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  • 标题:3D部分形状の融合による全体形状の復元と精度向上
  • 本地全文:下载
  • 作者:Joon Bo Shim ; Yoshinori Takeuchi ; Toshiharu Mukai
  • 期刊名称:映像情報メディア学会誌
  • 印刷版ISSN:1342-6907
  • 电子版ISSN:1881-6908
  • 出版年度:2001
  • 卷号:55
  • 期号:11
  • 页码:1479-1490
  • DOI:10.3169/itej.55.1479
  • 出版社:The Institute of Image Information and Television Engineers
  • 摘要:We describe a novel approach for recovering an exact 3D whole model using image sequences. To recover a whole shape, more than two images should be used, which is convenient to avoid problems such as inclusion of noise and self occlusion. We present the methods of fusion and integration of 3D shapes. The fusion process indicates that 3D partial shapes in the same viewpoint set are fused sequentially to improve accuracy. The integration process indicates that refined partial shapes by the fusion process in each viewpoint set are integrated to construct the whole shape with high accuracy. The novel iterative orthonormal fitting transform method (IOFTM) is utilized to transform the shapes' coordinate system to the standard one. IOFTM is compared with the steepest descent method. We fuse shapes by the point-weighted fusion method. The whole shape is constructed by the integration of partial shapes' points which are at lower noise level between corresponding feature points. The system is divided into five stages : first, reconstruction of partial shapes at different camera positions, second, fusion of the partial shapes to obtain a para-ideal shape by the uniform-weighted fusion method, third, detection of the outlier shapes and feature points based on evaluation function, fourth, fusion of shapes by the point-weighted fusion method, and fifth, integration of accurate partial shapes to construct the refined whole shape. Experimental results indicate that our system performs well in removing noise with robustness. The noise reduction rates are 85.8%-97.4% in the simulation and real image experiments, respectively.
  • 关键词:Multiple Viewpoints;Iterative Orthonormal Fitting Transform Method (IOFTM);Point-Weighted Fusion;Evaluation Function;Outlier
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