• DocumentCode
    595201
  • Title

    Sketch-based face alignment for thermal face recognition

  • Author

    Lin Sun ; Dai, X.X.

  • Author_Institution
    Dept. of Comput. Sci., Zhejiang Univ. City Coll., Hangzhou, China
  • fYear
    2012
  • fDate
    11-15 Nov. 2012
  • Firstpage
    2347
  • Lastpage
    2350
  • Abstract
    In this paper, we present a novel face alignment approach in thermal infrared face recognition. The alignment procedure is based on closest point set matching between sketch faces. Linear combination of positional and local pattern features is embedded in the pointwise distance to solve the local minimum problem for ICP due to edge noise in sketch faces. The comprehensive experiments, including intra-class, inter-class and variable expressions, show the alignment accuracy and face recognition performance results of our algorithm compared to manual labelling, ICP and congealing methods.
  • Keywords
    emotion recognition; face recognition; feature extraction; image matching; infrared imaging; set theory; ICP; closest point set matching; interclass expressions; intraclass expressions; local minimum problem; local pattern features; pointwise distance; positional pattern features; sketch-based face alignment; thermal infrared face recognition; variable expressions; Face; Face recognition; Histograms; Image edge detection; Iterative closest point algorithm; Labeling; Manuals;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition (ICPR), 2012 21st International Conference on
  • Conference_Location
    Tsukuba
  • ISSN
    1051-4651
  • Print_ISBN
    978-1-4673-2216-4
  • Type

    conf

  • Filename
    6460636