Authors: Yue Jingya
Addresses: Zhengzhou University of Aeronautics, Zhengzhou Henan, 450046, China
Abstract: 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.
Keywords: 3D vessel model; geometric reconstruction; MeTiS meshing; Bayes; neighbour node.
International Journal of Innovative Computing and Applications, 2020 Vol.11 No.2/3, pp.123 - 130
Received: 01 Mar 2019
Accepted: 29 Apr 2019
Published online: 30 Apr 2020 *