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Image Colorization with an Affective Word

  • Xiaohui Wang
  • Jia Jia
  • Hanyu Liao
  • Lianhong Cai
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7633)

Abstract

An important role of image color is the conveyer of emotions (through color themes). The colorization is less useful with an undesired color theme, even semantically correct, which has been rarely considered previously. In this paper, we propose a complete system for the image colorization with an affective word. We only need users to assist object segmentation along with text labels and give an affective word. First, the text labels along with other object characters are jointly used to filter the internet images to give each object a set of semantically correct reference images. Second, we select a set of color themes according to the affective word based on art theories. With these themes, a generic algorithm is adopted to select the best reference for each object. Finally, we propose a hybrid texture synthesis approach to colorize each object. Our experiments show that the results of our system have both the correct semantics and the desired emotions.

Keywords

Image colorization affective word color theme 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Xiaohui Wang
    • 1
  • Jia Jia
    • 1
  • Hanyu Liao
    • 1
  • Lianhong Cai
    • 1
  1. 1.Key Laboratory of Pervasive Computing, Ministry of Education, Tsinghua National Laboratory for Information Science and Technology (TNList), Department of Computer Science and TechnologyTsinghua UniversityChina

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