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Evaluating distance metrics for animation blending

Published: 26 April 2009 Publication History

Abstract

Reusing motion capture data is of great importance in games and simulations. Therefore, many techniques from motion synthesis aim at concatenating or blending existing pieces of motion. For concatenation, a distance metric is required to detect good transition points. In this paper, three common distance metrics are evaluated both quantitatively and qualitatively. In the quantitive analysis we evaluate foot-skate, path deviation and on-line running time. The qualitative analysis is done by a user study. We observed that the point cloud metric results in a very slow graph search and a high path deviation compared to the other metrics. However, this metric results in less foot skating. We also show that increasing the graph size does not alway introduce more visual artifacts. Based on our observations, we propose a set of guidelines when using these metrics in a motion synthesizer.

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  • (2022)A new framework for the evaluation of locomotive motion datasets through motion matching techniquesProceedings of the 15th ACM SIGGRAPH Conference on Motion, Interaction and Games10.1145/3561975.3562951(1-10)Online publication date: 3-Nov-2022
  • (2017)Differencing and merging for 3D animation revision controlProceedings of the European Association for Computer Graphics: Posters10.2312/egp.20171038(7-8)Online publication date: 24-Apr-2017
  • (2015)Investigating similarity measures for locomotor trajectories based on the human perception of differences in motions2015 IEEE International Workshop on Advanced Robotics and its Social Impacts (ARSO)10.1109/ARSO.2015.7428196(1-6)Online publication date: Jun-2015
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    FDG '09: Proceedings of the 4th International Conference on Foundations of Digital Games
    April 2009
    386 pages
    ISBN:9781605584379
    DOI:10.1145/1536513
    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: 26 April 2009

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    Author Tags

    1. animation
    2. blending
    3. comparison
    4. evaluation
    5. metric
    6. motion
    7. synthesis

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    Cited By

    View all
    • (2022)A new framework for the evaluation of locomotive motion datasets through motion matching techniquesProceedings of the 15th ACM SIGGRAPH Conference on Motion, Interaction and Games10.1145/3561975.3562951(1-10)Online publication date: 3-Nov-2022
    • (2017)Differencing and merging for 3D animation revision controlProceedings of the European Association for Computer Graphics: Posters10.2312/egp.20171038(7-8)Online publication date: 24-Apr-2017
    • (2015)Investigating similarity measures for locomotor trajectories based on the human perception of differences in motions2015 IEEE International Workshop on Advanced Robotics and its Social Impacts (ARSO)10.1109/ARSO.2015.7428196(1-6)Online publication date: Jun-2015
    • (2015)Automated human motion segmentation via motion regularitiesThe Visual Computer: International Journal of Computer Graphics10.1007/s00371-013-0902-531:1(35-53)Online publication date: 1-Jan-2015
    • (2014)Data-Driven Reconstruction of Human Locomotion Using a Single SmartphoneComputer Graphics Forum10.1111/cgf.1246933:7(11-19)Online publication date: 1-Oct-2014
    • (2014)Flexible editing of human motion by three-way decompositionComputer Animation and Virtual Worlds10.1002/cav.153425:1(57-68)Online publication date: 1-Jan-2014
    • (2013)Perception of Approach and Reach in Combined Interaction TasksProceedings of Motion on Games10.1145/2522628.2522632(165-170)Online publication date: 6-Nov-2013
    • (2012)Efficient Generation of Dancing Animation Synchronizing with Music Based on Meta Motion GraphsIEICE Transactions on Information and Systems10.1587/transinf.E95.D.1646E95.D:6(1646-1655)Online publication date: 2012
    • (2011)Combining path planners and motion graphsComputer Animation and Virtual Worlds10.1002/cav.38722:1(59-78)Online publication date: 1-Jan-2011
    • (2010)Evaluating the physical realism of character animations using musculoskeletal modelsProceedings of the Third international conference on Motion in games10.5555/1948395.1948398(11-22)Online publication date: 14-Nov-2010
    • Show More Cited By

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