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    Nonrigid structure-from-motion from 2-d images using Markov Chain Monte Carlo

    Zhou, H. and Li, Xuelong and Sadka, Abdul H. (2012) Nonrigid structure-from-motion from 2-d images using Markov Chain Monte Carlo. IEEE Transactions on Multimedia 14 (1), pp. 168-177. ISSN 1520-9210.

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    In this paper we present a new method for simultaneously determining 3-D shape and motion of a nonrigid object from uncalibrated 2-D images without assuming the distribution characteristics. A nonrigid motion can be treated as a combination of a rigid rotation and a nonrigid deformation. To seek accurate recovery of deformable structures, we estimate the probability distribution function of the corresponding features through random sampling, incorporating an established probabilistic model. The fitting between the observation and the projection of the estimated 3-D structure will be evaluated using a Markov chain Monte Carlo based expectation maximization algorithm. Applications of the proposed method to both synthetic and real image sequences are demonstrated with promising results.


    Item Type: Article
    School: School of Business, Economics & Informatics > Computer Science and Information Systems
    Depositing User: Sarah Hall
    Date Deposited: 07 Jun 2013 08:19
    Last Modified: 11 Oct 2016 15:27


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