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Panoramic video textures

Published: 01 July 2005 Publication History

Abstract

This paper describes a mostly automatic method for taking the output of a single panning video camera and creating a panoramic video texture (PVT): a video that has been stitched into a single, wide field of view and that appears to play continuously and indefinitely. The key problem in creating a PVT is that although only a portion of the scene has been imaged at any given time, the output must simultaneously portray motion throughout the scene. Like previous work in video textures, our method employs min-cut optimization to select fragments of video that can be stitched together both spatially and temporally. However, it differs from earlier work in that the optimization must take place over a much larger set of data. Thus, to create PVTs, we introduce a dynamic programming step, followed by a novel hierarchical min-cut optimization algorithm. We also use gradient-domain compositing to further smooth boundaries between video fragments. We demonstrate our results with an interactive viewer in which users can interactively pan and zoom on high-resolution PVTs.

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cover image ACM Conferences
SIGGRAPH '05: ACM SIGGRAPH 2005 Papers
July 2005
826 pages
ISBN:9781450378253
DOI:10.1145/1186822
  • Editor:
  • Markus Gross
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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Publication History

Published: 01 July 2005

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Author Tags

  1. panoramas
  2. video textures
  3. video-based rendering

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SIGGRAPH '05 Paper Acceptance Rate 98 of 461 submissions, 21%;
Overall Acceptance Rate 1,822 of 8,601 submissions, 21%

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  • (2024)VidPanos: Generative Panoramic Videos from Casual Panning VideosSIGGRAPH Asia 2024 Conference Papers10.1145/3680528.3687664(1-11)Online publication date: 3-Dec-2024
  • (2024)Neural Light Spheres for Implicit Image Stitching and View SynthesisSIGGRAPH Asia 2024 Conference Papers10.1145/3680528.3687660(1-11)Online publication date: 3-Dec-2024
  • (2023)Text-Guided Synthesis of Eulerian CinemagraphsACM Transactions on Graphics10.1145/361832642:6(1-13)Online publication date: 5-Dec-2023
  • (2023)Blind Video Deflickering by Neural Filtering with a Flawed Atlas2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)10.1109/CVPR52729.2023.01006(10439-10448)Online publication date: Jun-2023
  • (2023)Blowing in the Wind: CycleNet for Human Cinemagraphs from Still Images2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)10.1109/CVPR52729.2023.00052(459-468)Online publication date: Jun-2023
  • (2021)Layered neural atlases for consistent video editingACM Transactions on Graphics10.1145/3478513.348054640:6(1-12)Online publication date: 10-Dec-2021
  • (2020)Layered neural rendering for retiming people in videoACM Transactions on Graphics10.1145/3414685.341776039:6(1-14)Online publication date: 27-Nov-2020
  • (2019)View-Dependent Video Textures for 360° VideoProceedings of the 32nd Annual ACM Symposium on User Interface Software and Technology10.1145/3332165.3347887(249-262)Online publication date: 17-Oct-2019
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  • (2019)Structure-Constrained Motion Sequence GenerationIEEE Transactions on Multimedia10.1109/TMM.2018.288523521:7(1799-1812)Online publication date: Jul-2019
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