Hybrid Skeletal-Surface Motion Graphs for Character Animation from 4D Performance Capture

ACM Trans. Graph. Pub Date : 2015-03-02 DOI:10.1145/2699643
Peng Huang, M. Tejera, J. Collomosse, A. Hilton
{"title":"Hybrid Skeletal-Surface Motion Graphs for Character Animation from 4D Performance Capture","authors":"Peng Huang, M. Tejera, J. Collomosse, A. Hilton","doi":"10.1145/2699643","DOIUrl":null,"url":null,"abstract":"We present a novel hybrid representation for character animation from 4D Performance Capture (4DPC) data which combines skeletal control with surface motion graphs. 4DPC data are temporally aligned 3D mesh sequence reconstructions of the dynamic surface shape and associated appearance from multiple-view video. The hybrid representation supports the production of novel surface sequences which satisfy constraints from user-specified key-frames or a target skeletal motion. Motion graph path optimisation concatenates fragments of 4DPC data to satisfy the constraints while maintaining plausible surface motion at transitions between sequences. Space-time editing of the mesh sequence using a learned part-based Laplacian surface deformation model is performed to match the target skeletal motion and transition between sequences. The approach is quantitatively evaluated for three 4DPC datasets with a variety of clothing styles. Results for key-frame animation demonstrate production of novel sequences that satisfy constraints on timing and position of less than 1% of the sequence duration and path length. Evaluation of motion-capture-driven animation over a corpus of 130 sequences shows that the synthesised motion accurately matches the target skeletal motion. The combination of skeletal control with the surface motion graph extends the range and style of motion which can be produced while maintaining the natural dynamics of shape and appearance from the captured performance.","PeriodicalId":7121,"journal":{"name":"ACM Trans. Graph.","volume":"33 1","pages":"17:1-17:14"},"PeriodicalIF":0.0000,"publicationDate":"2015-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"43","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM Trans. Graph.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2699643","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 43

Abstract

We present a novel hybrid representation for character animation from 4D Performance Capture (4DPC) data which combines skeletal control with surface motion graphs. 4DPC data are temporally aligned 3D mesh sequence reconstructions of the dynamic surface shape and associated appearance from multiple-view video. The hybrid representation supports the production of novel surface sequences which satisfy constraints from user-specified key-frames or a target skeletal motion. Motion graph path optimisation concatenates fragments of 4DPC data to satisfy the constraints while maintaining plausible surface motion at transitions between sequences. Space-time editing of the mesh sequence using a learned part-based Laplacian surface deformation model is performed to match the target skeletal motion and transition between sequences. The approach is quantitatively evaluated for three 4DPC datasets with a variety of clothing styles. Results for key-frame animation demonstrate production of novel sequences that satisfy constraints on timing and position of less than 1% of the sequence duration and path length. Evaluation of motion-capture-driven animation over a corpus of 130 sequences shows that the synthesised motion accurately matches the target skeletal motion. The combination of skeletal control with the surface motion graph extends the range and style of motion which can be produced while maintaining the natural dynamics of shape and appearance from the captured performance.
混合骨架表面运动图形从4D性能捕捉的角色动画
我们提出了一种新的混合表示从4D性能捕获(4DPC)数据的角色动画,结合了骨骼控制和表面运动图形。4DPC数据是多视点视频中动态表面形状和相关外观的临时对齐三维网格序列重建。混合表示支持生成满足用户指定关键帧或目标骨骼运动约束的新表面序列。运动图路径优化将4DPC数据片段连接在一起,以满足约束条件,同时在序列之间的转换中保持合理的表面运动。利用学习到的基于零件的拉普拉斯曲面变形模型对网格序列进行时空编辑,以匹配目标骨骼运动和序列之间的转换。该方法对具有各种服装风格的三个4DPC数据集进行了定量评估。关键帧动画的结果表明,新序列的生成满足了序列持续时间和路径长度小于1%的时序和位置约束。在130个序列的语料库上对动作捕捉驱动动画的评估表明,合成的运动准确地匹配目标骨骼运动。骨骼控制与表面运动图形的结合扩展了运动的范围和风格,可以在保持捕获性能的形状和外观的自然动态的同时产生。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信