, and seems
to be a well thought-out product.  We've had no complaints at all.

3. I've used the Sun VideoPix card. When it comes to grabbing single frames
(motionless) it's OK. I use the PAL-format, which gives about 720x575
pixels.  NTSC gives, I think, 640x480.  Also, it stores 7 bits of luminosity
per pixel, and 2*7 bits of chrominance per every four pixels. So, the
color-information appears a bit slower than the intensity. Maybe this is only
natural. The eye might be better at intensity differences than those of
color.

To grab a movie in realtime is harder. I've managed to grab about 6 frames/s,
on a Sparc 2, each frame having a resolution of 320x240 full color.  Full
frame-rate would be 25-30 frames/s.

4. I have messed around with the videopix card quite a bit, and it seems to
be a viable tools for conferencing, image-oriented mail and multimedia, etc,
but does not produce the quality required for high-end image processing
applications.

5. We have one of these boards here at ANU, but we just got the thing so we
don't have much experience with it so far. It can display about a frame a
second from live video or TV in color, but the quality isn't as good as I
expected. That may be a result of the poor quality signal from the TV though.
It can do a few frames a second in black and white.  The frame grabs work
pretty good, but it is hard to get the exact frame that you want.

*** Technical Specification ***

1. Colour (8 and 24 bit)

Yes.

2. Greyscale (256 levels)

Yes.

3. Monochrome

Yes. 1bit per pixel file saves are available. All functions work on 1bit
frame buffers, also.

4. A resolution of 512x512 or better

Square pixel PAL resolution is what you get from the VFCtool software, but we
also have an API that lets you get the full non-square data. So you can
customize your software to control VideoPix directly. The API isn't a
specific tool per say, but a list of defined driver calls.

5. Video input

2 Composite (NTSC or PAL), 1 S-Video (NTSC or PAL) all software selectable.

6. Continuous Frame Gabbing - (what is the max frames grabbed per sec ?)

Ah. This depends on which mode (B&W or Colour) and what display resolution
you selected from the software. Basically it's:

mode            resolution (displayed)          FPS

Colour          Full (640x480 NTSC)              1
Colour          Half (320x240 NTSC)              ~3.5
Colour          Quarter (160x120 NTSC)           ~5

B&W             Full (640x480 NTSC)              ~3.5
B&W             Half (320x240 NTSC)              ~6.5
B&W             Quarter (160x120 NTSC)           ~8.5

The fastest library routine that is supplied might be able to grab 15 fields
per second, NTSC, in raw YUV format.

*** Technical Explanation ***

The ADC's are a full 8 bits, But the SAA9051 Multi-Standard Decoder operates
only on 7 bits. The output of the decoder is 4:1:1 digital YUV data that is
stored in the boards FRAM. There is a full frame of FRAM on the board for
either NTSC or PAL.

Basicaly the board looks like this:

input conn -> SWITCH-AGC-FILTER-ADC -> SAA9051 decoder-> FRAM ->SBUS
input conn -|                             |                      |
input conn -|                              --------I2C UART -----


What happens along this decode path is this:

1. The video source is supplied via the input connectors. Which input is
selected via the software. Commands are send through I2C bus to tell the
decoder which input has been requested.

2. Now the video has been selected, the ADC now gain adjusts the video levels
and  low pass filters the signal to trap out un-wanted noise above 6.5Mhz.
Then the video is buffered and sent into the ADC. The ADC digitizes the CVBS
signal with 8 bit resolution. The data is then sent to the decoder.

3. Now the data is taken into the SAA9051 decoder. Although the part has an
8bit hardware interface to the input ADC's, the internal resolution that the
chip operates at is only 7bits in the (y) luminance path. The color
information (c) is decoded and sub-sampled and then outputed with the (y)
information to produces a 4:1:1 digital YUV output data stream.

4. The information is now stored in the on-board 1 Meg FRAM (Field RAM)
buffer at video speed. FRAM is a memory specially designed for use in video
frame store applications. It was first used in televisions that had
Picture-In-Picture (PIP) processors. It now can be found in most high end
VCR's being used for time base correction applications or in digitizers like
VideoPix. FRAM looks like a big FIFO, and is in fact read like a FIFO. But
it's storage cell can hold an entire field of PAL (or NTSC) video. Now that
this information is held in the FRAM, The application can now access it from
the SBUS. This is where the speed bottleneck is.

5. SBUS. Once the data is requested, it is sent in it's raw YUV data form
into the host memory via VideoPix's slave interface. The data transfer speeds
are fast, but not fast enough for real-time transfers (30FPS). This amount of
data is in the order of ~20 MBytes/sec which requires an expensive (at the
time) DMA interface. This also swamps SBUS disallowing of transactions to
occur from other SBUS cards. Since SBUS is considerd a general purpose I/O
bus and not a high speed video bus, it would be wrong for any SBUS card to
take more than 50% of the bandwith at anytime.

The net results is that we have an upper limit as to how fast we can transfer
the data from the card to the host ram.

6. Once the data is in the host, the software does several things to it. The
data arrives as 4:1:1 coded YUV non-square (4:3 aspect) pixels. In order to
display this on the console, the data is transcoded to RGB and dithered if
the framebuffer is only 8bits. It is then sub-sampled to render a square
image. This basicaly means dropping every fith pixel.

7. The data is now bit-blited to the display for you to enjoy!.

*** My thoughts ***

I will be buying one. If your main frame grabber specification is
real time frame grabbing you will have to purchase a different, more
expensive frame grabber. For the price it seems good value for money.

I have two sample jpeg images (90%) grabbed from TV using the videopix card
if anyone is interested.

Thank you again for everyone that sent info to me. 

Regards,
Mark

------------------------------

Date: Wed, 9 Dec 92 15:28:07 EST
From: bedard@robocop.NYU.EDU (Patricia Bedard)
Subject: References on automatic face recognition

Following my previous request for references on automatic face recognition,
many people expressed an interest in the compilation, so I thought it might
be useful to post it to the vision list.

Here is the list of references that I have compiled.  If you notice that
some references that you know about are missing, please let me know.
Cheers,

Patricia

Patricia J. Bedard       (bedard@robocop.nyu.edu)
Courant Institute of Mathematical Sciences
New York University
251 Mercer St.
New York, NY, 10012  U.S.A.

***************

survey (with extensive bibliography):
====================================
Ashok Samal and Prasana A. Iyengar: "Automatic Recognition and
Analysis of Human Faces and facial Expressions: A Survey"
Pattern Recognition _25(1)_, 65--77, 1992.


references:
==========
Andrew C. Aitchison and Ian Craw.  "Synthetic Images Of Faces - An Approach
to Model-Based face recognition" in "BMVC91, Proceedings of the British
Machine Vision Conference", 1991, (Peter Mowforth, editor) Springer-Verlag.

Shigeru Akamatsu and Tsutomu Sasaki and Hideo Fukamachi and Nobuhiko Masui
and Yasuhito Suenaga.  "An Accurate and Robust Face Identification Scheme"
in ICPR'92, 1992.

Shigeru Akamatsu and Tsutomu Sasaki and Hideo Fukamachi and Yasuhito Suenaga.
"A robust face identification scheme --- KL expansion of an invariant feature
space" in Intelligent Robots and Computer Vision X: Algorithms and Techniques",
SPIE #1607, 1991.  pp. 71-84.

Robert Baron, Mechanisms of human facial recognition
International Journal of Man-Machine Studies (1981) 15, 137-178

Alan Bennett and Ian Craw.  "Finding Image Features Using Deformable Templates
And Detailed Prior Statistical Knowledge" in "BMVC91, Proceedings of the
British Machine Vision Conference", 1991, (Peter Mowforth, editor),
Springer-Verlag.

Brunelli, R. and Poggio, T. "Face Recognition through Geometrical Features"
in "Proc. 2nd European Conf. on Computer Vision, Lecture Notes in Computer
Science #588" (G. Sandini, editor), Springer Verlag, 1992.  pp. 792-800.

R. Brunelli and T. Poggio, ``HyperBF networks for gender classification,''
Proc. DARPA IU Workshop, 1992, 311--314.

Buhmann, Joachim and Lades, Martin and von der Marlsburg, Christoph.  "Size
and Distortion Invariant Object Recognition by Hierarchical Graph Matching",
IJCNN, 1990, V.2.  pp. 411-416.

Burt, Peter J.  "Smart Sensing within a Pyramid Vision Machine" in
"Proceedings of the {IEEE}", 1988, vol 76, no 8, pp. 1006-1015.

Craw, Ian and Cameron, Peter. "Face Recognition by Computer" in
"Proc. British Machine Vision Conference", 1992, (David Hogg and Roger
Boyle, editors), Springer Verlag.

Ian Craw and Peter Cameron.  "Parameterising Images for Recognition and
Reconstruction" in "BMVC91, Proceedings of the British Machine Vision
Conference", 1991,(Peter Mowforth, editor), Springer-Verlag.

I. Craw, H. Ellis and J.R. Lishman, Automatic extraction of face-features
Pattern Recognition Letters, 5, 1987, 183-187

Ian Craw and David Tock and Alan Bennett.  "Finding Face Features" in ECCV'92,
Lecture Notes in Computer Science #588, Springer Verlag.  pp.

S. Edelman and D. Reisfeld and Y. Yeshurun.  "Learning to recognize faces
from examples" in "Proc. 2nd European Conf. on Computer Vision, Lecture Notes
in Computer Science #588", (G. Sandini, editor), Springer Verlag, 1992.
pp. 787-791.

Fleming, Michael K. and Cottrell, Garrison W. ""Categorization of Faces
Using Unsupervised Feature Extraction" in IJCNN, 1990, Vol 2, pp. 65-70.

R Gallery and T I P Trew. "An Architecture for Face Classification" in
"Colloquium: Machine Storage and Recognition of Faces. IEE Digest 017, 1992.

Goldstein, A. Jay and Harmon, Leon D. and Lesk, Ann B.  "Identification of
Human Faces" in "Proceedings of the {IEEE}", 1971, Vol 59, No 5, pp. 748-760.

G.G. Gordon, ``Face recognition based on depth and curvature features,''
Proc. IEEE CVPR, 1992, 808--810.

Govindaraju, Venu and Srihari, Sargur. N. and Sher, David B.  "A Computational
Model for Face Location" in ICCV'90, pp. 718-721.

Harmon, L. D. and Khan, M. K. and Lasch, Richard and Ramig, P. F.
"Machine Identification of Human Faces" in "Pattern Recognition", 1981,
Vol 13, No. 2, pp. 97-110.

Hong, Zi-Quan.  "Algebraic feature extraction of image for recognition" in
"Pattern Recognition", Vol 24, March 1991, pp. 211-219.

Jia, Xiaoguang and Nixon, Mark S.  "On developing an extended feature set
for automatic face recognition" in "Colloquium: Machine Storage and
Recognition of Faces, IEE Digest 017", 1992.

Kanade, Takeo.  "Computer Recognition of Human Faces" in volume 47 of
"Interdisciplinary Systems Research", Birkhauser, Basel, Stuttgart, 1977.

Kaya, Y. and Kobayashi, K.  ""A Basic Study on Human Face Recognition" in
"Frontiers of Pattern Recognition", 1972, pp. 265-289.

Kirby, M. and Sirovich, L.  "Application of the Karhunen-Lo\`{e}ve
Procedure for the Characterization of Human Faces" in PAMI-12, 1980,
V.12, no 1, pp. 103-108.

J.C. Lee and E. Milios, ``Matching range images of human faces,''
Proc. ICCV, 1990, 722--726.

B.S. Manjunath, R. Chellappa, and C. von der Malsburg, ``A feature based
approach to face recognition,'' Proc. IEEE CVPR, 1992, 373--378.

Nakamura, Osamu and Mathur, Shailendra and Minami, Toshi.  "Identification
of Human Faces Based on Isodensity Maps" in "Pattern Recognition", 1991,
Vol 24, no 3, pp. 263-272.

A. Pentland and S. Sclaroff, ``Closed-form solutions for physically
based shape modeling and recognition,'' IEEE PAMI, Vol.\ 13,
1991, 715--729.

C.S. Ramsey and K. Sutherland and D. Renshaw and P.B. Denyer.  "A Comparison
of Vector Quantisation Codebook Generation  Algorithms Applied to Automatic
Face Recognition" in "Proceedings of BMVC-92", (David Hogg, editor),
Springer-Verlag, 1992.

Anne-Caroline Schreiber et. al., Facenet: A Connectionist Model of
Face Identification in Context
European Journal of Cognitive Psychology, 1991, 3 (1), 177-198

Ken Sutherland, D. Rensham, and P.B. Denyer.  "A novel automatic face
recognition algorithm employing vector quantization" in "Colloquium:
Machine Storage and Recognition of Faces, IEE Digest 017", 1992.

D. Terzopoulos and K. Waters, ``Analysis of facial images using
physical and anatomical models,'' Proc. ICCV,
1990, 727--732.

David Tock and Ian Craw and Roly Lishman.  "A Knowledge Based System for
Measuring Faces" in "BMVC90, Proceedings of the British Machine Vision
Conference", 1990.  pp. 401-407.

M. Turk, "Interactive-Time Vision:  Face Recognition as a Visual
Behavior", Ph.D. Thesis, MIT Media Lab, August 1991.

M. Turk and A. Pentland, ``Eigenfaces for recognition,''
{\sl Journal of Cognitive Neuroscience}, Vol. 3, No. 1, pp. 71-86, 1991.

M. Turk and A. Pentland, ``Face Recognition Using
Eigenfaces,'' {\sl Proc. CVPR}, Maui, Hawaii, pp. 586-591, 1991.

M. Turk and A. Pentland, ``Recognition in face space,''
{\sl Intelligent Robots and Computer Vision IX}, SPIE Vol. 1381,
Boston, MA, 1990.  (Reprinted in
H. Nasr (ed.), {\sl Selected Papers on Automatic Object Recognition},
SPIE Optical Engineering Press, Washington, 1991.)

Wong, K. H. and Law, Hudson H. M. and Tsang, P. W. M.  "A system for
recognising human faces" in "Proceedings of the International Conference
on Acoustics, Speech and Signal Processing", 1989, pp.1638-1642.

Y. Yacoob and L. Davis, Qualitative Labeling of Human Face Features from
Range Data, Technical Report CS-TR-2971, Center for Automation Research,
University of Maryland, College Park, MD, Oct. 1992.

A.L. Yuille, D.S. Cohen, and P.W. Hallinan, ``Feature extraction
from faces using deformable templates,'' Proc. IEEE CVPR, 1989,
104--109.

Alan Yuille, Deformable Templates for face recognition
Journal of Cognitive Neuroscience, 1991, Vol 3, No. 1, p59-70


papers soon to be released:
==========================
work by Martin Lades, C. von der Malsburg (et al.?) to appear in IEEE Trans.
on Computers.

report on face recognition prepared by Alex Pentland, Terry Sejnowski and
others soon to be publicly available.


------------------------------

From: nde@scs.leeds.ac.uk
Date: Fri, 11 Dec 92 12:57:10 GMT
Subject: Snakes: summary of responses (long)
Status: R

The response to my request for references on snakes and active contour
models was terrific: my thanks go to all who contributed information. I've
collated the various contributions into the list below.

Nick Efford
School of Computer Studies
Leeds University, Leeds, UK

@inproceedings{amini88:iccv,
    author	= "Amini, A. and Tehrani, S. and Weymouth, T",
    year	= 1988,
    title	= "Using dynamic programming for minimizing the energy of
		  active contours in the presence of hard constraints",
    booktitle	= "Proceedings of the Second International Conference on
		  Computer Vision, Tampa, Florida",
    pages	= "95--99"}

@inproceedings{berger90:icpr,
    author	= "Berger, M. O. and Mohr, R.",
    year	= 1990,
    title	= "Towards autonomy in active contour models",
    booktitle	= "Proceedings of the Tenth International Conference on
		  Pattern Recognition"}

@article{brzak91:cvgip,
    author	= "Brzakovic, D. and Liakopoulos, A. and Hong, L.",
    year	= 1991,
    title	= "Spline models for boundary detection/description:
		  formulation and performance evaluation",
    journal	= "CVGIP: Graphical Models and Image Processing",
    volume	= 53,
    number	= 4,
    pages	= "392--401"}

@incollection{calbom91,
    author	= "Calbom, I. and Terzopoulos, D. and Harris, K. M.",
    year	= 1991,
    title	= "Reconstructing and visualizing models of neuronal
		  dendrites",
    booktitle	= "Scientific Visualization of Physical Phenomena",
    publisher	= "Springer-Verlag",
    pages	= "623--638"}

@article{cohen91:cvgip,
    author	= "Cohen, L. D.",
    year	= 1991,
    title	= "Note on active contour models and balloons",
    journal	= "CVGIP: Image Understanding",
    volume	= 53,
    number	= 2,
    pages	= "211-218"}

@inproceedings{cohen90:iccv,
    author	= "Cohen, L. and Cohen, I.",
    year	= 1990,
    title	= "A finite element method applied to new active contour
		  models and {3D} reconstructions",
    booktitle	= "Proceedings of the Third International Conference on
		  Computer Vision, Osaka, Japan, December 1990",
    pages	= "587--591"}

@article{cohen92:cvgip,
    author	= "Cohen, I. and Cohen, L. D. and Ayache, N.",
    year	= 1992,
    title	= "Using deformable templates to segment {3D} imags and
		  infer differential structures",
    journal	= "CVGIP: Image Understanding",
    volume	= 56,
    number	= 2,
    pages	= "242--263"}

@inproceedings{cohen92:cvpr,
    author	= "Cohen, L. D. and Cohen, I.",
    year	= 1992,
    title	= "Deformable models for {3D} medical images using
		  finite elements and balloons",
    booktitle	= "IEEE Computer Society Conference on Computer Vision
		  and Pattern Recognition, Champaign, Illinois, June
		  1992"}

@techreport{davatz92,
    author	= "Davatzikos, C. A. and Prince, J. L.",
    year	= 1992,
    title	= "An active contour algorithm for thick curves",
    institution	= "Johns Hopkins University",
    number	= "JHU/ECE 92-07"}

@inproceedings{davatz92:icassp,
    author	= "Davatzikos, C. A. and Prince, J. L.",
    year	= 1992,
    title	= "Segmentation and mapping of highly-convoluted
		  contours with applications to medical images",
    booktitle	= "Proceedings of ICASSP '92, IEEE Conference on
		  Acoustics, Speech and Signal Processing"}

@unpublished{davatz93:cvpr,
    author	= "Davatzikos, C. A. and Prince, J. L.",
    year	= 1993,
    title	= "Adaptive active contour algorithms for extracting and
		  mapping thick curves",
    note	= "Submitted to CVPR '93, IEEE Conference on Computer
		  Vision and Pattern Recognition"}

@article{kass88:ijcv,
    author	= "Kass, M. and Witkin, A. and Terzopoulos, D.",
    year	= 1988,
    title	= "Snakes: active contour models",
    journal	= "International Journal of Computer Vision",
    volume	= 1,
    number	= 4,
    pages	= "321--331"}

@article{leymarie92:pami,
    author	= "Leymarie, F. and Levine, M. D.",
    year	= 1992,
    title	= "Simulating the grassfire transform using an active
		  contour model",
    journal	= "IEEE Transations on Pattern Analysis and Machine
		  Intelligence",
    volume	= 14,
    number	= 1,
    pages	= "56--75"}

@unpublished{leymarie93:pami,
    author	= "Leymarie, F. and Levine, M. D.",
    year	= 1993,
    title	= "Tracking deformable objects in the plane using an
		  active contour model",
    note	= "To appear in IEEE Transactions on Pattern Analysis
		  and Machine Intelligence"}

@inproceedings{menet90:darpa,
    author	= "Menet, S. and Saint-Marc, P. and Medioni, G.",
    year	= 1990,
    title	= "B-snakes: implementation and application to stereo",
    booktitle	= "Proceedings of the DARPA Image Understanding
		  Workshop, Pittsburgh, Pennsylvania, September 1990"}

@article{poggio85,
    author	= "Poggio, T. and Torre, V. and Koch, C.",
    year	= 1985,
    title	= "Computational vision and regularization theory",
    journal	= "Nature",
    volume	= 317,
    pages	= "314--319"}

@inproceedings{richens92:ipa,
    author	= "Richens, D. and Rougan, N. and Bloch, I. and
		  Mousseaux, E.",
    year	= 1992,
    title	= "Segmentation by deformable contours of {MRI} sequence
		  of left ventricle for quantitative myocardial
		  analysis",
    booktitle	= "IEE Proceedings of the Fourth International
		  Conference on Image Processing and its Applications,
		  Maastricht, April 1992",
    pages	= "393--396"}

@article{rougan91:spie,
    author	= "Rougan, N. and Preteux, F.",
    year	= 1991,
    title	= "Deformable markers: mathematical morphology for
		  active contour model control",
    journal	= "Proceedings of the Society of Photo-Optical
		  Instrumentation Engineers",
    volume	= 1568,
    pages	= "78--89"}

@inproceedings{rougan92:embs,
    author	= "Rougan, N. and Preteux, F.",
    year	= 1992,
    title	= "Oriented smoothness constraints for adaptive active
		  contour models",
    booktitle	= "Proceedings of the Fourteenth Conference of the IEEE
		  Engineering in Medicine and Biology Society",
    pages	= "1916--1917"}

@article{samad91:spie,
    author	= "Samadani, R.",
    year	= 1991,
    title	= "Adaptive snakes: control of damping and material
		  parameters",
    journal	= "Proceedings of the Society of Photo-Optical
		  Instrumentation Engineers",
    volume	= 1568}

@article{sinha92:pami,
    author	= "Sinha, S. S. and Schunk, B. G.",
    year	= 1992,
    title	= "A two-stage algorithm for discontinuity-preserving
		  surface reconstruction",
    journal	= "IEEE Transactions on Pattern Analysis and Machine
		  Intelligence",
    volume	= "PAMI-14",
    number	= 1,
    pages	= "36--55"}

@article{snyder91:pami,
    author	= "Snyder, M. A.",
    year	= 1991,
    title	= "On the mathematical foundations of smoothness
		  constraints for the determination of optical flow and
		  for surface reconstruction",
    journal	= "IEEE Transactions on Pattern Analysis and Machine
		  Intelligence",
    volume	= "PAMI-13",
    number	= 11,
    pages	= "1105--1114"}

@article{staib92:pami,
    author	= "Staib, L. H. and Duncan, J. S.",
    year	= 1992,
    title	= "Boundary finding with parametrically deformable
		  models",
    journal	= "IEEE Transactions on Pattern Analysis and Machine
		  Intelligence",
    volume	= "PAMI-14",
    number	= 11,
    pages	= "1061--1075"}

@article{terzop86:pami,
    author	= "Terzopoulos, D.",
    year	= 1986,
    title	= "Regularization of inverse visual problems involving
		  discontinuities",
    journal	= "IEEE Transactions on Pattern Analysis and Machine
		  Intelligence",
    volume	= "PAMI-8",
    number	= 4,
    pages	= "413--423"}

@article{terzop87:cg,
    author	= "Terzopoulos, D. and Platt, J. and Barr, A. and
		  Fleischer, K.",
    year	= 1987,
    title	= "Elastically deformable models",
    journal	= "Computer Graphics",
    volume	= 21,
    number	= 4,
    pages	= "205--214"}

@article{terzop88:cga,
    author	= "Terzopoulos, D. and Witkin, A.",
    year	= 1988,
    title	= "Physically-based models with rigid and deformable
		  components",
    journal	= "IEEE Computer Graphics and Applications",
    month	= "November",
    pages	= "41--51"}

@article{terzop88:ai,
    author	= "Terzopoulos, D. and Witkin, A.",
    year	= 1988,
    title	= "Constraints on deformable models: recovering shape
		  and non-rigid motion",
    journal	= "Artificial Intelligence",
    volume	= 36,
    pages	= "91--123"}

@article{waite90:bttj,
    author	= "Waite, J. B. and Welsh, W. J.",
    year	= 1990,
    title	= "Head boundary location using snakes",
    journal	= "British Telecom Technology Journal",
    volume	= 8,
    number	= 3,
    pages	= "127--136"}

@article{will92:cvgip,
    author	= "Williams, D. J. and Shah, M.",
    year	= 1992,
    title	= "A fast algorithm for active contours and curvature
		  information",
    journal	= "CVGIP: Image Understanding",
    number	= 55,
    volume	= 1,
    pages	= "14--26"}

@article{yuille92:ijcv,
    author	= "Yuille, A. L. and Hallinan, P. W. and Cohen, D. S.",
    year	= 1992,
    title	= "Feature extraction from faces using deformable
		  templates",
    journal	= "International Journal of Computer Vision",
    volume	= 8,
    number	= 2,
    pages	= "99--111"}

------------------------------

End of VISION-LIST digest 11.43
************************
Newsgroups: comp.ai,comp.ai.philosophy,comp.ai.neural-nets,sci.lang,comp.cog-eng,can.ai