Multi-character Motion Retargeting for Large-Scale Transformations

Research output: Chapter in Book/Report/Conference proceedingConference contribution

21 Downloads (Pure)

Abstract

Unlike single-character motion retargeting, multi-character motion retargeting (MCMR) algorithms should be able to retarget each character’s motion correcly while maintaining the interaction between them. Existing MCMR solutions mainly focus on small scale changes between interacting characters. However, many retargeting applications require large-scale transformations. In this paper, we propose a new algorithm for large-scale MCMR. We build on the idea of interaction meshes, which are structures representing the spatial relationship among characters. We introduce a new distance-based interaction mesh that embodies the relationship between characters more accurately by prioritizing local connections over global ones. We also introduce a stiffness weight for each skeletal joint in our mesh deformation term, which defines how undesirable it is for the interaction mesh to deform around that joint. This parameter increases the adaptability of our algorithm for large-scale transformations and reduces optimization time considerably. We compare the performance of our algorithm with current state-of-the-art MCMR solution for several motion sequences under four different scenarios. Our results show that our method not only improves the quality of retargeting, but also significantly reduces computation time.

Original languageEnglish
Title of host publicationAdvances in Computer Graphics - 36th Computer Graphics International Conference, CGI 2019, Proceedings
Subtitle of host publicationAdvances in Computer Graphics
EditorsMarina Gavrilova, Nadia Magnenat Thalmann, Hiroshi Ishikawa, Jian Chang, Nadia Magnenat Thalmann, Eckhard Hitzer
PublisherSpringer Verlag
Pages94-106
Number of pages13
ISBN (Electronic)978-3-030-22514-8
ISBN (Print)978-3-030-22513-1
DOIs
Publication statusE-pub ahead of print - 12 Jun 2019
Event36th Computer Graphics International Conference, CGI 2019 - Calgary, Canada
Duration: 17 Jun 201920 Jun 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11542 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference36th Computer Graphics International Conference, CGI 2019
CountryCanada
CityCalgary
Period17/06/1920/06/19

Keywords

  • Character interaction
  • Computer animation
  • Joint stiffness
  • Mesh deformation
  • Motion retargeting
  • Space-time optimization

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Naghizadeh, M., & Cosker, D. (2019). Multi-character Motion Retargeting for Large-Scale Transformations. In M. Gavrilova, N. M. Thalmann, H. Ishikawa, J. Chang, N. M. Thalmann, & E. Hitzer (Eds.), Advances in Computer Graphics - 36th Computer Graphics International Conference, CGI 2019, Proceedings: Advances in Computer Graphics (pp. 94-106). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11542 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-030-22514-8_8

Multi-character Motion Retargeting for Large-Scale Transformations. / Naghizadeh, Maryam; Cosker, Darren.

Advances in Computer Graphics - 36th Computer Graphics International Conference, CGI 2019, Proceedings: Advances in Computer Graphics. ed. / Marina Gavrilova; Nadia Magnenat Thalmann; Hiroshi Ishikawa; Jian Chang; Nadia Magnenat Thalmann; Eckhard Hitzer. Springer Verlag, 2019. p. 94-106 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11542 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Naghizadeh, M & Cosker, D 2019, Multi-character Motion Retargeting for Large-Scale Transformations. in M Gavrilova, NM Thalmann, H Ishikawa, J Chang, NM Thalmann & E Hitzer (eds), Advances in Computer Graphics - 36th Computer Graphics International Conference, CGI 2019, Proceedings: Advances in Computer Graphics. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11542 LNCS, Springer Verlag, pp. 94-106, 36th Computer Graphics International Conference, CGI 2019, Calgary, Canada, 17/06/19. https://doi.org/10.1007/978-3-030-22514-8_8
Naghizadeh M, Cosker D. Multi-character Motion Retargeting for Large-Scale Transformations. In Gavrilova M, Thalmann NM, Ishikawa H, Chang J, Thalmann NM, Hitzer E, editors, Advances in Computer Graphics - 36th Computer Graphics International Conference, CGI 2019, Proceedings: Advances in Computer Graphics. Springer Verlag. 2019. p. 94-106. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-030-22514-8_8
Naghizadeh, Maryam ; Cosker, Darren. / Multi-character Motion Retargeting for Large-Scale Transformations. Advances in Computer Graphics - 36th Computer Graphics International Conference, CGI 2019, Proceedings: Advances in Computer Graphics. editor / Marina Gavrilova ; Nadia Magnenat Thalmann ; Hiroshi Ishikawa ; Jian Chang ; Nadia Magnenat Thalmann ; Eckhard Hitzer. Springer Verlag, 2019. pp. 94-106 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
@inproceedings{b6c35e93726644378a5c75df31f5e6c6,
title = "Multi-character Motion Retargeting for Large-Scale Transformations",
abstract = "Unlike single-character motion retargeting, multi-character motion retargeting (MCMR) algorithms should be able to retarget each character’s motion correcly while maintaining the interaction between them. Existing MCMR solutions mainly focus on small scale changes between interacting characters. However, many retargeting applications require large-scale transformations. In this paper, we propose a new algorithm for large-scale MCMR. We build on the idea of interaction meshes, which are structures representing the spatial relationship among characters. We introduce a new distance-based interaction mesh that embodies the relationship between characters more accurately by prioritizing local connections over global ones. We also introduce a stiffness weight for each skeletal joint in our mesh deformation term, which defines how undesirable it is for the interaction mesh to deform around that joint. This parameter increases the adaptability of our algorithm for large-scale transformations and reduces optimization time considerably. We compare the performance of our algorithm with current state-of-the-art MCMR solution for several motion sequences under four different scenarios. Our results show that our method not only improves the quality of retargeting, but also significantly reduces computation time.",
keywords = "Character interaction, Computer animation, Joint stiffness, Mesh deformation, Motion retargeting, Space-time optimization",
author = "Maryam Naghizadeh and Darren Cosker",
year = "2019",
month = "6",
day = "12",
doi = "10.1007/978-3-030-22514-8_8",
language = "English",
isbn = "978-3-030-22513-1",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "94--106",
editor = "Marina Gavrilova and Thalmann, {Nadia Magnenat} and Hiroshi Ishikawa and Jian Chang and Thalmann, {Nadia Magnenat} and Eckhard Hitzer",
booktitle = "Advances in Computer Graphics - 36th Computer Graphics International Conference, CGI 2019, Proceedings",

}

TY - GEN

T1 - Multi-character Motion Retargeting for Large-Scale Transformations

AU - Naghizadeh, Maryam

AU - Cosker, Darren

PY - 2019/6/12

Y1 - 2019/6/12

N2 - Unlike single-character motion retargeting, multi-character motion retargeting (MCMR) algorithms should be able to retarget each character’s motion correcly while maintaining the interaction between them. Existing MCMR solutions mainly focus on small scale changes between interacting characters. However, many retargeting applications require large-scale transformations. In this paper, we propose a new algorithm for large-scale MCMR. We build on the idea of interaction meshes, which are structures representing the spatial relationship among characters. We introduce a new distance-based interaction mesh that embodies the relationship between characters more accurately by prioritizing local connections over global ones. We also introduce a stiffness weight for each skeletal joint in our mesh deformation term, which defines how undesirable it is for the interaction mesh to deform around that joint. This parameter increases the adaptability of our algorithm for large-scale transformations and reduces optimization time considerably. We compare the performance of our algorithm with current state-of-the-art MCMR solution for several motion sequences under four different scenarios. Our results show that our method not only improves the quality of retargeting, but also significantly reduces computation time.

AB - Unlike single-character motion retargeting, multi-character motion retargeting (MCMR) algorithms should be able to retarget each character’s motion correcly while maintaining the interaction between them. Existing MCMR solutions mainly focus on small scale changes between interacting characters. However, many retargeting applications require large-scale transformations. In this paper, we propose a new algorithm for large-scale MCMR. We build on the idea of interaction meshes, which are structures representing the spatial relationship among characters. We introduce a new distance-based interaction mesh that embodies the relationship between characters more accurately by prioritizing local connections over global ones. We also introduce a stiffness weight for each skeletal joint in our mesh deformation term, which defines how undesirable it is for the interaction mesh to deform around that joint. This parameter increases the adaptability of our algorithm for large-scale transformations and reduces optimization time considerably. We compare the performance of our algorithm with current state-of-the-art MCMR solution for several motion sequences under four different scenarios. Our results show that our method not only improves the quality of retargeting, but also significantly reduces computation time.

KW - Character interaction

KW - Computer animation

KW - Joint stiffness

KW - Mesh deformation

KW - Motion retargeting

KW - Space-time optimization

UR - http://www.scopus.com/inward/record.url?scp=85067700229&partnerID=8YFLogxK

U2 - 10.1007/978-3-030-22514-8_8

DO - 10.1007/978-3-030-22514-8_8

M3 - Conference contribution

SN - 978-3-030-22513-1

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 94

EP - 106

BT - Advances in Computer Graphics - 36th Computer Graphics International Conference, CGI 2019, Proceedings

A2 - Gavrilova, Marina

A2 - Thalmann, Nadia Magnenat

A2 - Ishikawa, Hiroshi

A2 - Chang, Jian

A2 - Thalmann, Nadia Magnenat

A2 - Hitzer, Eckhard

PB - Springer Verlag

ER -