David B. Cooper
- email: cooper@lems.brown.edu
-
office: Barus and Holley, Rm. 318
- phone: (401) 863-2601
- fax: (401) 863-1157
- Box D, Engineering
Brown University
Providence, RI 02912 - phone: (401) 863-2601
David B. Cooper
Professor of Engineering,
Fellow of the IEEE
B.Sc. and Sc.M in Electrical
Engineering, MIT 1957.
Ph.D. in Applied Mathematics,
Columbia University, 1966.
Industrial Experience: Engineer and then Senior Engineer, Sylvania Electric Products and then Raytheon Corporation, working on statistical communications and radar research and advanced development, 1957-1966. Over the years, I have consulted for a number of industrial and government organizations.
Brown University: Faculty member since 1966.
Course Teaching: In recent years, I have been teaching undergraduate courses in Image Understanding, and Signals And Systems. I have been teaching graduate courses in Pattern Recognition And Computer Vision, and Applied Stochastic Processes.
Recent and Present Principal Research Investigations: Stochastic geometry/Computer Vision/Pattern Recognition/Machine learning.
My recent and present research interests focus on modeling, manipulating and inferring of semantically meaningful 2D and 3D geometry from images taken by a moving camera or multiple cameras in different positions or from dense-data laser scans, e.g., LIDAR 3D data sets, and on applications to the humanities. Computer Vision is replete with approaches that illustrate the possibilities of partially solving interesting tasks. My interests are in design and in understanding the limitations: what are the tradeoffs in achievable accuracy, minimal computational cost, and system ‘practicality’. This requires insightful appropriate modeling of pattern class geometry, image formation, and uncertainty in prior knowledge and in data measurement and subsequent information extraction. My interest is in both still and moving 3D scenes. One of the ultimate goals of this work is estimation of virtual 3D immersive environments for purposes of virtual entertainment-travel, remote collaboration for work or scientific research, etc.
The design of complex
pattern-recognition/computer
Among research projects in progress are: 1) A unified Bayesian approach, based on image continuous intensity and edges (such as those from silhouettes and self occlusions) to 3D reconstruction from images taken by cameras in different positions; 2) Low probability of error vehicle class recognition in one or more video clips where the video clips can cover view regions that are disjoint; 3) Change detection based on estimating 3D scene geometry and appearance from multiview images, and then checking for 3D change based on the consistency of a new image taken from a new arbitrary position under new arbitrary illumination conditions. Emphasis in 3) is on image edge data which arises from 3D ridges or 3D curves which are boundaries between different materials, e.g., metal/glass or concrete/glass.
Embedded in the preceding subject matter is what I call the ‘1000’ camera problem: why are ad hoc networks of huge numbers of battery-powered inexpensive cameras having onboard processing and wireless communication capability potentially extremely useful, and how might such systems be analyzed and designed?
My interest in applications to the humanities arises from my feeling that just as Engineering has been highly successful in research and advanced development in biology and medicine, it can also be highly successful in the humanities. My group has done preliminary work in digital virtual sculpting, is substantially involved in extracting information from archaeological site-excavation artifacts, and is considering problems of information handling in public policy.
In applications to archaeology, my group has pioneered estimation of ceramic vessel representations from dense-data laser scans of vessel fragments found at an archaeological site, a first system for automatic Bayesian estimation of pot models from potsherds when a pot has broken into a small number of potsherds, and the preliminary semiautomatic virtual assembly of sculpture based on dense-data laser scans of their scattered fragments. I have been principal investigator along with a multidisciplinary group of co investigators on a number of NSF grants that have and are continuing to deal with a variety of projects: see www.lems.brown.edu/shape.
Search BANNER for courses taught by Professor Cooper this year.
Professor Cooper is a Principal Investigator in the SHAPE Lab., a multidisciplinary project supported by Brown and the NSF, involving the Divisions of Engineering and Applied Mathematics, and the Departments of Old World Art and Archaeology, and Visual Arts, and the Media Research Lab. at New York University.
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Last modified: Mar. 19, 2008.