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Very fast generation of content-preserved photo collage under canvas size constraint

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Abstract

Photo collage, which constructs a compact and visually appealing representation from a collection of input images, can offer a most convenient and impressive user experience. Most previous approaches to collage construction have utilized saliency detection and visibility optimization. However, such methods are computationally expensive and not feasible for real-time applications such as online image retrieval or interactive photo browsing. Moreover, the effectiveness of automatic saliency detection may be questionable. Even if the main regions of interest are retained accurately, some visually not salient but semantically important items such as logos, captions, and copyright information located at the margins and corners may be missed. In our alternative approach, we address the issue of content-preserved collage, which avoids content-harmful processes such as cropping or changes to aspect ratio and orientation. Based on a full balanced binary layout tree, our algorithm can pack all the input images tightly onto the collage canvas while keeping their visual information unchanged. The proposed algorithm is fast, requiring less than 0.5 ms to generate a 100-image collage. We also present several extensions and applications oriented to a variety of usage contexts and device platforms.

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Notes

  1. Time calculations exclude the cost of image I/O

  2. Demo video is from Final Fantasy XIIII game movie.

  3. http://youtu.be/gIax02Re2Jg

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Authors and Affiliations

  1. Department of Information and Communication Engineering, The University of Tokyo, Tokyo, Tokyo, Japan

    Zhipeng Wu & Kiyoharu Aizawa

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  1. Zhipeng Wu
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  2. Kiyoharu Aizawa
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Correspondence to Zhipeng Wu.

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Wu, Z., Aizawa, K. Very fast generation of content-preserved photo collage under canvas size constraint. Multimed Tools Appl 75, 1813–1841 (2016). https://doi.org/10.1007/s11042-014-2375-6

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  • DOI: https://doi.org/10.1007/s11042-014-2375-6

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