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VISION-LIST Digest Volume 12 Issue 41
VISION-LIST Digest Tue Sep 14 10:42:51 PDT 93 Volume 12 : Issue 41
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Today's Topics:
Centroid from boundary
CAD package for modeling of 3-D objects
Recognition of objects with movable joints
Algorithm for autostereograms
E-mail address of A Nowak, A Florek or T Piascik
Signature Database
Research Fellow Post - Leeds, UK
REQUEST FOR INFO: Experts for AI in sci.data.processing in Europe
Re: Breakthrough technologies
Final Program: Machine Learning in Computer Vision: What, Why and How?
------------------------------
Date: 8 Sep 93 16:08 -0700
From: Esfandiar Bandari <bandari@cs.ubc.ca>
Subject: Centroid from boundary
Is there a way of finding the centriod (and higher order moments) of a closed
curve. These curves can have concavities, and there is no information as
to where the inside of the curve is -- i.e. no real region growing option.
Thanks in advance.
--- Esfandiar
----------------------------------------------------------------------
Date: Sat, 11 Sep 1993 09:20:13 GMT
From: e9209h60@v9000.ntu.ac.sg
Subject: CAD package for modeling of 3-D objects
Organization: Nanyang Technological University - Singapore
I am working on range images for recognition of 3-d objects. For the
automatic construction of models I require a suitable CAD package. If anybody
can help me obtaining literature for CAD packages for modelling of
objects with sculptured surfaces, it shall be of great help to me.
I want the E-mail addresses of the supplier's contact person.
I am doing my Ph.D at NTU, Singapore. My E-mail address is
e9209h60@ntuvax.ntu.ac.sg
Thanks.
------------------------------
Date: Fri, 10 Sep 93 11:25:39 EDT
From: jeanlaur@mailbox.syr.edu (Jean-Laurent)
Organization: Syracuse University, Syracuse, NY
Subject: Recognition of objects with movable joints
Hi,
I am looking for any articles, books or other references that may deal with
the recognition of objects with movable joints. I would appreciate any help
or lead about this topic at the following email address:
jeanlaur@mailbox.syr.edu
Thanks in advance.
P.J.L.
------------------------------
Date: Sat, 11 Sep 1993 07:26:51 GMT
From: Marco Bertamini <mb2p@fermi.clas.virginia.edu>
Organization: University of Virginia
Subject: Algorithm for autostereograms
We plan to start a project on binocular vision which will require
producing autostereograms on a computer screen. However, we have not
been able to find any published algorithm for generating
autostereograms or information on the logic of their generation.
Does anybody on the net know where we could find this
information?
Replies to brunon@univ.trieste.it
or
mb2p@virginia.edu
Thanks a lot.
------------------------------
Date: 11 Sep 93 06:50:38 GMT
From: image@cs.curtin.edu.au (Image)
Organization: Curtin University of Technology
Subject: E-mail address of A Nowak, A Florek or T Piascik
Hi there,
I need to contact the following people from
Laborartory of Automation and Robotics Technical University
of Poznan, Poland.
Andrzej Nowak
Andrzej Florek
Tomasz Piascik
If you know their email addresses or if you are Andrzej, or Tomasz please
respond by mailing me at chowkc@cs.curtin.edu.au
------------------------------
Date: Tue, 7 Sep 93 22:29:40 EDT
From: keh@usha.cs.wayne.edu
Subject: Signature Database
Dear Sir:
I am interested in the subject of signature verification. Do you have any
signature database that is set up for signature research. If you have some,
I would appreciate it if you could tell me how to access your database.
Thank you very much for your.
Ke Han
Vision and Nueral Network Laboratory
Department of Computer Science
Wayne State University
Detroit, MI 48201
Tel: (313) 577-5070
Fax: (313) 577-6868
------------------------------
From: Ian Dryden <iand@amsta.leeds.ac.uk>
Date: Mon, 13 Sep 93 16:24:47 BST
Subject: Research Fellow Post - Leeds, UK
THE UNIVERSITY OF LEEDS
DEPARTMENT OF STATISTICS
Research Fellow
A research project on ESTIMATING POPULATION CHARACTERISTICS AND MOVEMENTS
OF BIOLOGICAL OBJECTS THROUGH IMAGE SEQUENCES has been funded by the
AFRC for three years from 1st October, 1993. It is a joint link
project with Silsoe Research Institute, Bedfordshire. A research fellow
is required to work on this project under the supervision
of Professor K.V. Mardia, Professor J.T. Kent (University of Leeds) and
Robin Tillett (Silsoe Research Institute). The large image analysis group
in the Department of Statistics will also be involved in the work.
The main objectives of the project are to estimate population characteristics
such as mean size and shape of biological objects and to statistically
summarize the movement of biological objects through image sequences.
The methodology will be focused on two applications in fisheries and agriculture.
Applicants should have a good background in Statistics/Mathematics
with a Ph.D (or near completion), preferably related to image analysis or
spatial statistics, and some computing experience.
The appointment, tenable for a period of three years, will commence on
1st October, 1993 or soon after and the salary will be on the scale for
Research Staff Grade 1A (12,828-20,442 Pounds) according to qualifications
and experience.
Informal enquiries may be made to
Professor K.V. Mardia. Tel: 0532 - 335101
e-mail: k.v.mardia@uk.ac.leeds
or
Dr. C.C. Taylor. Tel: 0532 - 335168
e-mail: charles@uk.ac.leeds.amsta
Application forms and further particulars may be obtained from the
Personnel Office (Academic Section), The University of Leeds, Leeds, LS2 9JT.
Tel: 0532 - 335771, quoting reference number 53/1. Closing date for
applications will be announced in the press advertisement.
The University of Leeds promotes an equal opportunities policy.
------------------------------
Date: Wed, 8 Sep 93 11:52:59 +0200
From: joachim@wgs.estec.esa.nl
Subject: REQUEST FOR INFO: Experts for AI in sci.data.processing in Europe
Dear netters,
the subject says it almost completely:
I would like to compile a list with the names of the experts or institutes
which have a particular interest in the field of applying Artificial Intelligence
to scientific data processing (low level feature extraction to high level fusion
and interpretation of data). They should be in Europe (it seems somehow much
easier to get information from the States - are we over here not doing relevant
work?).
If those people have some connections to the space domain, this would be an
additional plus. We would like to get some activity started in this domain and
need a clear view of what the state of the art is. If anybody is interested I
can mail the results.
Thanks for your time and effort
joachim fuchs
European Space Agency
= esa/estec-WGS c/o Joachim Fuchs =
= Keplerlaan 1 Telephone: +31/1719-85296 =
= Postbus 299 Telefax: +31/1719-85419 =
= NL-2200 AG Noordwijk Email: joachim@wgs.estec.esa.nl or =
= The Netherlands jfuchs@estec.estec.esa.nl =
------------------------------
Date: Mon, 13 Sep 93 20:52:57 -0500
From: "Igor Tulchinsky" <p00867@psilink.com>
Subject: Re: Breakthrough technologies
| I am seeking breakthrough technologies. |
| |
| Properly developing such technologies |
| requires a combination of resources |
| that its owners are unlikely to have |
| simply because the acquisition of such |
| resources is an industry in itself. |
| |
| Timely access to capital markets, |
| connections in the industry necessary |
| for forming corporate partnerships, |
| and reputation are all needed to |
| take a technology to its full potential. |
| |
| If you are an owner of a breakthrough |
| technology, whether you are a scientist |
| or a corporation, I may be able to |
| provide you with all the key ingredients |
| for developing your technology to the |
| fullest extent. |
| |
| Please send me e-mail and I will be |
| glad to give you more specific |
| information. |
| |
| Sincerely, |
| |
| |
| Igor Tulchinsky |
------------------------------
Date: Mon, 13 Sep 93 17:05:09 EDT
From: Dr Kevin Bowyer <kwb@tortugas.csee.usf.edu>
Subject: Final Program: Machine Learning in Computer Vision: What, Why and How?
AAAI Fall Symposium Series
Machine Learning in Computer Vision: What, Why and How?
Final Program
October 22 - 24, 1993
Sheraton Imperial Hotel and Convention Center
Research Triangle Park
Raleigh, North Carolina
(registration is limited-- e-mail fss@aaai.org for registration information)
Friday, October 22
9:00 - 10:30-- Exciting and Controversial Invited talks on Learning and Vision
Task-Oriented Vision Learning, Tom Mitchell, Carnegie-Mellon University
In what sense might vision be learned?, Chris Brown, University of Rochester
11:00 - 12:30-- moderated by Diane Cook, University of Texas at Arlington
Incremental Modelbase Updating: Learning New Model Sites
Kuntal Sengupta and Kim L. Boyer, The Ohio State University
Learning Image to Symbol Conversion
Malini Bhandaru, Bruce Draper and Victor Lesser, University of Massachusetts at Amherst
Transformation-invariant Indexing and Machine Discovery for Computer Vision
Darrell Conklin, Queen's University
Recognition and Learning of Unknown Objects in a Hierarchical Knowledge-base
L. Dey, P.P. Das, and S. Chaudhury, I.I.T., Delhi
Unsupervised Learning of Object Models
C. K. I. Williams, R. S. Zemel, Univ. of Toronto; M. C. Mozer, Univ. of Colorado
2:00 - 3:30-- moderated by Pat Langley, Siemens Corporate Research
Learning and Recognition of 3-D Objects from Brightness Images
Hiroshi Murase and Shree K. Nayar, Columbia University
Adaptive Image Segmentation Using Multi-Objective Evaluation and Hybrid Search Methods
Bir Bhanu, Sungkee Lee, Subhodev Das, University of California
Learning 3D Object Recognition Models from 2D Images
Arthur R. Pope and David G. Lowe, University of British Columbia
Matching and Clustering: Two Steps Towards Automatic Objective Model Generation
Patric Gros, LIFIA, Grenoble, France
Learning About A Scene Using an Active Vision System
P. Remagnino, M. Bober and J. Kittler, University of Surrey, UK
4:00 - 5:30-- moderated by Bruce Draper, University of Massachusetts
Learning Indexing Functions for 3-D Model-Based Object Recognition
Jeffrey S. Beis and David G. Lowe, University of British Columbia
Non-accidental Features in Learning
Richard Mann and Allan Jepson, University of Toronto
Feature-Based Recognition of Objects
Paul A. Viola, Massachusetts Institute of Technology
Learning Correspondences Between Visual Features and Functional Features
Hitoshi Matsubara, Katsuhiko Sakaue and Kazuhiko Yamamoto, ETL, Japan
A Self-Organizing Neural Network that Learns to Detect and Represent
Visual Depth from Occlusion Events
Johnathon A. Marshall and Richard K. Alley, University of North Carolina
Saturday, October 23
9:00 - 10:30-- Exciting and Controversial Invited talks on Learning and Vision
Machine Learning and Computer Vision: An odd couple that could be ideal
Ramesh Jain, University of California at San Diego.
Reinforcement Learning and Computer Vision
Rich Sutton, GTE Research Labs
11:00 - 12:30-- moderated by Sridhar Mahadevan, University of South Florida
Learning from the Schema Learning System
Bruce Draper, University of Massachusetts
Learning Symbolic Names for Perceived Colors
J.M. Lammens and S.C. Shapiro, SUNY Buffalo
Extracting a Domain Theory from Natural Language to
Construct a Knowledge Base for Visual Recognition
Lawrence Chachere and Thierry Pun, University of Geneva
Symbolic and Subsymbolic Learning for Vision: Some Possibilities
Vasant Honavar, Iowa State University
A Vision-Based Learning Method for Pushing Manipulation,
Marcos Salganicoff, Univ. of Pennsylvania; Giorgio Metta, Andrea Oddera
and Giulio Sandini, University of Genoa.
2:00 - 3:30-- moderated by Randall Nelson, University of Rochester
A Classifier System for Learning Spatial Representations Based
on a Morphological Wave Propagation Algorithm
Michael M. Skolnick, R.P.I.
Evolvable Modeling: Structural Adaptation Through Hierarchical Evolution
for 3-D Model-based Vision
Thang C. Nguyen, David E. Goldberg, Thomas S. Huang, University of Illinois
Developing Population Codes for Object Instantiation Parameters
Richard S. Zemel, Geoffrey E. Hinton, University of Toronto
Integration of Machine Learning and Vision into an Active Agent Paradigm
Peter W. Pachowicz, George Mason University
Assembly plan from observation
K. Ikeuchi and S.B. Kang, Carnegie-Mellon University
4:00 - 5:30-- moderated by Robin Murphy, Colorado School of Mines
Learning Shape Models for a Vision Based Human-Computer Interface
Jakub Segen, A.T.\&T. Bell Laboratories
Learning Visual Speech
G. J. Wolff, K. V. Prasad, D. G. Stork & M. Hennecke, Ricoh California Research Center
Learning open loop control of complex motor tasks
Jeff Schneider, University of Rochester
Issues in Learning from Noisy Sensory Data
J. Bala and P. Pachowicz, George Mason University
Learning combination of evidence functions in object recognition
D. Cook, L. Hall, L. Stark and K. Bowyer, University of South Florida
Sunday, October 24
9:00 - 10:30-- moderated by Abraham Waksman, Air Force Office of Scientific Research
Exciting and Controversial Panel Discussion:
Managing resource boundedness and achieving scale-up
with the help of machine learning
11:00 - 12:30-- moderated by Bir Bhanu, University of California at Riverside
Learning for Vision: Up with the Gigabyte! Death to the Functional View!
Randal Nelson, University of Rochester
Learning to Eliminate Background Effects in Object Recognition
Robin R. Murphy, Colorado School of Mines
The Prax Approach to Learning a Large Number of Texture Concepts
J. Bala, R. Michalski, and J. Wnek, George Mason University
Non-Intrusive Gaze Tracking Using Artificial Neural Networks
Dean A. Pomerleau and Shumeet Baluja, Carnegie Mellon University
Toward a General Solution to the Symbol Grounding Problem: Combining
Machine Learning and Computer Vision
Paul Davidsson, Lund University
------------------------------
End of VISION-LIST digest 12.41
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