TY - GEN
T1 - Line-Based Structure for Voxel Model
AU - Jiangxin, Fan
AU - Shikai, Jing
AU - Lei, Che
AU - Tianren, Liu
AU - Zefang, Shi
AU - Zhijun, He
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021/4/23
Y1 - 2021/4/23
N2 - The voxel model discretizes the solid model with voxels, and can represent the local physical properties of the model such as materials, colors, and materials. For the problem of having low operation efficiency and taking up a lot of storage space caused by the huge amount of voxel model data, this paper proposes a Line-Based Structure for the voxel model. In this structure, the voxel model is treated as an ordered set of Lines, which is formed of voxels. It builds the correlation of independent voxels. Based on this structure, this paper achieves a voxel batch operation method and proposed voxel data fast indexing function, improving the operation efficiency of the voxel model. Then using the state of each position in the space to represent whether the voxel exists in that position, the voxel model data compressing and decompressing methods are proposed. This achieves effective compression of large data voxel models and provides a quick preview function of the model, reducing the voxel model storage space. The effect of the method in this paper is verified through experiments.
AB - The voxel model discretizes the solid model with voxels, and can represent the local physical properties of the model such as materials, colors, and materials. For the problem of having low operation efficiency and taking up a lot of storage space caused by the huge amount of voxel model data, this paper proposes a Line-Based Structure for the voxel model. In this structure, the voxel model is treated as an ordered set of Lines, which is formed of voxels. It builds the correlation of independent voxels. Based on this structure, this paper achieves a voxel batch operation method and proposed voxel data fast indexing function, improving the operation efficiency of the voxel model. Then using the state of each position in the space to represent whether the voxel exists in that position, the voxel model data compressing and decompressing methods are proposed. This achieves effective compression of large data voxel models and provides a quick preview function of the model, reducing the voxel model storage space. The effect of the method in this paper is verified through experiments.
KW - Line-Based Structure
KW - compression
KW - data structure
KW - index
KW - voxel model
UR - http://www.scopus.com/inward/record.url?scp=85107554124&partnerID=8YFLogxK
U2 - 10.1109/ICIEA52957.2021.9436759
DO - 10.1109/ICIEA52957.2021.9436759
M3 - Conference contribution
AN - SCOPUS:85107554124
T3 - 2021 IEEE 8th International Conference on Industrial Engineering and Applications, ICIEA 2021
SP - 522
EP - 528
BT - 2021 IEEE 8th International Conference on Industrial Engineering and Applications, ICIEA 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 8th IEEE International Conference on Industrial Engineering and Applications, ICIEA 2021
Y2 - 23 April 2021 through 26 April 2021
ER -