Topic Information Award/Contract Number Proposal Information Company Performance

Safe Standoff Detection of Bulk Explosives on a Person

HSHQDC-13-C-00025 DHS SBIR-2012.1-H-SB012.1-003-0015-II
(DHS SBIR-2012.1 Phase II)
Portable Imager for Stand-off Detection of Person-Bourne Bulk Military and Homemade Explosives

Polestar Technologies, Inc.
220 Reservoir Street
Suite 3
Needham Heights, MA 02494-3133


Title: Portable Imager for Stand-off Detection of Person-borne Bulk Military and Homemade Explosives. The overall goal of this SBIR proposal is to develop a portable system for stand-off detection of concealed explosives. The system will produce images positively identifying the presence of explosives and have the ability to detect and identify different types of military explosives (like TNT, C-4, PETN) and homemade explosives such as TATP and HMTD. The system will process persons entering a federal building from a stand-off distance of 3-5m at a data collection rate sufficient to image moving subjects. The system's power and weight will allow it to be portable so that it can be deployed at any required location inside or outside the building. The proposed imager could be deployed at mass transit locations, national security event checkpoints, controlled-entry checkpoints at the entrance to buildings of national importance or at entrance to largely attended sports and entertainment venues.

Capability for the Tracking of Any and Every Person within a Security Perimeter

HSHQDC-13-C-00072 DHS SBIR-2012.1-H-SB012.1-005 -0006-II
(DHS SBIR-2012.1 Phase II)
Remote Identification and Tracking of Non-Cooperative Subjects (REMIT-NCS)

Charles River Analytics Inc.
625 Mount Auburn Street
Cambridge, MA 02138-4555


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 crowd 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 signatures from tracked individuals in surveillance imagery by reconstructing a tracked individual's anthropometric parameters (shape and pose) and using these to produce higher-order, viewpoint-insensitive signatures from the individual's intrinsic attributes (e.g., physical build and motion characteristics) and extrinsic attributes (i.e., outward appearance). The combined intrinsic and extrinsic signatures are then compared to a database of similarly processed tracks to identify the features most suitable for supporting long-term tracking and re-acquisition. Persons moving from one camera view to another are then re-acquired by the system via the resulting discriminative models, enabling persistent tracking of individuals throughout the facility.