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Video retargeting combining warping and summarizing optimization

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Abstract

We construct a unified interactive video retargeting system for video summarization, completion, and reshuffling. Our system combines the advantages of both video warping and summarizing processing. We first warp the video to present initial editing results, then refine the results using patch-based summarizing optimization, which mainly eliminates possible distortion produced in the warping step. We develop a Mean Value Coordinate (MVC) warping method due to its simplicity and efficiency used in the initialization. For refining processing, the summarization optimization is built on a 3D bidirectional similarity measure between the original and edited video, to preserve the coherence and completeness of the final editing result. We further improve the quality of summarization by applying a color histogram matching during the optimization, and accelerate the summarization optimization by using a constrained 3D Patch-Match algorithm. Experiment results show that the proposed video retargeting system effectively supports video summarization, completion, and reshuffling while avoiding issues like texture broken, video jittering, and detail losing.

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Acknowledgements

This work was partly supported by the National Basic Research Program of China (No. 2012CB725303), the NSFC (Nos. 61070081 and 41271431), the Open Project Program of the State Key Lab of CAD&CG (Grant No. A1208), the Luojia Outstanding Young Scholar Program of Wuhan University, the Project of the Science and Technology Plan for Zhejiang Province (Grant No. 2012C21004), the Fundamental Research Funds for the Central Universities, and the Academic Award for Excellent Ph.D. Candidates funded by Ministry of Education of China (No. 5052012211001).

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Correspondence to Chunxia Xiao.

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Nie, Y., Zhang, Q., Wang, R. et al. Video retargeting combining warping and summarizing optimization. Vis Comput 29, 785–794 (2013). https://doi.org/10.1007/s00371-013-0830-4

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