Article

The cartoon animation filter

Authors:

Steven M. Drucker,

Maneesh Agrawala,

Michael F. CohenAuthors Info & Claims

SIGGRAPH '06: ACM SIGGRAPH 2006 Papers

Pages 1169 - 1173

https://doi.org/10.1145/1179352.1142010

Published: 01 July 2006 Publication History

Abstract

We present the "Cartoon Animation Filter", a simple filter that takes an arbitrary input motion signal and modulates it in such a way that the output motion is more "alive" or "animated". The filter adds a smoothed, inverted, and (sometimes) time shifted version of the second derivative (the acceleration) of the signal back into the original signal. Almost all parameters of the filter are automated. The user only needs to set the desired strength of the filter. The beauty of the animation filter lies in its simplicity and generality. We apply the filter to motions ranging from hand drawn trajectories, to simple animations within PowerPoint presentations, to motion captured DOF curves, to video segmentation results. Experimental results show that the filtered motion exhibits anticipation, follow-through, exaggeration and squash-and-stretch effects which are not present in the original input motion data.

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Cited By

Ahmed AAbdelrazek MAryal SNguyen T(2023)An overview of Eulerian video motion magnification methodsComputers and Graphics10.1016/j.cag.2023.10.015117:C(145-163)Online publication date: 1-Dec-2023
https://dl.acm.org/doi/10.1016/j.cag.2023.10.015
Tazawa RMori HToyama F(2022)Enhanced Motion Details of Virtual Humans Using Machine Learning2022 International Conference on Cyberworlds (CW)10.1109/CW55638.2022.00025(114-117)Online publication date: Sep-2022
https://doi.org/10.1109/CW55638.2022.00025
Fahmy G(2021)Detection of Micro Movements of Facial Muscles in Facial Videos2021 9th International Japan-Africa Conference on Electronics, Communications, and Computations (JAC-ECC)10.1109/JAC-ECC54461.2021.9691309(1-4)Online publication date: 13-Dec-2021
https://doi.org/10.1109/JAC-ECC54461.2021.9691309
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Index Terms

The cartoon animation filter
1. Computing methodologies
  1. Computer graphics
    1. Animation
    2. Shape modeling
      1. Parametric curve and surface models
      2. Volumetric models
  2. Modeling and simulation
    1. Simulation types and techniques
      1. Simulation by animation
2. Theory of computation
  1. Randomness, geometry and discrete structures

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Published In

cover image ACM Conferences

SIGGRAPH '06: ACM SIGGRAPH 2006 Papers

July 2006

742 pages

ISBN:1595933646

DOI:10.1145/1179352

Conference Chair:
John Finnegan
Purdue University
,
Program Chair:
Julie Dorsey
Yale University

Copyright © 2006 ACM.

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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Published: 01 July 2006

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SIGGRAPH06: Special Interest Group on Computer Graphics and Interactive Techniques Conference

July 30 - August 3, 2006

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Acceptance Rates

SIGGRAPH '06 Paper Acceptance Rate 86 of 474 submissions, 18%;

Overall Acceptance Rate 1,822 of 8,601 submissions, 21%

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Cited By

Ahmed AAbdelrazek MAryal SNguyen T(2023)An overview of Eulerian video motion magnification methodsComputers and Graphics10.1016/j.cag.2023.10.015117:C(145-163)Online publication date: 1-Dec-2023
https://dl.acm.org/doi/10.1016/j.cag.2023.10.015
Tazawa RMori HToyama F(2022)Enhanced Motion Details of Virtual Humans Using Machine Learning2022 International Conference on Cyberworlds (CW)10.1109/CW55638.2022.00025(114-117)Online publication date: Sep-2022
https://doi.org/10.1109/CW55638.2022.00025
Fahmy G(2021)Detection of Micro Movements of Facial Muscles in Facial Videos2021 9th International Japan-Africa Conference on Electronics, Communications, and Computations (JAC-ECC)10.1109/JAC-ECC54461.2021.9691309(1-4)Online publication date: 13-Dec-2021
https://doi.org/10.1109/JAC-ECC54461.2021.9691309
Lima JMiosso CFarias M(2020)Hybrid Motion Magnification based on Same-Frame Optical Flow Computations2020 IEEE 22nd International Workshop on Multimedia Signal Processing (MMSP)10.1109/MMSP48831.2020.9287152(1-7)Online publication date: 21-Sep-2020
https://doi.org/10.1109/MMSP48831.2020.9287152
Fahmy GFahmy OFahmy M(2019)Fast Enhanced DWT based Video Micro Movement Magnification2019 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT)10.1109/ISSPIT47144.2019.9001874(1-6)Online publication date: Dec-2019
https://doi.org/10.1109/ISSPIT47144.2019.9001874
Su QBai XFu HTai CWang JMandryk RHancock MPerry MCox A(2018)Live SketchProceedings of the 2018 CHI Conference on Human Factors in Computing Systems10.1145/3173574.3174236(1-12)Online publication date: 21-Apr-2018
https://dl.acm.org/doi/10.1145/3173574.3174236
Popek MDanielewska MIskander D(2017)Assessing frequency response of video motion magnification techniques2017 Signal Processing Symposium (SPSympo)10.1109/SPS.2017.8053674(1-4)Online publication date: Sep-2017
https://doi.org/10.1109/SPS.2017.8053674
Ruhland KPrasad MMcDonnell R(2017)Data-Driven Approach to Synthesizing Facial Animation Using Motion CaptureIEEE Computer Graphics and Applications10.1109/MCG.2017.327146737:4(30-41)Online publication date: 2017
https://doi.org/10.1109/MCG.2017.3271467
Kazi RGrossman TUmetani NFitzmaurice GKaye JDruin ALampe CMorris DHourcade J(2016)Motion AmplifiersProceedings of the 2016 CHI Conference on Human Factors in Computing Systems10.1145/2858036.2858386(4599-4609)Online publication date: 7-May-2016
https://dl.acm.org/doi/10.1145/2858036.2858386
KOMMA TSAITO TABE S(2013)Analysis and Adaptation for Exaggeration Types of Animation MotionJournal of Graphic Science of Japan10.5989/jsgs.47.2-3_1347:2-3(13-23)Online publication date: 2013
https://doi.org/10.5989/jsgs.47.2-3_13
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