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Light Detection and Ranging (LIDAR) Surface Feature Extraction Tool

Award Information

Agency:
Department of Defense 		Branch:
Navy 		Award ID:
74990 		Program Year/Program:
2006 / SBIR
Agency Tracking Number:
N043-245-0533 		Solicitation Year:
N/A 		Solicitation Topic Code:
N/A 		Solicitation Number:
N/A
Small Business Information
Visual Learning Systems, Inc.
1719 Dearborn Avenue Missoula, MT 59801-2391
View profile »
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No
 
Phase 2
Fiscal Year: 2006
Title: Light Detection and Ranging (LIDAR) Surface Feature Extraction Tool
Agency / Branch: DOD / NAVY
Contract: N61339-06-C-0055
Award Amount: $1,000,000.00
 

Abstract:

NAVAIR requires accurate and timely 3-D geospecific features, terrain, and imagery data to support Modeling and Simulation (M&S) software applications used in training and pre-mission rehearsal simulators. LIDAR data provides an excellent source for spatially accurate digital terrain and 3-D feature information; however, current visual database production techniques require hundreds of man-hours to extract and attribute features. Automated processes are necessary to achieve the Navy's goal of good M&S data that is efficiently processed and correctly formatted. Bottlenecks in producing good data are a result of manual processes used in (1) registering old features and imagery to newly acquired imagery and LIDAR, (2) extracting and editing complex 3-D geometries, and (3) updating and attributing features. The proposed Phase II workplan promises to significantly alleviate these bottlenecks by developing a system that exploits the information content of LIDAR and multiband imagery using machine learning-based feature extraction technology. The envisioned system will have the capability of automating the extraction of M&S features from LIDAR, registering features to images, allowing dynamic interaction with analysts, interrogating analysts when it needs additional information, and embedding the ability to create a continuously updated repository of feature extraction models.

Principal Investigator:

Stuart Blundell
COO
4068291384
sblundell@vls-inc.com

Business Contact:

David Opitz
CEO
4068291384
opitz@vls-inc.com
Small Business Information at Submission:

VISUAL LEARNING SYSTEMS, INC.
P.O. Box 8226 Missoula, MT 59807

EIN/Tax ID: 810529309
DUNS: N/A
Number of Employees:
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No