GPU-based Motion Matching for Crowds in the Unreal Engine

Nagaraj Raparthi; Eric Acosta; Alan Liu; Tim McLaughlin

doi:10.1145/3415264.3425474

GPU-based Motion Matching for Crowds in the Unreal Engine

Nagaraj Raparthi, Eric Acosta, Alan Liu, Tim McLaughlin

Medicine

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Scopus citations

Abstract

Motion Matching is a computationally expensive animation selection process where a motion capture database is regularly searched to identify the best frame of animation to be played. This study presents a process used to compute these calculations in parallel by using multiple GPU threads. The described work is shown to greatly reduce the computational time of CPU - based Motion Matching within the Unreal Engine.

Original language	English
Title of host publication	SIGGRAPH Asia 2020 Posters. SA 2020
Publisher	Association for Computing Machinery, Inc
ISBN (Electronic)	9781450381130
DOIs	https://doi.org/10.1145/3415264.3425474
State	Published - 4 Dec 2020
Event	SIGGRAPH Asia 2020 Posters - International Conference on Computer Graphics and Interactive Techniques, SA 2020 - Virtual, Online, Korea, Republic of Duration: 4 Dec 2020 → 13 Dec 2020

Publication series

Name	SIGGRAPH Asia 2020 Posters. SA 2020

Conference

Conference	SIGGRAPH Asia 2020 Posters - International Conference on Computer Graphics and Interactive Techniques, SA 2020
Country/Territory	Korea, Republic of
City	Virtual, Online
Period	4/12/20 → 13/12/20

Access to Document

10.1145/3415264.3425474

Cite this

@inproceedings{963704ecb2d0432888f0f63635a48a2f,

title = "GPU-based Motion Matching for Crowds in the Unreal Engine",

abstract = "Motion Matching is a computationally expensive animation selection process where a motion capture database is regularly searched to identify the best frame of animation to be played. This study presents a process used to compute these calculations in parallel by using multiple GPU threads. The described work is shown to greatly reduce the computational time of CPU - based Motion Matching within the Unreal Engine.",

author = "Nagaraj Raparthi and Eric Acosta and Alan Liu and Tim McLaughlin",

note = "Publisher Copyright: {\textcopyright} 2020 Owner/Author.; SIGGRAPH Asia 2020 Posters - International Conference on Computer Graphics and Interactive Techniques, SA 2020 ; Conference date: 04-12-2020 Through 13-12-2020",

year = "2020",

month = dec,

day = "4",

doi = "10.1145/3415264.3425474",

language = "English",

series = "SIGGRAPH Asia 2020 Posters. SA 2020",

publisher = "Association for Computing Machinery, Inc",

booktitle = "SIGGRAPH Asia 2020 Posters. SA 2020",

}

Raparthi, N, Acosta, E, Liu, A & McLaughlin, T 2020, GPU-based Motion Matching for Crowds in the Unreal Engine. in SIGGRAPH Asia 2020 Posters. SA 2020. SIGGRAPH Asia 2020 Posters. SA 2020, Association for Computing Machinery, Inc, SIGGRAPH Asia 2020 Posters - International Conference on Computer Graphics and Interactive Techniques, SA 2020, Virtual, Online, Korea, Republic of, 4/12/20. https://doi.org/10.1145/3415264.3425474

TY - GEN

T1 - GPU-based Motion Matching for Crowds in the Unreal Engine

AU - Raparthi, Nagaraj

AU - Acosta, Eric

AU - Liu, Alan

AU - McLaughlin, Tim

PY - 2020/12/4

Y1 - 2020/12/4

N2 - Motion Matching is a computationally expensive animation selection process where a motion capture database is regularly searched to identify the best frame of animation to be played. This study presents a process used to compute these calculations in parallel by using multiple GPU threads. The described work is shown to greatly reduce the computational time of CPU - based Motion Matching within the Unreal Engine.

AB - Motion Matching is a computationally expensive animation selection process where a motion capture database is regularly searched to identify the best frame of animation to be played. This study presents a process used to compute these calculations in parallel by using multiple GPU threads. The described work is shown to greatly reduce the computational time of CPU - based Motion Matching within the Unreal Engine.

UR - http://www.scopus.com/inward/record.url?scp=85099778845&partnerID=8YFLogxK

U2 - 10.1145/3415264.3425474

DO - 10.1145/3415264.3425474

M3 - Conference contribution

AN - SCOPUS:85099778845

T3 - SIGGRAPH Asia 2020 Posters. SA 2020

BT - SIGGRAPH Asia 2020 Posters. SA 2020

PB - Association for Computing Machinery, Inc

T2 - SIGGRAPH Asia 2020 Posters - International Conference on Computer Graphics and Interactive Techniques, SA 2020

Y2 - 4 December 2020 through 13 December 2020

ER -