Opportunistic Sensing for Object and Activity Recognition from Multi-Modal, Multi-Platform Data

Security applications, including homeland security and sousveillance applications, suffer from the problem of data deluge. It's easy to record data; it's very hard to find anybody who actually has the time to see or hear all of the data. The goal of this research is to develop systems that can automatically reconfigure themselves as necessary to track potentially interesting people, things, or events.

This project is funded by ARO MURI 31, 2009-2014, and is a collaboration among researchers from Rice University, the University of Maryland, the University of Illinois, Duke, UCLA, and Yale. Many of our publications have been written in collaboration with the US Army Research Labs. For more information, consult the menus at the top of this page, or follow any of these links: