Variable duration motion texture for human motion modeling

  • Tianyu Huang*
  • , Fengxia Li
  • , Shouyi Zhan
  • , Jianyuan Min
  • *Corresponding author for this work

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

2 Citations (Scopus)

Abstract

Statistical model is an effective method for character motion modeling. In this paper, a variable duration motion texture is proposed to represent complex human motion that is statistically similar to the original captured motion data. The motion texture is defined as a three-level structure with moton abstracts, motons and their distribution. The motion texture is modeled by a Semi-SLDS (Semi- Switching Linear Dynamic System), which provides an intuitive framework for describing the continuous but nonlinear dynamics of human motion. To explicitly incorporate duration modeling capability, the Semi-SLDS is adopted to improve SLDS by replacing the Markov switching layer with semi-Markov model. In addition, the proposed approach is proved flexible and effective by several motion applications, namely motion synthesis, motion recognition and motion compression.

Original languageEnglish
Title of host publicationPRICAI 2006
Subtitle of host publicationTrends in Artificial Intelligence - 9th Pacific Rim International Conference on Artificial Intelligence, Proceedings
PublisherSpringer Verlag
Pages603-612
Number of pages10
ISBN (Print)3540366679, 9783540366676
DOIs
Publication statusPublished - 2006
Event9th Pacific Rim International Conference on Artificial Intelligence - Guilin, China
Duration: 7 Aug 200611 Aug 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4099 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference9th Pacific Rim International Conference on Artificial Intelligence
Country/TerritoryChina
CityGuilin
Period7/08/0611/08/06

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