Approach to Enhancing Target Discrimination via 3D Visualization without 3D Glasses

Award Information
Agency:
Department of Defense
Branch
Missile Defense Agency
Amount:
$100,000.00
Award Year:
2005
Program:
STTR
Phase:
Phase I
Contract:
HQ0006-05-C-7277
Award Id:
74792
Agency Tracking Number:
05-0112T
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
15400 Calhoun Drive, Suite 400, Rockville, MD, 20855
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
161911532
Principal Investigator:
Chi-manKwan
Director of Research & Development
(301) 294-5238
ckwan@i-a-i.com
Business Contact:
MarkJames
Contract & Proposal Manager
(301) 294-5221
mjames@i-a-i.com
Research Institute:
ARIZONA STATE UNIV.
Baoxin Li
Depart of Computer Science , Ira A. Fulton School
Tempe, AZ, 85287
(480) 965-3190
Nonprofit college or university
Abstract
There are many factors that render automatic target recognition challenging. These include cluttered background, adverse weather and acquisition conditions, spatially closed targets, spectrally-matched decoys, and the limits on sensor resolution etc. One solution is to have a 3D display, which will help discriminate the targets. However, a major challenge in rectifying the sensor streams, i.e. to relate one image to the other on a pixel-by-pixel basis, is that the sensors are not calibrated, thus simply using standard stereoscopic vision algorithms will not generate accurate stereo images. Here we propose an algorithm for stereo image creation in real-time, and has very high accuracy due to the use of state-of-the-art algorithms developed recently by this team. The first step is that we apply Gabor filter to systematically select pixel points as features. This feature correspondence and tracking algorithm will minimize the impact of errors caused by uncalibrated cameras and cluttered background. Then an efficient algorithm for tracking the feature points in the subsequent frames is used. Thus potentially we can have a real-time algorithm that can run with stringent constraint of computational resources. Finally, we have an efficient algorithm to create a stereo image.

* information listed above is at the time of submission.

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