Remote Identification and Tracking of Non-Cooperative Subjects (REMIT-NCS)

Award Information
Agency:
Department of Homeland Security
Branch:
N/A
Amount:
$99,973.78
Award Year:
2012
Program:
SBIR
Phase:
Phase I
Contract:
HSHQDC-12-C-00024
Agency Tracking Number:
DHS SBIR-2012.1-H-SB012.1-005 -0006-I
Solicitation Year:
2012
Solicitation Topic Code:
H-SB012.1-005
Solicitation Number:
DHS SBIR-2012.1
Small Business Information
Charles River Analytics Inc.
625 Mount Auburn Street, Cambridge, MA, 02138-4555
Hubzone Owned:
N
Socially and Economically Disadvantaged:
N
Woman Owned:
N
Duns:
115243701
Principal Investigator
 Camille Monnier
 (617) 491-3474
 cmonnier@cra.com
Business Contact
 Mark Felix
Title: Contracts Manager
Phone: (617) 491-3474
Email: mfelix@cra.com
Research Institution
N/A
Abstract
The ability to reliably track and recognize individuals inside a security perimeter is a critical component of next-generation distributed security systems. While state-of-the-art surveillance systems can reliably track pedestrians in sparse, static environments with minor occlusions and few moving subjects, performance degrades rapidly as scene complexity and population density increase. The problem becomes even more difficult when tracking individuals over long time scales, or across cameras with non-overlapping fields of view, a scenario which is unavoidable in most urban environments. Existing systems are also unable to re-acquire individuals who have been previously tracked in a separate location, but for whom recent track data is unavailable. To address these issues, we propose a system for Remote Identification and Tracking of Non-Cooperative Subjects (REMIT-NCS). REMIT-NCS extracts stable, descriptive bio-signatures from tracked individuals in remote imagery by reconstructing the anthropometric parameters (shape and pose) of a tracked individual and using them to produce higher-order, viewpoint-insensitive descriptions of a specific individual's dynamics. The combined descriptions of a tracked pedestrian's static and dynamic attributes are then compared to a database of similarly generated tracks to identify the features most suitable for supporting long-term tracking and re-acquisition.

* information listed above is at the time of submission.

Agency Micro-sites

US Flag An Official Website of the United States Government