A swarm intelligence based searching strategy for articulated 3D human body tracking

Simple item page
dc.contributor.authorZhang, X.
dc.contributor.authorHu, W.
dc.contributor.authorWang, X.
dc.contributor.authorKong, Y.
dc.contributor.authorXie, N.
dc.contributor.authorWang, H.
dc.contributor.authorLing, H.
dc.contributor.authorMaybank, S.
dc.contributor.conferenceIEEE Conference on Computer Vision and Pattern Recognition Workshops (2010 : San Francisco, CA)
dc.date.issued2010
dc.description.abstractThis paper proposes an annealed particle swarm optimization based particle filter algorithm for articulated 3D human body tracking. In our algorithm, a sampling covariance and an annealing factor are incorporated into the velocity updating equation of particle swarm optimization (PSO). The sampling covariance and the annealing factor are initiated with appropriate values at the beginning of the PSO iteration, and `annealing' is carried out at reasonable steps. Experiments with multi-camera walking sequences from the Brown dataset show that: 1) the proposed tracker can effectively alleviate the problem of inconsistency between the image likelihood and the true model; 2) the tracker is also robust to noise and body self-occlusion.
dc.description.statementofresponsibilityXiaoqin Zhang, Weiming Hu, Xiangyang Wang, Yu Kong, Nianhua Xie, Hanzi Wang, Haibin Ling, Steve Maybank
dc.identifier.citation2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops, CVPRW 2010: pp.45-50
dc.identifier.doi10.1109/CVPRW.2010.5543804
dc.identifier.isbn9781424470297
dc.identifier.urihttp://hdl.handle.net/2440/64298
dc.language.isoen
dc.publisherIEEE
dc.publisher.placeUSA
dc.rights©2010 IEEE
dc.source.urihttps://doi.org/10.1109/cvprw.2010.5543804
dc.titleA swarm intelligence based searching strategy for articulated 3D human body tracking
dc.typeConference paper
pubs.publication-statusPublished

Files

Collections

Computer Science publications