Automated Swimmer Recongition Algorithms for the HarborGuard Intrusion Detection System

Award Information
Agency:
Department of Defense
Branch
Navy
Amount:
$599,942.00
Award Year:
2007
Program:
SBIR
Phase:
Phase II
Contract:
N00030-07-C-0045
Award Id:
74974
Agency Tracking Number:
N043-228-0546
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
1410 Sachem Place, Suite 202, Charlottesville, VA, 22901
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
120839477
Principal Investigator:
Jason Burkholder
Sr. Research Scinetist
(434) 973-1215
burkholder@bainet.com
Business Contact:
David Ward
President
(434) 973-1215
barron@bainet.com
Research Institution:
n/a
Abstract
The remote identification of surfaced swimmers in a harbor environment is a critical requirement for a comprehensive waterside security system. This requirement can be clearly divided into detection and classification objectives. Detection in this context means identifying the presence of a target on the surface of the water. Classification means discriminating between different types of targets - specifically, discriminating between swimmers on the surface and non-swimmer targets. In Phase I, Barron Associates, Inc. collaborated with L-3 Communications Klein Associates to develop highly-effective baseline automatic swimmer recognition (ASR) algorithms. The baseline ASR algorithms were demonstrated using a diverse set of radar data that included images of swimmers and other small targets, such as birds, buoys, and floats. Barron Associates extracted features from the radar images and classification algorithms to identify swimmers. The ASR algorithm achieved perfect classification of the radar targets in closed-set tests and, importantly, achieved excellent classification performance in open-set tests. The objectives of this Phase II SBIR effort are to: (1) implement the algorithms and supporting software for online, near real-time operation; (2) evaluate the algorithms in adverse environmental conditions; and (3)enhance the algorithms to incorporate additional sensor data, such as multiple radars, video/thermal images, and sonar signals.

* information listed above is at the time of submission.

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