基于MeTis网格的Bayes三维船模几何重建

Yue Jingya
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引用次数: 0

摘要

为了提高三维模型几何重构过程的压缩效率,提出了一种基于MeTiS网格的Bayes三维船模几何重构算法。编码端采用MeTiS方法对原始三维网格进行子网划分,子网的几何形状采用随机线性矩阵进行编码,并利用伪随机数生成器考虑边界节点的相邻节点构造数据序列;然后利用贝叶斯算法设计几何模型重构算法,从理论上给出了均值、方差矩阵和模型参数的学习规则,实现了三维模型的几何重构;最后,在三维模型标准测试库和三维船舶模型上,与GFT、LSM和CSGFT等算法进行仿真比较,表明本文方法具有较高的比特率压缩指数和较低的重构误差,显著提高了计算效率。
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MeTis meshing-based Bayes 3D ship model geometry reconstruction
In order to improve the compression efficiency of 3D model geometry reconstruction process, a MeTiS meshing-based Bayes 3D ship model geometry reconstruction algorithm is proposed. The original 3D mesh is subnetted by the MeTiS method at the coding end, and the geometrical shape of the subnet is coded by a random linear matrix, and the neighbour node of the boundary node is considered to construct the data sequence by the pseudo random number generator; then the Bayes algorithm is used to design the geometric model reconstruction algorithm, and the learning rules for the mean, variance matrix and model parameter are theoretically given, realising the geometric reconstruction of 3D model; finally, on the 3D model standard test library and 3D ship model, the simulation comparison with the GFT, LSM and CSGFT and other algorithms show that the proposed method has a relatively high bit rate compression index and a low reconstruction error, leading to significantly improved computational efficiency.
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来源期刊
CiteScore
1.40
自引率
0.00%
发文量
23
期刊介绍: IJICA proposes and fosters discussion on all new computing paradigms and corresponding applications to solve real-world problems. It will cover all aspects related to evolutionary computation, quantum-inspired computing, swarm-based computing, neuro-computing, DNA computing and fuzzy computing, as well as other new computing paradigms
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