Automatic Extraction of Urban Features from Terrestrial LIDAR Systems

Award Information
Agency:
Department of Defense
Branch
Army
Amount:
$730,000.00
Award Year:
2006
Program:
SBIR
Phase:
Phase II
Contract:
W9132V-06-C-0020
Agency Tracking Number:
A052-121-2622
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
VISUAL LEARNING SYSTEMS, INC.
P.O. Box 8226, Missoula, MT, 59807
Hubzone Owned:
N
Socially and Economically Disadvantaged:
N
Woman Owned:
N
Duns:
150373442
Principal Investigator:
Stuart Blundell
COO
(406) 829-1384
sblundell@vls-inc.com
Business Contact:
David Opitz
President
(406) 829-1384
opitz@vls-inc.com
Research Institution:
n/a
Abstract
The U.S. Army requires automated feature extraction (AFE) software to collect 3D urban features from terrestrial LIDAR data in a timely and cost-effective manner to support the ground-based Warfighter operating in the urban battlespace. Vehicle-mounted terrestrial LIDAR systems have the capability to capture very-accurate 3D measurements of the urban environment with spatial resolutions on the order of 5 centimeters or less. The 3D imaging capability of these collection systems is negated, however, by a lack of commercial software tools capable of exploiting terrestrial LIDAR datasets with a high degree of automation. Current approaches for creating high-resolution 3D urban models are expensive, requiring thousands of man-hours to digitize feature geometries, assign textures to features, and then attribute features. Visual Learning Systems, Inc. has developed a unique capability to automatically extract 3D urban features from terrestrial LIDAR data including building facades, doors, windows, poles, trees, vehicles and other urban features of interest. The proposed Ground-Based 3D Urban Modeling Toolkit, designed as a plug-in for VLS' Feature Analyst and LIDAR Analyst software, provides the Army with a comprehensive and automated 3D feature extraction solution for urban environments.

* information listed above is at the time of submission.

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