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A New Visual Comfort-Based Stereoscopic Image Retargeting Method

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Advances in Visual Computing (ISVC 2013)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 8033))

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Abstract

In this paper, we present a novel stereoscopic image retargeting method of reducing both visual discomfort and the geometric distortion of objects in an image. Given a specific target display size, our method adaptively deforms the input stereoscopic image using color and disparity contrast based on a saliency analysis method. The deformation is defined and performed by solving an energy minimization problem. We propose an energy function combining geometric distortion and alignment consistency. We also consider excess disparity and misalignment to reduce visual discomfort of the resized stereoscopic image. To validate our stereoscopic image retargeting method for addressing visual comfort, we perform a user study. Experimental results show that our method is efficient and offers more user-friendly retargeting results than previously proposed methods.

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Author information

Authors and Affiliations

  1. Dept. of Computer Engineering, The Catholic University of Korea, #43-1 Yeokgok 2-dong, Wonmi-Gu, Bucheon, Gyeonggi-do, Korea

    Sang-Hyun Cho

  2. Dept. of Digital Media, The Catholic University of Korea, #43-1 Yeokgok 2-dong, Wonmi-Gu, Bucheon, Gyeonggi-do, Korea

    Hang-Bong Kang

Authors
  1. Sang-Hyun Cho
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  2. Hang-Bong Kang
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Editor information

Editors and Affiliations

  1. University of Nevada, Reno, NV, USA

    George Bebis

  2. NASA Ames Research Center, Moffett Field, CA, USA

    Richard Boyle

  3. Lawrence Berkeley National Laboratory, Berkeley, CA, USA

    Bahram Parvin

  4. Desert Research Institute, Reno, NV, USA

    Darko Koracin

  5. Arizona State University, Tempe, AZ, USA

    Baoxin Li

  6. Mitsubishi Electric Research Laboratories, Cambridge, MA, USA

    Fatih Porikli

  7. University of California, Riverside, CA, USA

    Victor Zordan

  8. AT&T Research Labs, Florham Park, NJ, USA

    James Klosowski

  9. ZIRST, Saint-Ismier Cedex, France

    Sabine Coquillart

  10. Qualcomm Research, San Diego, CA, USA

    Xun Luo

  11. Oxford e-Research Centre, University of Oxford, Oxford, UK

    Min Chen

  12. IBM, Hawthorne, NY, USA

    David Gotz

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© 2013 Springer-Verlag Berlin Heidelberg

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Cho, SH., Kang, HB. (2013). A New Visual Comfort-Based Stereoscopic Image Retargeting Method. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2013. Lecture Notes in Computer Science, vol 8033. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41914-0_29

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  • DOI: https://doi.org/10.1007/978-3-642-41914-0_29

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-41913-3

  • Online ISBN: 978-3-642-41914-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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