NEURAL NET BASED PRIMING AND MODEL BASED ATR USING MOTION CUES

Award Information
Agency:
Department of Defense
Branch
Air Force
Amount:
$298,122.00
Award Year:
1994
Program:
SBIR
Phase:
Phase II
Contract:
n/a
Award Id:
18427
Agency Tracking Number:
18427
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
6811 Kneilworth Avenue, Suite, 306, Riverdale, MD, 20737
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
n/a
Principal Investigator:
Dr Srinevasan Raghaven
(301) 927-3223
Business Contact:
() -
Research Institute:
n/a
Abstract
Object-oriented methodologies such as model-based vision provide a robust and more intelligent solution to the ATR problem. Because these methodologies exploit a priori knowledge of a limited number of target models, while allowing the targets to be oriented towards the viewer in any arbitrary fashion, they result in a powerful ATR system. The central focus of this proposal is on building an automatic target recognition system for identifying mobile targets using an object-image alignment approach. Using this approach, we propose to develop a two stage recognition algorithm. The first stage of this algorithm makes use of the three-point object-image correspondence theorim of Huttenlocher and Ullman (1990) to narrow the search for constrained matching of object-image pairs. The second stage of the algorithm uses the mean-field annealing techique to compute the object-image transformation parameters from multiple matches by minimizing a least-squares measure. For segmentation of the target from its background, we employ a motion-based segmentation algorithm developed earlier by LNK.

* information listed above is at the time of submission.

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