Motivation
Public Safety
University of Maryland Security Operations Center (SOC), a division of the campus's Public Safety maintains a CCTV network of over 500 cameras. The SOC actively monitors over 350 cameras throughout the day to enhance campus security and gain reliable information about particular incidents occuring on campus.
Camera networks are expensive and in this tight economy, public funding is limited. Public Safety is looking for scalable, cost effective ways to increase security while increasing force efficiency. One instance is selecting and focusing cameras in response to an incident or alert.
Currently, SOC responds to incidents by manually selecting and focusing of relevant cameras. This approach does not scale well as each operator can only manipulate a single camera at a time. An automated mechanism for focusing cameras would scale better as it:
- focuses sets of cameras in parallel;
- allocates relevant resources;
- can recall cameras that are not actively monitored, but may have a relevant perspective;
- can handle dynamic networks, such as mobile/portable cameras;
- allows operators to spend more time analyzing the incident from more perspectives;