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                            Library & Multimedia
 Optimal gradient pursuit for face alignment
NCJ Number
              305611

Author(s)
          Xiaoming Liu
Date Published

2011
Length
              7 pages
Annotation
              This paper proposes a new face model named “Optimal Gradient Pursuit Model”, where the objective is to minimize the angle between the gradient direction and the vector pointing toward the ground-truth shape parameter.
Abstract
              Face alignment aims to fit a deformable landmark-based mesh to a facial image so that all facial features can be located accurately. In discriminative face alignment, an alignment score function, which is treated as the appearance model, is learned such that moving along its gradient direction can improve the alignment. The authors formulate an iterative approach to solve this minimization problem. With extensive experiments in generic face alignment, the authors show that their model improves the alignment accuracy and speed compared to the state-of-the-art discriminative face alignment approach. (Publisher abstract provided)
      
  
          Additional Details
Grant Number(s)
        2007-DE-BX-K191


  
  
        
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        NIJ-Sponsored


  
  
        
  Award
        Site-Adaptive Face Recognition at a Distance
    
  
  
Date Published: January 1, 2011
    
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        Pursuit



  
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