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    题名: A Robust Normalization Algorithm for Three Dimensional Models Based on Clustering and Star Topology
    作者: 劉正忠
    贡献者: 電子工程(學)系
    日期: 2011-10
    上传时间: 2017-11-23 09:31:02 (UTC+8)
    摘要: Recently, the fast growth of 3D models has pushed people to develop efficient 3D model registration, recognition, retrieval and watermarking techniques. However, the poses and sizes of the same 3D model may be represented differently from file to file. In order to minimize these differences and simplify the complexity for 3D model registration, recognition, retrieval and watermarking, each 3D model must be normalized. This paper combines the 3D model calibration scheme, clustering scheme and star topology scheme to embed the normalization information of a model in the original model. Experimental results show that the proposed algorithm is effective and efficient in 3D model normalization and has the following advantages: (a) each vertex of a compound 3D model can be traversed due to using the clustering scheme; (b) the correct rate of extracting the normalization information is very high because it utilizes three verification codes to do triple verifications of the extracted normalization information; (c) the signal-to-noise-ratio (SNR) between the embedded model and the original model is very high and the distortion very small; (d) it is 100 % robust against the combination of affine transformations due to the fact that the normalization information is embedded in angles of meshes; (e) it is excellent at keeping robust against the cropping attack, because the embedded feature triangular meshes are uniformly and separately distributed on the model and it only needs three embedded feature triangular meshes to offer normalization information to normalize the cropped model. © ICIC International 2011. (24 refs)
    關聯: International Journal of Innovative Computing, Information and Control.
    显示于类别:[電子工程系(所)] 【電子工程系所】期刊論文

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