Path: utzoo!utgpu!news-server.csri.toronto.edu!cs.utexas.edu!sun-barr!apple!agate!ucbvax!ADS.COM!Vision-List-Request From: Vision-List-Request@ADS.COM (Vision-List moderator Phil Kahn) Newsgroups: comp.ai.vision Subject: Vision-List digest delayed redistribution Message-ID: <9012010500.AA26033@deimos.ads.com> Date: 30 Nov 90 21:54:50 GMT Sender: daemon@ucbvax.BERKELEY.EDU Reply-To: Vision-List@ADS.COM Distribution: inet Organization: The Internet Lines: 350 Approved: vision-list@ads.com Vision-List Digest Fri Nov 30 13:54:50 PDT 90 - Send submissions to Vision-List@ADS.COM - Send requests for list membership to Vision-List-Request@ADS.COM Today's Topics: Converting Rosenfeld's mebib troff format to BiBtex/Refer/etc. Anyone doing PSYCHOPHYSICAL testing of image compression??? Graduate study in neural networks 7th IEEE Conference on AI Applications - Program available Questionnaire on State of the Art in CAD-Based Vision Systems ---------------------------------------------------------------------- Date: Tue, 27 Nov 90 17:06:32 -0800 From: vision@deimos.ads.com (Philip Kahn) Subject: converting Rosenfeld's mebib troff format to BiBtex/Refer/etc. Rosenfeld's bibliographies are in a format called mebib. Several readers have noted an interest in obtaining a database accessible version of his references (e.g., in BibTex or Refer format). Please contact me if you know how to do this or are interested in finding out how it can be done. thanks, phil... ------------------------------ Date: 28 Nov 90 05:38:03 GMT From: David Honig Subject: anyone doing PSYCHOPHYSICAL testing of image compression??? I'm interested in obtaining references to groups doing psychophysical research on image and image-sequence compression methods. Where the "psychophysical" study can be defined as anything more formal than asking your neighbor, "hey Joe, how do ya' think this version looks?" (which I'm afraid is all too common!) Thanks, David ------------------------------ Date: Fri, 30 Nov 90 15:13:20 -0500 From: caroly@park.bu.edu Subject: graduate study in neural networks GRADUATE PROGRAM IN COGNITIVE AND NEURAL SYSTEMS (CNS) AT BOSTON UNIVERSITY Gail A.Carpenter & Stephen Grossberg, Co-Directors The Boston University graduate program in Cognitive and Neural Systems offers comprehensive advanced training in the neural and computational principles, mechanisms, and architectures that underly human and animal behavior, and the application of neural network architectures to the solution of outstanding technological problems. Applications for Fall, 1991 admissions and financial aid are now being accepted for both the MA and PhD degree programs. To obtain a brochure describing the CNS Program and a set of application materials, write or telephone: Cognitive & Neural Systems Program Boston University 111 Cummington Street, Room 240 Boston, MA 02215 (617) 353-9481 or send a mailing address to: caroly@park.bu.edu Applications for admission and financial aid should be received by the Graduate School Admissions Office no later than January 15. Applicants are required to submit undergraduate (and, if applicable, graduate) transcripts, three letters of recommendation, and Graduate Record Examination (GRE) scores. The Advanced Test should be in the candidate's area of departmental specialization. GRE scores may be waived for MA candidates and, in exceptional cases, for PhD candidates, but absence of these scores may decrease an applicant's chances for admission and financial aid. Description of the CNS Program: The Cognitive and Neural Systems (CNS) Program provides advanced training and research experience for graduate students interested in the neural and computational principles, mechanisms, and architectures that underly human and animal behavior, and the application of neural network architectures to the solution of outstanding technological problems. Students are trained in a broad range of areas concerning cognitive and neural systems, including vision and image processing; speech and language understanding; adaptive pattern recognition; associative learning and long-term memory; cognitive information processing; self-organization; cooperative and competitive network dynamics and short-term memory; reinforcement, motivation, and attention; adaptive sensory-motor control and robotics; and biological rhythms; as well as the mathematical and computational methods needed to support advanced modeling research and applications. The CNS Program awards MA, PhD, and BA/MA degrees. The CNS Program embodies a number of unique features. Its core curriculum consists of eight interdisciplinary graduate courses each of which integrates the psychological, neurobiological, mathematical, and computational information needed to theoretically investigate fundamental issues concerning mind and brain processes and the applications of neural networks to technology. Each course is taught once a week in the evening to make the program available to qualified students, including working professionals, throughout the Boston area. Students develop a coherent area of expertise by designing a program that includes courses in areas such as Biology, Computer Science, Engineering, Mathematics, and Psychology, in addition to courses in the CNS core curriculum. The CNS Program prepares Ph.D. students for thesis research with scientists in one of several Boston University research centers or groups, and with Boston-area scientists collaborating with these centers. The unit most closely linked to the Program is the Center for Adaptive Systems. The Center for Adaptive Systems is also part of the Boston Consortium for Behavioral and Neural Studies, a Boston-area multi-institutional Congressional Center of Excellence. Another multi-institutional Congressional Center of Excellence focussed at Boston University is the Center for the Study of Rhythmic Processes. Other research resources include distinguished research groups in dynamical systems within the mathematics department; in theoretical computer science within the Computer Science Department; in biophysics and computational physics within the Physics Department; in sensory robotics, biomedical engineering, computer and systems engineering, and neuromuscular research within the Engineering School; and in neurophysiology, neuroanatomy, and neuropharmacology at the Medical School. ------------------------------ Date: Wed, 28 Nov 90 10:50:28 EST From: finin@PRC.Unisys.COM Subject: 7th IEEE Conference on AI Applications - Program available A copy of the advanced program of the the Seventh IEEE Conference on Artificial Intelligence Applications (CAIA-91) is now available and can be obtained by sending email to the mail agent CAIA-PROGRAM@PRC.UNISYS.COM. This agent will respond to all messages by returning via email the text of the advanced program, including a registration form and an accommodations form. CAIA-91 will be held on February 24-28, 1991 at the Fontainbleau Hilton Resort and Spa in Miami Beach, Florida. A series of twelve half-day tutorials will be held on February 24th and 25th. The technical program will be held on February 26th through the 28th. This will include 73 submitted papers, a number panels and the following invited talks: AI in Biology and Challenges of the Human Genome Project, Bruce Buchanan, University of Pittsburgh Technology and People, Eric Bloch, former director, NSF Toward Intelligent Systems in the DoD, Major Steven Cross, DARPA Application Projects at ICOT, K. C. Furukawa, ICOT The ESPRIT Program, D. E. Talbot, Commission of the European Communities "Applying Common Sense" - Necessity or Oxymoron?, Doug Lenat, MCC For more information about the conference in general, or to request hardcopy of the advanced program, contact: IEEE Computer Society, 1730 Massachusetts Ave. NW, Washington, DC 20036, 202-371-1013, fax: 202-728-0884. For more information about the technical program, contact: Tim Finin, Unisys Center for Advanced Information Tech., PO Box 517, Paoli PA 19301, 215-648-2840, fax: 215-648-2288, finin@prc.unisys.com. ------------------------------ Date: Wed, 28 Nov 90 18:03:47 EST From: Dr. Kevin Bowyer Subject: Questionnaire on State of the Art in CAD-Based Vision Systems IEEE Workshop on Directions in Automated ``CAD-Based'' Vision June 2-3, 1991 Maui, Hawaii (just prior to CVPR '91) Questionnaire on State of the Art in CAD-Based Vision Systems This survey form is being distributed for the purpose of organizing a panel session at the upcoming workshop on Directions in Automated ``CAD-Based'' Vision. We hope that this will serve to give the workshop a sharper focus and to facilitate some interesting discussion. Responses are solicited from all interested persons. Some representative subset of the respondents will be asked to lead a panel discussion at the workshop, organized by Avi Kak. A written report of the survey results will also be prepared. Responses are needed by January 1. You may respond by e-mail to kwb@sol.csee.usf.edu or by regular mail to Kevin Bowyer / Department of Computer Science and Engineering / University of South Florida / Tampa, Florida 33620 / USA. 1. What is the name of the system? 2. What is the system's purpose (intended application)? 3. What is the best generally accessible reference which describes the system? 4. What language(s) is the system written in? 5. What computer(s) does the system run on? 6. How long does it take to analyze the ``average'' scene of a single object? (If multiple computers are listed just above, specify which one this time is for.) 7. How long does it take to analyze the ``average'' scene of a jumbled pile of about a dozen objects in order to recognize at least one of the objects? (If multiple computers are listed just above, specify which one this time is for.) 8. Is the computational complexity of the system known? If so, what is it? (Specify order N-whatever, where N is ...) 9. What class of object shapes does the system handle? 10. Are object models entered into the system ... by hand? from a CAD system-- which one? by a set of standard images? some other method? 11. How many different objects are in the system database? 12. How many objects have been in the most complex scenes analyzed by the system? Were these all the same object or different objects? Have the objects all been made of the same material? Have the objects all been the same color? 13. Does the system use ... orthographic projection? perspective projection? orthographic with scale factor? 14. What type of imagery does the system use? range-- if so, what type(s)? intensity-- if so, grayscale or color? other-- if so, what? 15. Does the system use a single view or multiple views? 16. If the system uses multiple views, are the viewpoints fixed ahead of time? 17. If the system uses multiple views from varying viewpoints, how are they selected? 18. Does the system incorporate a ``table-top'' assumption? (That is, does it use explicit knowledge of a supporting plane for the objects?) 19. Can the system recognize occluded objects? if they share a supporting plane (example-- one behind the other on a table)? if they are laying on top of each other (example-- a pile of objects on a table)? 20. What type of image features are used by the system for matching? purely shape-based (edges, contours, junctions)? texture? color? other-- if so, what? 21. Does recognition include estimation of pose? 22. How many scenes has the system analyzed? 23. Is the lighting ... ``normal room lighting''? special lighting set up some time ago and not changed between scene analyses? optimized for each scene analysis? under automatic control of the recognition system in some way? 24. Is the matching strategy based on: interpretation trees of some type? iterative optimization techniqes? geometric hashing of some sort? other-- if so, what? 25. What do you consider the strongest point of your system? 26. What do you consider the strongest point of CAD-based vision systems generally? 27. What do you consider the weakest point of your system? 28. What do you consider the weakest point of CAD-based vision systems generally? 29. What important dimension of CAD-based vision systems is not captured in this survey? 30. E-mail and regular mail address for contacting you. ------------------------------ End of VISION-LIST ********************