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

Award Information
Agency: Department of Defense
Branch: Missile Defense Agency
Contract: HQ0006-05-C-7277
Agency Tracking Number: 05-0112T
Amount: $100,000.00
Phase: Phase I
Program: STTR
Awards Year: 2005
Solicitation Year: 2005
Solicitation Topic Code: MDA05-T008
Solicitation Number: N/A
Small Business Information
15400 Calhoun Drive, Suite 400, Rockville, MD, 20855
DUNS: 161911532
HUBZone Owned: N
Woman Owned: Y
Socially and Economically Disadvantaged: N
Principal Investigator
 Chi-Man Kwan
 Director of Research & Development
 (301) 294-5238
Business Contact
 Mark James
Title: Contract & Proposal Manager
Phone: (301) 294-5221
Research Institution
 Baoxin Li
 Depart of Computer Science , Ira A. Fulton School
Tempe, AZ, 85287
 (480) 965-3190
 Nonprofit college or university
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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