Article

Cartoon textures

Authors:

Christina de Juan,

Bobby BodenheimerAuthors Info & Claims

SCA '04: Proceedings of the 2004 ACM SIGGRAPH/Eurographics symposium on Computer animation

Pages 267 - 276

https://doi.org/10.1145/1028523.1028559

Published: 27 August 2004 Publication History

Abstract

In this paper we present a method for creating novel animations from a library of existing two-dimensional cartoon data. Drawing inspiration from the idea of video textures, sequences of similar-looking cartoon data are combined into a user-directed sequence. Starting with a small amount of cartoon data, we employ a method of nonlinear dimensionality reduction to discover a lower-dimensional structure of the data. The user selects a start and end frame and the system traverses this lower-dimensional manifold to re-sequence the data into a new animation. The system can automatically detect when a new sequence has visual discontinuities and may require additional source material.

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Cited By

Le TYao SWu CLee T(2024)Regenerating Arbitrary Video Sequences With Distillation Path-FindingIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2023.323773930:7(3622-3635)Online publication date: Jul-2024
https://doi.org/10.1109/TVCG.2023.3237739
Morace CLe TYao SZhang SLee T(2022)Learning a perceptual manifold with deep features for animation video resequencingMultimedia Tools and Applications10.1007/s11042-022-12251-181:17(23687-23707)Online publication date: 18-Mar-2022
https://doi.org/10.1007/s11042-022-12251-1
Dvorožnák MLi WKim VSýkora D(2018)ToonsynthACM Transactions on Graphics10.1145/3197517.320132637:4(1-11)Online publication date: 30-Jul-2018
https://dl.acm.org/doi/10.1145/3197517.3201326
Show More Cited By

Index Terms

Cartoon textures
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Image and video acquisition
        3D imaging
  2. Computer graphics
    1. Animation

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Information & Contributors

Information

Published In

cover image ACM Conferences

SCA '04: Proceedings of the 2004 ACM SIGGRAPH/Eurographics symposium on Computer animation

August 2004

388 pages

ISBN:3905673142

Conference Chairs:
Norman Badler
University of Pennsylvania
,
Mathieu Desbrun
University of Southern California
,
Ronan Boulic,
Dinesh Pai

Sponsors

SIGGRAPH: ACM Special Interest Group on Computer Graphics and Interactive Techniques
EUROGRAPHICS: The European Association for Computer Graphics

Publisher

Eurographics Association

Goslar, Germany

Publication History

Published: 27 August 2004

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SCA04

Sponsor:

SIGGRAPH
EUROGRAPHICS

SCA04: Symposium on Computer Animation 2004

August 27 - 29, 2004

Grenoble, France

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Overall Acceptance Rate 183 of 487 submissions, 38%

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Cited By

Le TYao SWu CLee T(2024)Regenerating Arbitrary Video Sequences With Distillation Path-FindingIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2023.323773930:7(3622-3635)Online publication date: Jul-2024
https://doi.org/10.1109/TVCG.2023.3237739
Morace CLe TYao SZhang SLee T(2022)Learning a perceptual manifold with deep features for animation video resequencingMultimedia Tools and Applications10.1007/s11042-022-12251-181:17(23687-23707)Online publication date: 18-Mar-2022
https://doi.org/10.1007/s11042-022-12251-1
Dvorožnák MLi WKim VSýkora D(2018)ToonsynthACM Transactions on Graphics10.1145/3197517.320132637:4(1-11)Online publication date: 30-Jul-2018
https://dl.acm.org/doi/10.1145/3197517.3201326
Al-Rousan RSunar MKolivand H(2016)Interactive toon shading using mesh smoothingInternational Journal of Intelligent Systems Technologies and Applications10.1504/IJISTA.2016.07834415:3(218-229)Online publication date: 1-Jan-2016
https://dl.acm.org/doi/10.1504/IJISTA.2016.078344
Yu J(2013)Cartoon features selection using Diffusion ScoreSignal Processing10.1016/j.sigpro.2012.06.01193:6(1510-1520)Online publication date: 1-Jun-2013
https://dl.acm.org/doi/10.1016/j.sigpro.2012.06.011
Liang ZZhuang YYang YXiao J(2013)Retrieval-based cartoon gesture recognition and applications via semi-supervised heterogeneous classifiers learningPattern Recognition10.1016/j.patcog.2012.06.02546:1(412-423)Online publication date: 1-Jan-2013
https://dl.acm.org/doi/10.1016/j.patcog.2012.06.025
Savoye YSavoye Y(2013)Reusing Performance Capture DataCage-based Performance Capture10.1007/978-3-319-01538-5_3(53-92)Online publication date: 17-Sep-2013
https://doi.org/10.1007/978-3-319-01538-5_3
Yu JTao D(2013)Animation Research: Modern TechniquesModern Machine Learning Techniques and Their Applications in Cartoon Animation Research10.1002/9781118559963.ch4(131-194)Online publication date: 2-Apr-2013
https://doi.org/10.1002/9781118559963.ch4
Zhu RYao MYe LXuan J(2012)Learning a hierarchical image manifold for Web image classificationJournal of Zhejiang University SCIENCE C10.1631/jzus.C120003213:10(719-735)Online publication date: 10-Oct-2012
https://doi.org/10.1631/jzus.C1200032
Savoye YGrau O(2012)Content-aware exaggerated editing for life-like captured animationsProceedings of the 9th European Conference on Visual Media Production10.1145/2414688.2414698(75-83)Online publication date: 5-Dec-2012
https://dl.acm.org/doi/10.1145/2414688.2414698
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