Multi-view Human Motion Capture with An Improved Deformation Skin Model
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Altmetric Citations
Lu, Yifan; Wang, Lei; Hartley, Richard; Li, Hongdong; Shen, Chunhua
Description
Markerless human motion capture has received much attention in computer vision and computer graphics communities. A hierarchical skeleton template is frequently used to model the human body in literature, because it simplifies markerless human motion capture as a problem of estimating the human body shape and joint angle parameters. The proposed work establishes a skeleton based markerless human motion capture framework, comprising of 1) an improved deformation skin model suitable for...[Show more]
dc.contributor.author | Lu, Yifan | |
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dc.contributor.author | Wang, Lei | |
dc.contributor.author | Hartley, Richard | |
dc.contributor.author | Li, Hongdong | |
dc.contributor.author | Shen, Chunhua | |
dc.coverage.spatial | Canberra Australia | |
dc.date.accessioned | 2015-12-08T22:34:03Z | |
dc.date.created | December 1-3 2008 | |
dc.identifier.isbn | 9780769534565 | |
dc.identifier.uri | http://hdl.handle.net/1885/34904 | |
dc.description.abstract | Markerless human motion capture has received much attention in computer vision and computer graphics communities. A hierarchical skeleton template is frequently used to model the human body in literature, because it simplifies markerless human motion capture as a problem of estimating the human body shape and joint angle parameters. The proposed work establishes a skeleton based markerless human motion capture framework, comprising of 1) an improved deformation skin model suitable for markerless motion capture while it is compliant with the computer animation standard, 2) image segmentation by using Gaussian mixture static background subtraction and 3) non-linear dynamic temporal tracking with Annealed Particle Filter. This framework is able to efficiently represent markerless human motion capture as an optimisation problem in the temporal domain and solve it by the classic optimisation scheme. Several experiments are used to illustrate its robustness and accuracy comparing with the existing approach. | |
dc.publisher | Institute of Electrical and Electronics Engineers (IEEE Inc) | |
dc.relation.ispartofseries | Digital Image Computing: Techniques and Applications (DICTA 2008) | |
dc.source | Proceedings of Digital Image Computing: Techniques and Applications (DICTA 2008) | |
dc.subject | Keywords: Annealed particle filters; Computer animation; Gaussian mixtures; Human bodies; Human motion capture; Joint angle; Markerless; Markerless motion capture; Multi-view; Non-linear dynamics; Optimisation; Skin model; Static background; Temporal domain; Comput | |
dc.title | Multi-view Human Motion Capture with An Improved Deformation Skin Model | |
dc.type | Conference paper | |
local.description.notes | Imported from ARIES | |
local.description.refereed | Yes | |
dc.date.issued | 2008 | |
local.identifier.absfor | 080106 - Image Processing | |
local.identifier.absfor | 080104 - Computer Vision | |
local.identifier.ariespublication | u4334215xPUB118 | |
local.type.status | Published Version | |
local.contributor.affiliation | Lu, Yifan, College of Engineering and Computer Science, ANU | |
local.contributor.affiliation | Wang, Lei, College of Engineering and Computer Science, ANU | |
local.contributor.affiliation | Hartley, Richard, College of Engineering and Computer Science, ANU | |
local.contributor.affiliation | Li, Hongdong, College of Engineering and Computer Science, ANU | |
local.contributor.affiliation | Shen, Chunhua, College of Engineering and Computer Science, ANU | |
local.description.embargo | 2037-12-31 | |
local.bibliographicCitation.startpage | 420 | |
local.bibliographicCitation.lastpage | 427 | |
local.identifier.doi | 10.1109/DICTA.2008.14 | |
dc.date.updated | 2016-02-24T10:57:55Z | |
local.identifier.scopusID | 2-s2.0-67549125047 | |
Collections | ANU Research Publications |
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