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Adaptive-Tangent Space Representation for Image Retrieval Based on Kansei

  • Myunggwon Hwang
  • Sunkyoung Baek
  • Hyunjang Kong
  • Juhyun Shin
  • Wonpil Kim
  • Soohyung Kim
  • Pankoo Kim
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4293)

Abstract

From the engineering aspect, the research on Kansei information is a field aimed at processing and understanding how human intelligence processes subjective information or ambiguous sensibility and how such information can be executed by a computer. Our study presents a method of image processing aimed at accurate image retrieval based on human Kansei. We created the Kansei-Vocabulary Scale by associating Kansei of high-level information with shapes among low-level features of an image and constructed the object retrieval system using Kansei-Vocabulary Scale. In the experimental process, we put forward an adaptive method of measuring similarity that is appropriate for Kansei-based image retrieval. We call it “adaptive-Tangent Space Representation (adaptive-TSR)”. The method is based on the improvement of the TSR in 2-dimensional space for Kansei-based retrieval. We then it define an adaptive similarity algorithm and apply to the Kansei-based image retrieval. As a result, we could get more promising results than the existing method in terms of human Kansei.

Keywords

Retrieval System Image Retrieval Shape Match Image Retrieval System Ontological Description 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Myunggwon Hwang
    • 1
  • Sunkyoung Baek
    • 1
  • Hyunjang Kong
    • 1
  • Juhyun Shin
    • 1
  • Wonpil Kim
    • 2
  • Soohyung Kim
    • 2
  • Pankoo Kim
    • 1
  1. 1.Dept. of Computer EngineeringChosun UniversityGwangjuKorea
  2. 2.Dept. of Computer ScienceChonnam National UniversityGwangjuKorea

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