A Divide-and-conquer Solution to 3D Human Motion Estimation from Raw MoCap Data

Tang, J; Li, L; Hou, J; Xin, H; Yu, X

A Divide-and-conquer Solution to 3D Human Motion Estimation from Raw MoCap Data

Tang, J Li, L Hou, J Xin, H Yu, X

Permalink

Publisher:: IEEE
Publication Type:: Conference Proceeding
Citation:: 2023 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW), 2023, pp. 767-768
Issue Date:: 2023-05-01

Closed Access

	Filename	Description	Size
	A_Divide-and-conquer_Solution_to_3D_Human_Motion_Estimation_from_Raw_MoCap_Data.pdf	Published version	513.64 kB	Adobe PDF	View/Open

Copyright Clearance Process

Recently Added
In Progress
Closed Access

This item is closed access and not available.

Full metadata record

Field	Value	Language
dc.contributor.author	Tang, J
dc.contributor.author	Li, L
dc.contributor.author	Hou, J
dc.contributor.author	Xin, H
dc.contributor.author	Yu, X https://orcid.org/0000-0002-0269-5649
dc.date	2023-03-25
dc.date.accessioned	2024-02-13T07:44:34Z
dc.date.available	2024-02-13T07:44:34Z
dc.date.issued	2023-05-01
dc.identifier.citation	2023 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW), 2023, pp. 767-768
dc.identifier.isbn	9798350348392
dc.identifier.uri	http://hdl.handle.net/10453/175645
dc.description.abstract	Marker based optical motion capture MoCap aims to estimate 3D human motions from a sequence of input raw markers In this paper we propose a divide and conquer strategy based MoCap solving network that accurately retrieves 3D human skeleton motions from raw marker sequences in real time Our core idea is to decompose the task of direct estimation of global human motion from all markers into first solving sub motions of local parts and then aggregating sub motions into a global one to achieve accurate motion estimation
dc.language	en
dc.publisher	IEEE
dc.relation.ispartof	2023 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW)
dc.relation.ispartof	2023 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops
dc.relation.isbasedon	10.1109/vrw58643.2023.00226
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	A Divide-and-conquer Solution to 3D Human Motion Estimation from Raw MoCap Data
dc.type	Conference Proceeding
utslib.location.activity	Shanghai, China
pubs.organisational-group	University of Technology Sydney
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	University of Technology Sydney/Strength - AAII - Australian Artificial Intelligence Institute
utslib.copyright.status	closed_access	*
dc.date.updated	2024-02-13T07:44:33Z
pubs.finish-date	2023-03-29
pubs.publication-status	Published
pubs.start-date	2023-03-25

Abstract:

Marker based optical motion capture MoCap aims to estimate 3D human motions from a sequence of input raw markers In this paper we propose a divide and conquer strategy based MoCap solving network that accurately retrieves 3D human skeleton motions from raw marker sequences in real time Our core idea is to decompose the task of direct estimation of global human motion from all markers into first solving sub motions of local parts and then aggregating sub motions into a global one to achieve accurate motion estimation

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/175645