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                            Library & Multimedia
 Using multi-instance enrollment to improve performance of 3D face recognition
NCJ Number
              304486

Author(s)
          Timothy C. Faltemier;
                        Kevin W. Bowyer;
                        Patrick J. Flynn
Date Published

November 2008
Length
              12 pages
Annotation
              This study explored the use of multi-instance enrollment as a means to improve the performance of 3D face recognition.
Abstract
              Experiments were performed using the ND-2006 3D face data set, which contains 13,450 scans of 888 subjects. This is the largest 3D face data set currently available and contains a substantial amount of varied facial expression. Results indicate that the multi-instance enrollment approach outperforms a state-of-the-art component-based recognition approach, in which the face to be recognized is considered as an independent set of regions. (Publisher Abstract)
      
  
          Additional Details
Grant Number(s)
        2005-DD-CX-K078


  
  
        
  Agencies
        NIJ-Sponsored


  
  
        
  Publication Type
        Research (Applied/Empirical)


  
  
        
  Award
        Center for Advanced Biometric Research and Evaluation
    
  
  
Date Published: November 1, 2008
    
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