article

A physically-based motion retargeting filter

Authors:

Hyeong-Seok KoAuthors Info & Claims

ACM Transactions on Graphics (TOG), Volume 24, Issue 1

Pages 98 - 117

https://doi.org/10.1145/1037957.1037963

Published: 01 January 2005 Publication History

Abstract

This article presents a novel constraint-based motion editing technique. On the basis of animator-specified kinematic and dynamic constraints, the method converts a given captured or animated motion to a physically plausible motion. In contrast to previous methods using spacetime optimization, we cast the motion editing problem as a constrained state estimation problem, based on the per-frame Kalman filter framework. The method works as a filter that sequentially scans the input motion to produce a stream of output motion frames at a stable interactive rate. Animators can tune several filter parameters to adjust to different motions, turn the constraints on or off based on their contributions to the final result, or provide a rough sketch (kinematic hint) as an effective way of producing the desired motion. Experiments on various systems show that the technique processes the motions of a human with 54 degrees of freedom, at about 150 fps when only kinematic constraints are applied, and at about 10 fps when both kinematic and dynamic constraints are applied. Experiments on various types of motion show that the proposed method produces remarkably realistic animations.

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Hu LZhang ZZhong CJiang BXia S(2024)Pose-Aware Attention Network for Flexible Motion Retargeting by Body PartIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2023.327791830:8(4792-4808)Online publication date: 1-Aug-2024
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Zhou LLannan NFan G(2024)A Review of Depth-Based Human Motion Enhancement: Past and PresentIEEE Journal of Biomedical and Health Informatics10.1109/JBHI.2023.325766228:2(633-644)Online publication date: Feb-2024
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Index Terms

A physically-based motion retargeting filter
1. Computing methodologies
  1. Artificial intelligence
    1. Control methods
      1. Motion path planning
  2. Computer graphics
    1. Animation

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cover image ACM Transactions on Graphics

ACM Transactions on Graphics Volume 24, Issue 1

January 2005

179 pages

ISSN:0730-0301

EISSN:1557-7368

DOI:10.1145/1037957

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Copyright © 2005 ACM.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 January 2005

Published in TOG Volume 24, Issue 1

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Cited By

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https://dl.acm.org/doi/10.1109/TVCG.2023.3277918
Zhang JTu ZWeng JYuan JDu B(2024)A Modular Neural Motion Retargeting System Decoupling Skeleton and Shape PerceptionIEEE Transactions on Pattern Analysis and Machine Intelligence10.1109/TPAMI.2024.338677746:10(6889-6904)Online publication date: Oct-2024
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Rekik RMarsot MOlivier AFranco JWuhrer S(2024)Correspondence-Free Online Human Motion Retargeting2024 International Conference on 3D Vision (3DV)10.1109/3DV62453.2024.00032(707-716)Online publication date: 18-Mar-2024
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Li TWon JClegg AKim JRai AHa S(2023)ACE: Adversarial Correspondence Embedding for Cross Morphology Motion Retargeting from Human to Nonhuman CharactersSIGGRAPH Asia 2023 Conference Papers10.1145/3610548.3618255(1-11)Online publication date: 10-Dec-2023
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