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Interactive editing of motion style using drives and correlations

Published: 01 August 2009 Publication History

Abstract

Animation data, from motion capture or other sources, is becoming increasingly available and provides high quality motion, but is difficult to customize for the needs of a particular application. This is especially true when stylistic changes are needed, for example, to reflect a character's changing mood, differentiate one character from another or meet the precise desires of an animator. We introduce a system for editing animation data that is particularly well suited to making stylistic changes. Our approach transforms the joint angle representation of animation data into a set of pose parameters more suitable for editing. These motion drives include position data for the wrists, ankles and center of mass, as well as the rotation of the pelvis. We also extract correlations between drives and body movement, specifically between wrist position and the torso angles. The system solves for the pose at each frame based on the current values of these drives and correlations using an efficient set of inverse kinematics and balance algorithms. An animator can interactively edit the motion by performing linear operations on the motion drives or extracted correlations, or by layering additional correlations. We demonstrate the effectiveness of the approach with various examples of gesture and locomotion.

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    cover image ACM Conferences
    SCA '09: Proceedings of the 2009 ACM SIGGRAPH/Eurographics Symposium on Computer Animation
    August 2009
    258 pages
    ISBN:9781605586106
    DOI:10.1145/1599470
    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 August 2009

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    • (2024)ASAP: animation system for agent-based presentationsThe Visual Computer10.1007/s00371-024-03622-wOnline publication date: 3-Oct-2024
    • (2020)Understanding the Predictability of Gesture Parameters from Speech and their Perceptual ImportanceProceedings of the 20th ACM International Conference on Intelligent Virtual Agents10.1145/3383652.3423882(1-8)Online publication date: 20-Oct-2020
    • (2019)Stylized human motion warping method based on identity-independent coordinatesSoft Computing10.1007/s00500-019-04489-zOnline publication date: 4-Nov-2019
    • (2019)Development and evaluation of a self-training system for tennis shots with motion feature assessment and visualizationThe Visual Computer10.1007/s00371-019-01662-1Online publication date: 6-May-2019
    • (2018)Self-Training System for Tennis Shots with Motion Feature Assessment and Visualization2018 International Conference on Cyberworlds (CW)10.1109/CW.2018.00025(82-89)Online publication date: Oct-2018
    • (2018)Expressive Human Pose Deformation Based on the Rules of Attractive PosesInteractivity, Game Creation, Design, Learning, and Innovation10.1007/978-3-319-76908-0_16(162-171)Online publication date: 7-Mar-2018
    • (2017)Finding rules of attractive human poses using decision tree and generating novel attractive posesProceedings of the Computer Graphics International Conference10.1145/3095140.3095173(1-6)Online publication date: 27-Jun-2017
    • (2017)Motion Style Retargeting to Characters With Different MorphologiesComputer Graphics Forum10.1111/cgf.1286036:6(86-99)Online publication date: 1-Sep-2017
    • (2016)Expert-Driven Perceptual Features for Modeling Style and Affect in Human MotionIEEE Transactions on Human-Machine Systems10.1109/THMS.2016.253776046:4(534-545)Online publication date: Aug-2016
    • (2014)Lessons from the artsNonverbal Communication in Virtual Worlds10.5555/2812748.2812758(123-148)Online publication date: 1-Jan-2014
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