Path: utzoo!utgpu!jarvis.csri.toronto.edu!rutgers!ucsd!ucbvax!ADS.COM!Vision-List-Request From: Vision-List-Request@ADS.COM (Vision-List moderator Phil Kahn) Newsgroups: comp.ai.vision Subject: Vision-List delayed redistribution Message-ID: <8909260430.AA04557@deimos.ads.com> Date: 25 Sep 89 20:40:06 GMT Sender: daemon@ucbvax.BERKELEY.EDU Reply-To: Vision-List@ADS.COM Distribution: inet Organization: The Internet Lines: 329 Approved: vision-list@ads.com Vision-List Digest Mon Sep 25 12:40:06 PDT 89 - Send submissions to Vision-List@ADS.COM - Send requests for list membership to Vision-List-Request@ADS.COM Today's Topics: New Service for Vision List: Relevant Journal Table of Contents BBS Call for Commentators: Visual Search & Complexity Subject: street address for IEEE CAIA-90 submissions 7th Intern. Conf. on Machine Learning IEEE Jrnl of Robotics and Automation Aug 89 IEEE Trans on PAMI Jul 89 ---------------------------------------------------------------------- Date: Mon, 25 Sep 89 12:14:29 PDT From: Vision-List-RequestSubject: New Service for Vision List: Relevant Journal Table of Contents Thanks to Jon Webb and the Computer Science Library at CMU, the Vision List will now be posting the table of contents for select relevant journals. These table of contents will be placed at the end of the List in order to avoid cluttering up subscriber discussion and comments. The goal of these indices is to simplify the identification of current relevant literature and help us all better manage our time. The journals include: IEEE Journal on Robotics and Automation (JRA), IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), International Journal on Computer Vision (IJCV), and Perception. We may also include CVGIP and Spatial Vision. JRA often has interesting vision articles, though it is not specifically vision oriented: please let me know if you believe it should be omitted. Comments are invited and encouraged. phil... ---------------------------------------------------------------------- Date: 19 Sep 89 05:41:53 GMT From: harnad@phoenix.princeton.edu (S. R. Harnad) Subject: BBS Call for Commentators: Visual Search & Complexity Keywords: computer vision, natural vision, complexity theory, brain Organization: Princeton University, NJ Below is the abstract of a forthcoming target article to appear in Behavioral and Brain Sciences (BBS), an international, interdisciplinary journal that provides Open Peer Commentary on important and controversial current research in the biobehavioral and cognitive sciences. Commentators must be current BBS Associates or nominated by a current BBS Associate. To be considered as a commentator on this article, to suggest other appropriate commentators, or for information about how to become a BBS Associate, please send email to: harnad@princeton.edu or write to: BBS, 20 Nassau Street, #240, Princeton NJ 08542 [tel: 609-921-7771] Analyzing Vision at the Complexity Level John K. Tsotsos Department of Computer Science, University of Toronto and The Canadian Institute for Advanced Research The general problem of visual search can be shown to be computationally intractable in a formal complexity-theoretic sense, yet visual search is widely involved in everyday perception and biological systems manage to perform it remarkably well. Complexity level analysis may resolve this contradiction. Visual search can be reshaped into tractability through approximations and by optimizing the resources devoted to visual processing. Architectural constraints can be derived using the minimum cost principle to rule out a large class of potential solutions. The evidence speaks strongly against purely bottom-up approaches to vision. This analysis of visual search performance in terms of task-directed influences on visual information processing and complexity satisfaction allows a large body of neurophysiological and psychological evidence to be tied together. Stevan Harnad INTERNET: harnad@confidence.princeton.edu harnad@princeton.edu srh@flash.bellcore.com harnad@elbereth.rutgers.edu harnad@princeton.uucp CSNET: harnad%confidence.princeton.edu@relay.cs.net BITNET: harnad1@umass.bitnet harnad@pucc.bitnet (609)-921-7771 ------------------------------ Date: 25 Sep 89 18:33:33 GMT From: finin@prc.unisys.com (Tim Finin) Subject: street address for IEEE CAIA-90 submissions Organization: Unisys Paoli Research Center, PO Box 517, Paoli PA 19301 REMINDER ----- IEEE CAIA-90 ----- DEAD LINE 9/29 ----- REMINDER 6th IEEE Conference on AI Applications For those colleagues who depend on express mailing (don't we all?), here is the street address to use: Se June Hong (Room 31-206) IBM T. J. Watson Research Center Route 134 (Kitchawan) and Taconic (PO box 218 if regular post) Yorktown Heights, NY 10598 Tim Finin finin@prc.unisys.com (internet) Unisys Paoli Research Center ..!{psuvax1,sdcrdcf,cbmvax}!burdvax!finin (uucp) PO Box 517 215-648-7446 (office), 215-386-1749 (home), ------------------------------ Posted-Date: Thu, 21 Sep 89 13:46:14 CDT From: ml90@cs.utexas.edu (B. Porter and R. Mooney) Date: Thu, 21 Sep 89 13:46:14 CDT Subject: 7th Intern. Conf. on Machine Learning@@ SEVENTH INTERNATIONAL CONFERENCE ON MACHINE LEARNING: CALL FOR PAPERS The Seventh International Conference on Machine Learning will be held at the University of Texas in Austin during June 21--23, 1990. Its goal is to bring together researchers from all areas of machine learning. The conference will include presentations of refereed papers, invited talks, and poster sessions. The deadline for submitting papers is February 1, 1990. REVIEW CRITERIA In order to ensure high quality papers, each submission will be reviewed by two members of the program committee and judged on clarity, significance, and originality. All sub- missions should contain new work, new results, or major extensions to prior work. If the paper describes a running system, it should explain that system's representation of inputs and outputs, its performance component, its learning methods, and its evalua- tion. In addition to reporting advances in current areas of machine learning, authors are encouraged to report results on exploring novel learning tasks. SUBMISSION OF PAPERS Each paper must have a cover page with the title, author's names, primary author's address and telephone number, and an abstract of about 200 words. The cover page should also give three keywords that describe the research. Examples of keywords include: PROBLEM AREA GENERAL APPROACH EVALUATION CRITERIA Concept learning Genetic algorithms Empirical evaluation Learning and planning Empirical methods Theoretical analysis Language learning Explanation-based Psychological validity Learning and design Connectionist Machine discovery Analogical reasoning Papers are limited to 12 double-spaced pages (including figures and references), formatted with twelve point font. Authors will be notified of acceptance by Friday, March 23, 1990 and camera-ready copy is due by April 23, 1990. Send papers (3 copies) to: For information, please contact: Machine Learning Conference Bruce Porter or Raymond Mooney Department of Computer Sciences ml90@cs.utexas.edu Taylor Hall 2.124 (512) 471-7316 University of Texas at Austin Austin, Texas 78712-1188 ------------------------------ Date: Fri, 22 Sep 89 10:29:21 EDT Subject: IEEE Jrnl of Robotics and Automation Aug 89 From: ES.Library@B.GP.CS.CMU.EDU REFERENCES [1] Ahmad, Shaheen and Luo, Shengwu. Coordinated Motion Control of Multiple Robotic Devices for Welding and Redundancy Coordination through Constrained Optimization in Cartesian Space. IEEE Journal of Robotics and Automation 5(4):409-417, August, 1989. [2] ElMaraghy, Hoda A. and Payandeh, S. Contact Prediction and Reasoning for Compliant Robot Motions. IEEE Journal of Robotics and Automation 5(4):533-538, August, 1989. [3] Hannaford, Blake. A Design Framework for Teleoperators with Kinesthetic Feedback. IEEE Journal of Robotics and Automation 5(4):426-434, August, 1989. [4] Jacak, Witold. A Discrete Kinematic Model of Robots in the Cartesian Space. IEEE Journal of Robotics and Automation 5(4):435-443, August, 1989. [5] Kumar, Vijay and Waldron, Kenneth J. Suboptimal Algorithms for Force Distribution in Multifingered Grippers. IEEE Journal of Robotics and Automation 5(4):491-498, August, 1989. [6] Kusiak, Andrew. Aggregate Scheduling of a Flexible Machining and Assembly System. IEEE Journal of Robotics and Automation 5(4):451-459, August, 1989. [7] Li, Chang-Jin. An Efficient Method for Linearization of Dynamic Models of Robotic Manipulators. IEEE Journal of Robotics and Automation 5(4):397-408, August, 1989. [8] Martin, D. P.; Baillieul, J.; and Hollerbach, J. M. Resolution of Kinematic Redundancy Using Optimization Techniques. IEEE Journal of Robotics and Automation 5(4):529-533, August, 1989. [9] Murray, John J. and Lovell, Gilbert H. Dynamic Modeling of Closed-Chain Robotic Manipulators and Implications for Trajectory Control. IEEE Journal of Robotics and Automation 5(4):522-528, August, 1989. [10] Pfeffer, Lawrence E.; Khatib, Oussama; and Hake, J. Joint Torque Sensory Feedback in the Control of a PUMA Manipulator. IEEE Journal of Robotics and Automation 5(4):418-425, August, 1989. [11] Rodriguez, Guillermo. Recursive Forward Dynamics for Multiple Robot Arms Moving a Common Task Object. IEEE Journal of Robotics and Automation 5(4):510-521, August, 1989. [12] Seraji, Homeyoun. Configuration Control of Redundant Manipulators: Theory and Implementation. IEEE Journal of Robotics and Automation 5(4):472-490, August, 1989. [13] Sorensen, Brett R.; Donath, Max; Yang, Guo-Ben; and Starr, Roland C. The Minnesota Scanner: A Prototype Sensor for Three-Dimensional Tracking of Moving Body Segments. IEEE Journal of Robotics and Automation 5(4):499-509, August, 1989. [14] Tsujimura, Takeshi and Yabuta, Tetsuro. Object Detection by Tactile Sensing Method Employing Force/Torque Information. IEEE Journal of Robotics and Automation 5(4):444-450, August, 1989. [15] Wang, Y. F. and Aggarwal, J. K. Integration of Active and Passive Sensing Techniques for Representing Three-Dimensional Objects. IEEE Journal of Robotics and Automation 5(4):460-471, August, 1989. ------------------------------ Date: Fri, 22 Sep 89 10:30:50 EDT Subject: IEEE Trans on PAMI Jul 89 From: ES.Library@B.GP.CS.CMU.EDU REFERENCES [1] Chen, David Shi. A Data-Driven Intermediate Level Feature Extraction Algorithm. IEEE Transactions on Pattern Analysis and Machine Intelligence PAMI-11(7):749-758, July, 1989. [2] Chen, Ming-Hua and Yan, Ping-Fan. A Multiscale Approach Based on Morphological Filtering. IEEE Transactions on Pattern Analysis and Machine Intelligence PAMI-11(7):694-700, July, 1989. [3] Gath, I. and Geva, A. B. Unsupervised Optimal Fuzzy Clustering. IEEE Transactions on Pattern Analysis and Machine Intelligence PAMI-11(7):773-781, July, 1989. [4] Mallat, Stephane G. A Theory for Multiresolution Signal Decomposition: The Wavelet Representation. IEEE Transactions on Pattern Analysis and Machine Intelligence PAMI-11(7):674-693, July, 1989. [5] Maragos, Petros. Pattern Spectrum and Multiscale Shape Representation. IEEE Transactions on Pattern Analysis and Machine Intelligence PAMI-11(7):701-716, July, 1989. [6] Peleg, Shmuel; Werman, Michael; and Rom, Hillel. A Unified Approach to the Change of Resolution: Space and Grey-Level. IEEE Transactions on Pattern Analysis and Machine Intelligence PAMI-11(7):739-742, July, 1989. [7] Sanz, Jorge L. C. and Huang, Thomas T. Image Representation by Sign Information. IEEE Transactions on Pattern Analysis and Machine Intelligence PAMI-11(7):729-738, July, 1989. [8] Shah, Y. C,; Chapman, R.; and Mahani, R. B. A New Technique to Extract Range Information. IEEE Transactions on Pattern Analysis and Machine Intelligence PAMI-11(7):768-773, July, 1989. [9] Strobach, Peter. Quadtree-Structured Linear Prediction Models for Image Sequence Processing. IEEE Transactions on Pattern Analysis and Machine Intelligence PAMI-11(7):742-748, July, 1989. [10] Usner, Michael and Eden, Murray. Multiresolution Feature Extraction and Selection for Texture Segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence PAMI-11(7):717-728, July, 1989. [11] Yeshurun, Yehezkel and Schwartz, Eric L. Cepstral Filtering on a Columnar Image Architecture: A Fast Algorithm for Binocular Stereo Segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence PAMI-11(7):759-767, July, 1989. ------------------------------ End of VISION-LIST ********************