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with partial support by The Office of Naval Research
Organizers:
Peter Olver
School of Mathematics
University of Minnesota
olver@math.umn.edu
Allen Tannenbaum
Department
of Computer and Electrical Engineering
University of Minnesota
tannenba@ee.umn.edu
Donald
Geman
Department of Mathematics and Statistics
University of Massachusetts at Amherst
geman@math.umass.edu
Yali
Amit
Department
of Statistics
The University of Chicago
amit@galton.uchicago.edu
Steven
Zucker
Computer Science and Electrical Engineering
Yale University
steven.zucker@yale.edu
This workshop will concentrate on mathematical and practical issues arising in the higher level processes in image analysis. These include object recognition, optical character and handwriting recognizers, printed-circuit board inspection systems, and quality control devices, motion detection, robotic control by visual feedback, theory of shape, reconstruction of objects from stereoscopic view and/or motion, and many others. Shape theory is of fundamental importance since it is the bottleneck between high and low level vision, and forms the bridge between the two workshops on vision. The recent geometric partial differential equation methods have been essential in throwing new light on this very difficult problem area. There are two classical approaches to approximating the shape of objects. The first is based on diffusion and often leads to the (Gaussian) smoothing of contour information. The resulting scale-space may often be viewed as generated by parabolic operators which progressively and globally smooth shapes. The second approach is based on morphological morphology operations that represent the interior of shapes as sets, e.g., a collection of disks. The resulting morphological space can be viewed as being defined via a hyperbolic operator whose weak or viscosity solutions progressively smooth shapes in a local manner. The geometric PDE approach based on abstract conservation principles, Hamilton-Jacobi theory, and curvature driven flows leads to a computational theory of shape that naturally characterizes its computational elements including protrusions, parts, bends, and seeds (which show where to place the components of a shape). Stochastic processes, including Markov random fields, have been used in a Bayesian framework to incorporate prior constraints on a smoothness and the regularities of discontinuities into algorithms for image restoration and reconstruction. Sequential decision theory has been used to develop algorithms for efficient identification of objects in a scene, including handwritten characters, roads in satellite imagery, and faces. Deformable templates have been used to automate the identification of structures, both normal and pathological, in medical imagery. Since human vision relies on a variety of symmetry transformations, including Euclidean, affine and projective invariance, the incorporation of group theory and invariants into the image processing equations has been of great importance in the design of algorithms, both continuous and numerical.
A primary goal of this workshop is to educate and interest mathematicians in the mathematical and scientific problems that arise in the study of computer and natural vision. There will be a mix of tutorials in natural and artificial vision and mathematical talks on the theoretical foundations of existing and proposed vision systems. An additional goal is to bring together researchers working in these areas to compare results and to collaborate on ways to integrate these approaches into a powerful overall mathematical approach to vision. Unlike numerical analysis, the computer vision community has yet to establish "benchmark" tests for comparison of the various visual processing systems that are available, making direct and rigorous comparisons difficult. In this workshop we propose to initiate the development of a set of benchmark visual images that can be used for overall comparison purposes.
Monday | Tuesday |
MONDAY,
NOVEMBER 13 All talks are in Lecture Hall EE/CS 3-180 unless otherwise noted. |
||
---|---|---|
8:30 am | Coffee and Registration |
Reception Room EE/CS 3-176 |
9:10 am | Willard Miller, Fred Dulles, and Peter Olver | Introduction |
9:30 am | Donald
Geman University of Massachusetts at Amherst |
Coarse-to-Fine Object Detection Talk slides |
10:30 am | Break | Reception Room EE/CS 3-176 |
11:00
am- |
Pietro
Perona Caltech |
Unsupervised Learning of Models for Object Recognition |
2:00-3:00 pm | Alan L. Yuille The Smith-Kettlewell Eye Research Institute |
Order Parameters for Detecting Target Curves in Images: When Does High Level Knowledge Help? Talk pdf postscript |
4:00 pm | IMA
Tea A variety of appetizers and beverages will be served. |
IMA East, 400 Lind Hall |
TUESDAY,
NOVEMBER 14 All talks are in Lecture Hall EE/CS 3-180 unless otherwise noted. |
||
9:15 am | Coffee | Reception Room EE/CS 3-176 |
9:30 am | Steven
Zucker Yale University |
How Folds Cut a Scene |
10:30 am | Break | Reception Room EE/CS 3-176 |
11:00
am- 12:00 pm |
Irving
Biederman University of Southern California |
Neural and Psychophysical Aspects of Visual Shape Recognition |
1:15 pm | Tai
Sing Lee Carnegie Mellon University |
The Influence of High Level Vision on Early Visual Processing in the Brain |
2:00 pm | Yali
Amit The University of Chicago |
A Neural Architecture for Learning, Detecting and Recognizing Objects Talk pdf postscript |
3:00 pm | Break | Reception Room EE/CS 3-176 |
3:30 pm | Panel
Discussion: Irving Biederman (University of Southern California), Donald Geman, (University of Massachusetts at Amherst), and Pietro Perona (Caltech) |
TBA |
WEDNESDAY,
NOVEMBER 15 All talks are in Lecture Hall EE/CS 3-180 unless otherwise noted. |
||
9:15 am | Coffee | Reception Room EE/CS 3-176 |
9:30 am |
Ian L. Dryden University of Nottingham |
Statistical Shape Analysis in High-Level Vision Talk pdf postscript |
10:30 am | Break | Reception Room EE/CS 3-176 |
11:00
am- 12:00 pm |
Jayant
M. Shah Northeastern University |
Local Symmetries and Segmentaton of Shapes Talk slides |
2:00 pm | Peter N. Belhumeur Yale University |
Shedding Light on Illumination |
3:00 pm | Break | Reception Room EE/CS 3-176 |
3:30 pm | David
Mumford Brown University |
What is the Space of Shapes and What Can We Do With It? |
4:15-5:00 pm | Song-Chun
Zhu Ohio State University |
Tackling Visual Complexity by Statistical Learning and Stochastic Computing Talk pdf |
THURSDAY,
NOVEMBER 16 All talks are in Lecture Hall EE/CS 3-180 unless otherwise noted. |
||
9:15 am | Coffee | Reception Room EE/CS 3-176 |
9:30 am | Davi
Geiger Courant Institute, NYU |
Measuring the Convexity of Shapes |
10:30 am | Break | Reception Room EE/CS 3-176 |
11:00
am- 12:00 pm |
Laurent
Younes CNRS |
Metrics, Shapes and Deformations |
2:00 pm | Benjamin B. Kimia Brown University |
Symmetry Maps and Transforms for Perceptual Organization and Object Recognition |
3:00 pm | Break | Reception Room EE/CS 3-176 |
3:30-4:30 pm | Ernst D. Dickmanns Universität der Bundeswehr München |
Talk pdf |
6:00 pm | Workshop Dinner | Shuang Chen Restaurant |
FRIDAY,
NOVEMBER 17 All talks are in Lecture Hall EE/CS 3-180 unless otherwise noted. |
||
9:15 am | Coffee | Reception Room EE/CS 3-176 |
9:30 am | John Oliensis NEC Research Institute Inc. |
From Movies to Geometric 3D Models: the Structure-from-Motion Problem |
10:30 am | Break | Reception Room EE/CS 3-176 |
11:00
am- 12:00 pm |
Rama
Chellappa University of Maryland |
Face Recognition and Verification in Still and Video Images |
Contributed
Talks The afternoon talks are in Lind Hall 409 unless otherwise noted. |
||
2:00 pm | Xavier
Pennec INRIA Sophia - Project Epidaure |
Probabilities and Statistics on Riemannian Manifolds: Basic Tools for Geometric Measurements Talk pdf |
2:30 pm | Mohamed
Ben Hadj Rhouma Georgia Institute of Technology |
Image Segmentation Using Integrate-and-Fire Oscillators |
3:00-3:30 pm | Jason
Miller Truman State University |
Relative Critical Sets and Ridges Sets of Functions |
Monday | Tuesday |
Name | Department | Affiliation |
---|---|---|
Yali Amit | Statistics | The University of Chicago |
Peter Belhumeur | Electrical Engineering and Computer Science | Yale University |
Mohamed Ben Rhouma | Center for Dynamical Systems and Nonlinear Studies | Georgia Institute of Technology |
Santiago Betelu | Institute for Mathematics and its Applications | |
Irving Biederman | Neuroscience Prog. and Dept.'s of Psych. and CSci | University of Southern California |
Mireille Boutin | Mathematics | University of Minnesota |
Michele Carriero | Mathematics | University of Lecce |
Jamylle Carter | Institute for Mathematics and its Applications | |
Vicent Caselles | Tecnologia | Universitat Pompeu-Fabra |
Rama Chellappa | Center for Automation Research | University of Maryland |
Li-Tien Cheng | Institute for Mathematics and its Applications | |
Alessandro Chiuso | Electronics and Informatics | University of Padova |
Fabio Cuzzolin | UCLA | |
Ernst Dickmanns | Institut für Systemdynamik und Flugmechanik | Universität der Bundeswehr München |
Ian Dryden | Mathematical Sciences | University of Nottingham |
Fred Dulles | Institute for Mathematics & its Applications | |
Selim Esedoglu | Institute for Mathematics and its Applications | |
Francois Fleuret | Projet Imedia | INRIA-Rocquencourt |
Davi Geiger | Computer Science and Neural Science | Courant Institute, NYU |
Donald Geman | Mathematics and Statistics | University of Massachusetts at Amherst |
Jack Goldfeather | Mathematics and Computer Science | Carleton College |
Fernando Carvalho Gomes | SITE | University of Ottawa |
Robert Gulliver | Mathematics | University of Minnesota |
Dirk Horstmann | Mathematisches Institut | Universitat zu Koeln |
Dan Kersten | Psychology | University of Minnesota |
Benjamin B. Kimia | Engineering | Brown University |
Samuel Krempp | Un. of Massachussetts | |
Christopher Lang | Indiana University Southeast | |
Antonio Leaci | Mathematics | University of Lecce |
Tai-Sing Lee | Comp. Sci & Cnbc | Carnegie Mellon University |
Andrey Litvin | Electrical and Computer Engineering | Boston University |
Darek Madej | Advanced Development | Symbol Technologies |
Andres Sole Martinez | Universitat Pompeu Fabra | |
Massimo Mascaro | Statistics | University of Chicago |
Donald E. McClure | Applied Mathematics | Brown University |
Peter McCoy | Mathematics | U.S. Naval Academy |
Jason Miller | Mathematics & Computer Science | Truman State University |
Ronald Miller | Ford Research Laboratory | Ford |
Willard Miller | Institute for Mathematics & its Applications | |
David Mumford | Applied Mathematics | Brown University |
John Oliensis | NEC Research Institute Inc. | |
Peter Olver | Mathematics | University of Minnesota |
Victor Patrangenaru | Mathematics and Statistics | Georgia State University |
Xavier Pennec | Unite de Recherche | INRIA Epidaure |
Pietro Perona | Electrical Engineering | Caltech |
Mary Pugh | Mathematics | University of Pennsylvania |
Anand Rangarajan | Diagnostic Radiology & Elec. Eng. | Yale University School of Medicine |
Christopher S. Raphael | Mathematics & Statistics | University of Massachusetts, Amherst |
Erik Schlicht | Psychology | University of Minnesota |
Kevin Schweiker | Engineering | Freestyle Technologies, Inc. |
Jayant M. Shah | Mathematics | Northeastern University |
Shuli Cohen Shwartz | U.C.G. Technologies Ltd. | The Technion Enterpreneurial Incubator Co. |
Stefano Soatto | Electrical Engineering | Washington University |
Allen Tannenbaum | Electrical & Computer Engineering | Georgia Institute of Technology |
Franco Tomarelli | Matematica | Politecnico di Milano |
Laurent Younes | Le Centre de Mathématiques et de Leurs App. | CNRS |
Alan Yuille | The Smith-Kettlewell Eye Research Institute | |
Song Chun Zhu | Computer & Information Sciences | Ohio State University |
Steven Zucker | Computer Science and Electrical Engineering | Yale University |
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