“Automatic Image Retargeting” by Setlur, Takagi, Raskar, Gleicher and Gooch

  • ©Vidya Setlur, Saeko Takagi, Ramesh Raskar, Michael Gleicher, and Bruce Gooch

  • ©Vidya Setlur, Saeko Takagi, Ramesh Raskar, Michael Gleicher, and Bruce Gooch

  • ©Vidya Setlur, Saeko Takagi, Ramesh Raskar, Michael Gleicher, and Bruce Gooch

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Title:

    Automatic Image Retargeting

Session/Category Title:   Artistic Depiction


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Abstract:


    We introduce a non-photorealistic algorithm for automatically retargeting images, that is, adapting them for display at different sizes and/or aspect ratios, while preserving the images’ important features and qualities. Our method accommodates images with multiple important regions by minimizing the unimportant space be- tween regions. The motivation for this work is the need for tools that allow us to author imagery once, and then automatically retarget that imagery for a variety of different display devices.

References:


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    Harrison, P. 2001. A non-hierarchical procedure for re-synthesis of complex textures. In Proceedings of WSCG 2001, 190–197.
    Itti, L., Koch, C., and Niebur, E. 1998. A model of saliencybased visual attention for rapid scene analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence 20, 11, 1254–1259.
    Robotics Institute, C. M. U. Face detection demonstration. http://www.vasc.ri.cmu.edu/cgi-bin/demos/findface.cgi.
    Suh, B., Ling, H., Bederson, B. B., and Jacobs, D. W. 2003. Automatic thumbnail cropping and its effectiveness. In Proceedings of UIST 2003, ACM, 11–99.


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