Robust Dynamic Vision Methods for Persistent Surveillance and Enhanced Vehicle Autonomy
Abstract
This research addressed the USAF s unprecedented proactive persistent surveillance Long Term Challenge. Specifically, we aimed at a substantial enhancement of the ability to conduct autonomous, video based, persistent intelligent surveillance, reconnaissance and threat assessment in highly uncertain, adversarial scenarios such as urban environments. At its core was a novel approach, stressing dynamic models as key enablers for finding, tracking and anticipating/assessing behavior of multiple targets using as inputs data streams from spatially distributed sensors. It included both theory developments in an emerging new field dynamics based extraction of information sparsely encoded in high dimensional data and an investigation of implementation issues.
Document Details
- Document Type
- Technical Report
- Publication Date
- Feb 28, 2012
- Accession Number
- ADA565336
Entities
People
- Mario Sznaier
- Octavia Camps
Organizations
- Northeastern University