SBIR/STTR Research Award

SBIR Phase I: Realtime Markerless Scene Tracking on a Smartphone

Award identifier 202e908d51de8857b3f7c52f6eeffa0e8089177bf9fa0ad97ee9bcdb777e1b74Awarding agency National Science Foundation

Award amount

$149,800

Program and phase

SBIR · Phase I

Award year

2010

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
National Science Foundation
Branch
Not reported
Recipient company
MoveableCode
Proposal award date
Not reported
Contract end date
Not reported
UEI
Not reported
Solicitation number
NSF 09-541
Topic code
IC

Research abstract

This Small Business Innovation Research (SBIR) Phase I project will determine the feasibility of robust, markerless, real-time tracking of a scene on a Smartphone for use in Mixed Reality (MR) applications. The problem to be solved is the expense and complexity of MR systems, thereby enabling the mass market adoption of MR applications. Existing high-end MR solutions require specialized equipment and custom hardware. Such equipment is expensive and not widely available. Existing Smartphone MR applications are inexpensive, but rely on fiduciary markers or known targets from which a Natural Feature Tracking training data set has previously been created. This imposes significant constraints on the deployment of MR applications: the location must be prepared in advance; or the consumer must change their behavior i.e. they must obtain a printed marker and bring it with them whenever they intend to use the MR application. The proposed innovation eliminates these challenges by using commodity hardware (a Smartphone) and markerless tracking. It enables solutions that are affordable, flexible and ideal for broad market adoption. High-end MR solutions are expensive and competing Smartphone offerings rely on the use of markers or pre-trained data sets. These restrictions present a clear barrier to mass market adoption. The proposed approach eliminates these obstacles, enabling broad adoption of MR applications. There is significant potential for commercialization of the innovation as a component of an MR application.

Technology keywords

Not reported

Agency intelligence

National Science Foundation

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.