NSF LogoNSF Award Abstract - #0428249

ITR - (NHS) - (int) Multi-level, Active Attention Surveillance


NSF Org IIS
Latest Amendment Date September 28, 2004
Award Number 0428249
Award Instrument Standard Grant
Program Manager Sylvia J. Spengler
IIS Division of Information & Intelligent Systems
CSE Directorate for Computer & Information Science & Engineering
Start Date October 1, 2004
Expires September 30, 2007 (Estimated)
Awarded Amount to Date $1300000
Investigator(s) Richard Parent parent@cis.ohio-state.edu (Principal Investigator)
David Woods (Co-Principal Investigator)
Sponsor Ohio State University Research Foundation
1960 Kenny Road
Columbus, OH 43210 614/292-3732
NSF Program(s) ITR FOR NATIONAL PRIORITIES
Field Application(s) 0104000 Information Systems,
0104000 Information Systems
Program Reference Code(s)
Program Element Code(s) 7314

Abstract

ABSTRACT This proposal seeks to advance security surveillance monitoring by introducing event-based reasoning. The team will use a formal event-discovery protocol to uncover event categories and the temporal structure of events. This results in an event template hierarchy. The event template hierarchy is supported by the enabling technologies of smart sensors, a reconfigurable network, and the use of persistent models for tracking. The result is an autonomous sensor network that can be effectively coupled to human operators in order to allow top-down control of the resources as well as the ability to modify the models for event and background activities. While the methodology is suitable for a wide variety of application domains, the work is grounded in a campus security and surveillance paradigm. By integrating research from Cognitive Science, Geography, and Computer Science (Graphics, and Vision), the team can create a paradigmatic shift in the way that surveillance systems are viewed and developed. The data stream is no longer composed merely of video and perhaps some low-level alarms; the focus is now extended to include events. Data and information no longer move toward a usersitting in front of a wall of monitors. Event contexts, set by higher-level events as well as by operators-in-the-loop, direct and focus attention in order to detect differences from a dynamic model of background activity. The result is that the information is more meaningful, the surveillance systems more focused, and the cognitive skills of the operators more efficiently utilized. A prototype system will be made available for pertinent security personnel to train and test. The work will contribute to training methodologies of security personnel. Under the purview of broader impact, the proposed work strives to include under-represented and minority student groups through targeted training in the use of video technology. Finally if successful, event-based strategic surveillance networks can provide alternatives to racial profiling. The individuals are judged only by their actions as encoded in the event models.

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