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    政大機構典藏 > 理學院 > 資訊科學系 > 期刊論文 >  Item 140.119/75279
    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/75279

    Title: Robust trifocal tensor constraints for structure from motion estimation
    Authors: Hor, Maw-Kae
    Chan, Kai-Hsuan
    Tang, C.-Y.
    Wu, Y.-L.
    Contributors: 資科系
    Keywords: Accurate estimation;Camera parameter;Estimation errors;Global optimization problems;Ground truth data;Multi-view stereo;Optimization solution;Orthogonal array;Reprojection error;Structure from motion;Trifocal tensor;Cameras;Errors;Estimation;Motion estimation;Particle swarm optimization (PSO);Pixels;Tensors;Parameter estimation
    Date: 2013
    Issue Date: 2015-05-21 17:25:31 (UTC+8)
    Abstract: It is important to estimate accurate camera parameters in multi-view stereo. In this paper, we use three-view relations, the trifocal tensor, to improve the Bundler, a popular structure from motion (SfM) system, for estimating accurate camera parameters. We propose a novel method: the Robust Orthogonal Particle Swarm Optimization (ROPSO) to estimate a robust and accurate trifocal tensor. In ROPSO, we formulate the trifocal tensor estimation as a global optimization problem and use the particle swarm optimization (PSO) for parameter searching. The orthogonal array is used to select the representative initial particles in PSO for more stable results. In the experiments, we use simulated and real ground truth data for statistical analysis. The experimental results show that the proposed ROPSO can achieve more accurate estimation of the trifocal tensor than the traditional methods and has higher probability to find the optimization solution than the traditional methods. Based on the trifocal tensor estimated by the proposed method, the SfM estimation errors can effectively be reduced. The average reprojection errors are reduced from 21.5 pixels to less than 1 pixel. © 2013 Elsevier B.V. All rights reserved.
    Relation: Pattern Recognition Letters, 34(6), 627-636
    Data Type: article
    DOI 連結: http://dx.doi.org/10.1016/j.patrec.2012.12.023
    DOI: 10.1016/j.patrec.2012.12.023
    Appears in Collections:[資訊科學系] 期刊論文

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