NSF Org:	CNS Division Of Computer and Network Systems
Recipient:	GEORGIA TECH RESEARCH CORP
Initial Amendment Date:	September 15, 1998
Latest Amendment Date:	October 10, 2002
Award Number:	9806822
Award Instrument:	Standard Grant
Program Manager:	Gregory R. Andrews CNS  Division Of Computer and Network Systems CSE  Directorate for Computer and Information Science and Engineering
Start Date:	September 1, 1998
End Date:	August 31, 2003 (Estimated)
Total Intended Award Amount:	$861,216.00
Total Awarded Amount to Date:	$861,216.00
Funds Obligated to Date:	FY 1998 = $861,216.00
History of Investigator:	Irfan Essa (Principal Investigator) irfan@cc.gatech.edu Christopher Atkeson (Co-Principal Investigator) Umakishore Ramachandran (Co-Principal Investigator) Gregory Abowd (Co-Principal Investigator)
Recipient Sponsored Research Office:	Georgia Tech Research Corporation 926 DALNEY ST NW ATLANTA GA  US  30318-6395 (404)894-4819
Sponsor Congressional District:	05
Primary Place of Performance:	Georgia Tech Research Corporation 926 DALNEY ST NW ATLANTA GA  US  30318-6395
Primary Place of Performance Congressional District:	05
Unique Entity Identifier (UEI):	EMW9FC8J3HN4
Parent UEI:	EMW9FC8J3HN4
NSF Program(s):	EXPERIMENTAL SYSTEMS/CADRE, DIGITAL SOCIETY&TECHNOLOGIES
Primary Program Source:	app-0198
Program Reference Code(s):	2861, 8888, 9179, 9218, HPCC, SMET
Program Element Code(s):	472500, 685000
Award Agency Code:	4900
Fund Agency Code:	4900
Assistance Listing Number(s):	47.070

ABSTRACT

9806822 Essa, Irfan A. Abowd, Gregory D. Georgia Institute of Technology Experimental Software Systems: Automated Understanding of Captured Experience The objective of this research is to reduce substantially the human input necessary for creating and accessing large collections of multimedia, particularly multimedia created by capturing what is happening in an environment. The existing software system which is being used as the starting point for this investigation is Classroom 2000, a system designed to capture what happens in classrooms, meetings, and offices. Classroom 2000 integrates and synchronizes multiple streams of captured text, images, handwritten annotations, audio, and video. In a sense, it automates note-taking for a lecture or meeting. The research challenge is to make sense of this flood of captured data. The project explores how the output of Classroom 2000 can be automatically structured, segmented, indexed, and linked. Machine learning and statistical approaches to language are used to attempt to understand the captured data. Techniques from computational perception are used to try to find structure in the captured data. An important component of this research is the experimental analysis of the software system being built. The expectation is that this research will have a dramatic impact on how humans work and learn, as technology aids humans by capturing and making accessible what happens in an environment.

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