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Information-theoretic Hashing Of 3d Objects Using Spectral Graph Theory

机译:利用谱图理论对3d对象进行信息论散列

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Identification and authentication of multimedia content has become one of the most important aspects of multimedia security. In this paper, we present a hashing technique for 3D models using spectral graph theory and entropic spanning trees. The main idea is to partition a 3D triangle mesh into an ensemble of sub-meshes, then apply eigen-decomposition to the Laplace-Beltrami matrix of each sub-mesh, followed by computing the hash value of each sub-mesh. This hash value is defined in terms of spectral coefficients and Tsallis entropy estimate. The experimental results on a variety of 3D models demonstrate the effectiveness of the proposed technique in terms of robustness against the most common attacks including Gaussian noise, mesh smoothing, mesh compression, scaling, rotation as well as combinations of these attacks.
机译:多媒体内容的标识和认证已成为多媒体安全性的最重要方面之一。在本文中,我们提出了一种使用频谱图理论和熵生成树的3D模型哈希技术。主要思想是将3D三角形网格划分为一组子网格,然后将特征分解应用于每个子网格的Laplace-Beltrami矩阵,然后计算每个子网格的哈希值。该散列值是根据频谱系数和Tsallis熵估计来定义的。在各种3D模型上的实验结果证明了该技术在针对最常见攻击(包括高斯噪声,网格平滑,网格压缩,缩放,旋转以及这些攻击的组合)的鲁棒性方面的有效性。

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