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                            Funding & Awards
 HandShot ID: A Fast 3-D Imaging System for Capturing Fingerprints, Palm Prints and Hand Geometry
Note:
              This awardee has received supplemental funding. This award detail page includes information about both the original award and supplemental awards.
Award Information
Awardee
              Carnegie Mellon University
Award #
              2005-IJ-CX-K046
Funding Category
              Competitive
Location
                    Pittsburgh, PA
Congressional District
              18
Status
              Closed
Funding First Awarded
              2004
Total funding (to date)
              $1,533,341
Original Solicitation
              FAST CAPTURE FINGERPRINT/PALM PRINT TECHNOLOGY
Description of original award (Fiscal Year 2004, $773,341)
Carnegie Mellon University seeks to develop their proposed Hand Shot system which will construct a visual 3-dimensional model of both hands, including palms, fingerprints, fingertips and sides of the fingers. The associated algorithms (1) stitch images from multiple cameras together, forming a complete 3-D model of both hands using active models to normalize for pose; (2) extract ridge detail based on contrast assessment under varying illumination effects, and (3) translate 3-D images to standardized formats. Hand Shot will be less error-prone, have high throughput and be an information-rich image acquisition system.

ca/ncf
Supplemental Award 1 (Fiscal Year 2007, $760,000)
This project will scientifically explore photographic contactless capture of fingerprints, palm prints, and hand geometry in order to achieve accurate capture at high resolution in 5 seconds. This effort will process and improve photographic capture sufficient to construct photograph-to-ink prints that match rolled ink prints of the same subjects in Automated Fingerprint Identification Systems (AFIS), allowing the development of an automated fingerprint imaging systems compatible with NIST standards and interoperable with the FBI's IAFIS system for use by local and other law enforcement agencies.
ca/ncf


  
Grant-Funded Publications
        
                      Face de-identification
                  Semi-supervised learning of multi-factor models for face de-identification
                  2D image database indexing: a coefficient-based approach
                  New directions in contact free hand recognition
                  Robust hand geometry measurements for person identification using active appearance models
                  Towards real-world face de-identification
                  Model-based face de-identification

  
Date Created: September 15, 2005
    
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