SBIR/STTR Research Award

Multi-Hypothesis Automated Wireframe Generation

Award identifier 4961b7d2af287fabe75c363e1281a9b60f05b39507b9845040f060aea4817da8Awarding agency Department of Defense · Air Force

Award amount

$99,662

Program and phase

SBIR · Phase I

Award year

2002

Explore This Research Award in CaptureIQ

Research the technology, evaluate the recipient and agency, identify related opportunities, and explore potential follow-on work with CaptureIQ.

Award details

Awarding agency
Department of Defense
Branch
Air Force
Recipient company
ALPHATECH, INC.
Proposal award date
Not reported
Contract end date
Not reported
UEI
KM4XFJ7CJSY8
Solicitation number
Not reported
Topic code
Not reported

Research abstract

"Accurate targeting using standoff missiles, such as JASSM, requires automatic target correlation algorithms using significant target features. Wireframe models that describe the significant edges and corners of fixed targets are well suited for this task.Great advances in wireframe construction from stereoscopic imagery have been achieved through the last twenty years of research in computer vision, but significant limitations still exist. Current model construction procedures are human-intensive and timeconsuming. Existing automated systems create too many spurious objects and incorrect hypotheses that lead to incorrect scene surface topologies, caused by physical phenomena such as surface reflectance, ambient lighting, shadows and occlusions generatedby complex scenes. We will make automated wireframe model algorithms truly useful for mission planning platforms by rigorously applying physical and probabilistic models to a wider set of image features. First, we will use a rigorous mathematical treatment of uncertaintiesto better characterize the data and avoid sensitive heuristics. Second, we will develop new probabilistic, phenomenologically motivated cueing algorithms to distinguish false alarms from targets. Finally, we will enhance algorithms to consider multipletarget hypotheses, with a model-based predict and match algorithm to robustly choose among competing hypotheses using predictions of edge, area, and texture

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Research funding history

217 SBIR/STTR records share this UEI (1983–2009). Reported award amounts total $62,908,538. Reported amounts are not federal obligations.

Phases: Phase I, Phase II

Agencies: Department of Defense, National Science Foundation, Department of Health and Human Services

Agency intelligence

Department of Defense

Back to SBIR/STTR Research Awards

Don't take our word for it. Ask AI about RFPCapture.

See what leading AI assistants have to say about RFPCapture and CaptureIQ.

Gemini opens without a prefilled question. The question is copied to your clipboard when the button works. You can also copy it here:

What is RFPCapture.com and its CaptureIQ platform from Smart Logic AI? How does it help federal contractors discover opportunities, evaluate bid/no-bid decisions, research government contracts, and prepare proposals? How does it compare with other federal capture platforms? Use independent sources where available.