🚀 go-pugleaf

University of Colorado at Boulder
Department of Computer Science
ECOT 717 Engineering Center
Campus Box 430
Boulder, Colorado 803090430
(303) 4927514, FAX: (303) 4922844

CS COLLOQUIUM
Mining Large Image Collections
Michael Burl
NASA Jet Propulsion Laboratory
April 23, 2001
3:00  3:50 PM
Engineering Center Classroom 245

Refreshments will be served afterwards in ECOT 831

Improvements in acquisition and storage technology have led to an explosion 
in the number and size of image collections in a variety of fields from 
medical imaging to the petroleum industry to digital libraries and the 
Internet to space exploration. Within these datasets there is a potential 
wealth of information; however, transforming from the raw data (perhaps 
millions of images each containing millions of pixels) to a higher-level 
understanding of the content of an image collection is a difficult task 
both due to the size of the datasets and the difficulty of automatically 
interpreting image data.  Recent attempts to approach the problem using a 
distributed set of human labelers [ClickWorkers] are interesting, but 
ultimately do not provide a long-term, reusable solution. In contrast, 
maturing technologies in data mining, computer vision, and machine 
learning, coupled with rapidly improving and affordable parallel and 
distributed hardware, have the potential to solve current and future image 
mining problems in an efficient, scalable way.

In this talk, we will provide an overview of our work toward systems and 
algorithms that can extract semantically meaningful content from data, with 
emphasis on specific algorithms that have been developed for visual 
recognition, querying, and discovery. We will also describe an exciting new 
project, the Autonomous Sciencecraft Constellation (ASC), that involves 
integrating perception, planning, and execution capabilities to create a 
highly capable spacecraft constellation that can make onboard decisions and 
carry out actions based on the content of the data collected.

Host:  Mike Mozer
------------------------------
http://www.cs.colorado.edu/department/events/colloquia/colloquia.html

Sign Language Interpreters Available Upon Request.  Please contact Jane 
Obrecht, Department of
Computer Science, Engineering  ECOT 722, 303-492-6101, at least five days 
prior to the colloquium.

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