• DocumentCode
    2815611
  • Title

    Face sketch-photo synthesis based on support vector regression

  • Author

    Zhang, Jiewei ; Wang, Nannan ; Gao, Xinbo ; Tao, Dacheng ; Li, Xuelong

  • Author_Institution
    Sch. of Electron. Eng., Xidian Univ., Xi´´an, China
  • fYear
    2011
  • fDate
    11-14 Sept. 2011
  • Firstpage
    1125
  • Lastpage
    1128
  • Abstract
    The existing face sketch-photo synthesis methods trend to lose some vital details more or less. In this paper, we propose a novel sketch-photo synthesis approach based on support vector regression (SVR) to handle this difficulty. First, we utilize an existing method to acquire the initial estimate of the synthesized image. Then, the final synthesized image is obtained by combining the initial estimate and the SVR based high frequency information together to further enhance the quality of synthesized image. Experimental results on the benchmark database and our new constructed database demonstrate that the proposed method can achieve significant improvement on perceptual quality. Moreover, the synthesized face images can obtain higher recognition rate when used in retrieval system.
  • Keywords
    face recognition; image enhancement; image retrieval; regression analysis; rendering (computer graphics); support vector machines; automatic face retrieval systems; face sketch-photo synthesis methods; high frequency information; perceptual quality improvement; support vector regression; synthesized image estimation; synthesized image quality enhancement; Databases; Face; Face recognition; Hidden Markov models; Image processing; Support vector machines; Training; Face sketch-photo synthesis; high-frequency information; support vector regression;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing (ICIP), 2011 18th IEEE International Conference on
  • Conference_Location
    Brussels
  • ISSN
    1522-4880
  • Print_ISBN
    978-1-4577-1304-0
  • Electronic_ISBN
    1522-4880
  • Type

    conf

  • DOI
    10.1109/ICIP.2011.6115625
  • Filename
    6115625