A System Theoretic Approach to Robust Detection Of Potential Threats from Video
This research aims at a substantial enhancement of the ability to conduct autonomous, video based, persistent intelligent surveillance, and reconnaissance and threat assessment in highly uncertain, adversarial scenarios such as urban environments. The main idea is the use of operator theoretic and convex analysis methods to recast several key sub-problems arising in this context -tracking, dynamic appearance, and activity recognition -into a finite dimensional convex optimization that can be efficiently solved.
Video-based surveillance methods have enormous potential for providing advance warning of terrorist activities and threats.- Octavia Camps, Project Leader
Faculty and Staff Currently Involved in Project
Students Currently Involved in Project
- Caglayan Dicle
- Oliver Lehmann
- Binlong Li