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

    Zhang, X. and Hu, W. and Wang, X. and Kong, Y. and Xie, N. and Wang, H. and Ling, H. and Maybank, Stephen J. (2010) A swarm intelligence based searching strategy for articulated 3D human body tracking. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2010, 13-18 Jun 2010, San Francisco, U.S..

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    Abstract

    This 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.

    Metadata

    Item Type: Conference or Workshop Item (Paper)
    Keyword(s) / Subject(s): Annealing, Equations, Humans, Image sampling, Legged locomotion, Noise robustness, Particle filters, Particle swarm optimization, Particle tracking, Sampling methods
    School: Birkbeck Faculties and Schools > Faculty of Science > School of Computing and Mathematical Sciences
    Depositing User: Administrator
    Date Deposited: 06 Nov 2012 11:07
    Last Modified: 09 Aug 2023 12:32
    URI: https://eprints.bbk.ac.uk/id/eprint/5566

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