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Video inpainting and implant via diversified temporal continuations (video demonstration)

Published: 23 October 2006 Publication History

Abstract

This video program presents several video inpainting/implant mechanisms implemented under different types of videos with diversified temporal continuations. We use an improved image inpainting method to remove foreground objects. Another set of objects are implanted into the inpainted video. Detailed algorithms are presented in a paper in the 2006 ACM Multimedia conference.

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[1]
Timothy K. Shih, Nick C. Tang, Wei-Sung Yeh, Ta-Jen Chen, and Wonjun Lee, "Video Inpainting and Implant via Diversified Temporal Continuations," in Proceedings of the 2006 ACM Multimedia conference, Santa Barbara, California, USA, October 23- 27, 2006.

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  1. Video inpainting and implant via diversified temporal continuations (video demonstration)

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      cover image ACM Conferences
      MM '06: Proceedings of the 14th ACM international conference on Multimedia
      October 2006
      1072 pages
      ISBN:1595934472
      DOI:10.1145/1180639
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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      New York, NY, United States

      Publication History

      Published: 23 October 2006

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      Author Tags

      1. object removal
      2. object tracking
      3. temporal continuations
      4. video implant
      5. video inpainting

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      MM06
      MM06: The 14th ACM International Conference on Multimedia 2006
      October 23 - 27, 2006
      CA, Santa Barbara, USA

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      Overall Acceptance Rate 2,145 of 8,556 submissions, 25%

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