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Synthesis and editing of human motion with generative human motion model

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this paper, a generic approach is presented to constructing generative motion model from prerecorded motion data that allows the synthesis of new motions or modification of existing motions in various ways. The key idea is to decompose human motion data into a series of latent variables which decompose a number of sports from different properties, in the way motion variations are interpreted by modeling human motion data in the Gaussian process. The effectiveness and flexibility of this approach in experiments and applications are demonstrated by constructing two generative motion models as an example of various kinds of motion properties.

Original languageEnglish
Title of host publicationProceedings - 2015 International Conference on Virtual Reality and Visualization, ICVRV 2015
EditorsZhong Zhou, Weiliang Meng, Junfeng Yao, Xiaopeng Zhang, Xun Luo
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages193-196
Number of pages4
ISBN (Electronic)9781467376730
DOIs
StatePublished - 9 May 2016
Event5th International Conference on Virtual Reality and Visualization, ICVRV 2015 - Xiamen, Fujian, China
Duration: 17 Oct 201518 Oct 2015

Publication series

NameProceedings - 2015 International Conference on Virtual Reality and Visualization, ICVRV 2015

Conference

Conference5th International Conference on Virtual Reality and Visualization, ICVRV 2015
Country/TerritoryChina
CityXiamen, Fujian
Period17/10/1518/10/15

Keywords

  • Character animation
  • Generative motion models
  • Motion editing and synthesis

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