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Automatic Extraction of Urban Features from Terrestrial LIDAR Systems

Award Information
Agency: Department of Defense
Branch: Army
Contract: W9132V-06-C-0020
Agency Tracking Number: A052-121-2622
Amount: $730,000.00
Phase: Phase II
Program: SBIR
Solicitation Topic Code: A05-121
Solicitation Number: 2005.2
Solicitation Year: 2005
Award Year: 2006
Award Start Date (Proposal Award Date): 2006-08-24
Award End Date (Contract End Date): 2008-08-24
Small Business Information
P.O. Box 8226
Missoula, MT 59807
United States
DUNS: 150373442
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Stuart Blundell
 (406) 829-1384
Business Contact
 David Opitz
Title: President
Phone: (406) 829-1384
Research Institution

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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