Cartoon Character Recognition Using Concentric Multi-Region Histograms of Oriented Gradients

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Abstract

Comic books are a kind of serial narrative artwork made up of comic pages. As an essential part of comics, cartoon characters appear throughout the whole series. Therefore, the recognition of cartoon characters is useful for many applications of comics. Normally, images of the same character are similar but with different representations in different scenes, such as facial expressions, poses, and viewpoints, which make them difficult to be recognized. In contrast to human being, besides face regions, there are many other parts offering the identification features for cartoon characters. In this paper, we focus on cartoon character recognition and propose Concentric Multi-Region model to explore the significant features from the parts around face regions. Histograms of Oriented Gradients (HOG) is utilized for the description of regions, and the AdaBoost algorithm is applied to obtain a new descriptor named Concentric Multi-Region Histograms of Oriented Gradients (CMR-HOG). In the experiments, 17 labeled cartoon characters are applied. Compared to other face and object recognition methods only based on face regions, the proposed method shows better performance. In addition, we proved its scalability for cartoon character recognition.

Journal

  • IEEJ Transactions on Electronics, Information and Systems

    IEEJ Transactions on Electronics, Information and Systems 132(11), 1847-1854, 2012-11-01

    The Institute of Electrical Engineers of Japan

References:  22

Codes

  • NII Article ID (NAID)
    10031120135
  • NII NACSIS-CAT ID (NCID)
    AN10065950
  • Text Lang
    ENG
  • Article Type
    ART
  • ISSN
    03854221
  • NDL Article ID
    024080345
  • NDL Call No.
    Z16-795
  • Data Source
    CJP  NDL  J-STAGE 
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