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Real-time video photomosaics with optimized image set and GPU

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Abstract

We propose a real-time approach to automatically generate photomosaic videos from a set of optimized images by taking advantage of CUDA GPU acceleration. Our approach divides an input image into smaller cells—usually rectangular cells—and replaces each cell with a small image of an appropriate color pattern. Photomosaics require a large set of tile images with a variety of patterns to create high-quality digital mosaic images. Because a large database of images requires longer processing time and larger storage space for searching patterns from the database, this requirement causes problems in developing a real-time system or mobile applications that have limited resources. This paper deals with a real-time video photomosaics using genetic feature selection method for building an optimized image set and taking advantage of CUDA to accelerate pattern searching that minimizes computation cost.

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Acknowledgments

This work was supported by the IT R&D program of MCST/MKE/IITA. (2008-F-030-02, Development of Full 3D Reconstruction Technology for Broadcasting Communication Fusion)

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Authors and Affiliations

  1. ETRI, 218 Gajeongno, Yuseong-gu, Daejeon, Republic of Korea

    Yoon-Seok Choi, Soonchul Jung, Jae Woo Kim & Bon-Ki Koo

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  1. Yoon-Seok Choi
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  2. Soonchul Jung
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Correspondence to Yoon-Seok Choi.

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Choi, YS., Jung, S., Kim, J.W. et al. Real-time video photomosaics with optimized image set and GPU. J Real-Time Image Proc 9, 569–578 (2014). https://doi.org/10.1007/s11554-013-0384-8

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