三维网格客观质量评价 
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Objective Quality Assessment for Three-Dimensional Meshes
1 宁波大学信息科学与工程学院, 浙江 宁波 315211
2 南京大学计算机软件新技术国家重点实验室, 江苏 南京 210093
图 & 表
图 1. LIRIS/EPFL general-purpose原始三维网格。(a) Armadillo;(b) Venus;(c) Dinosaur;(d) Rockerarm
Fig. 1. Original 3D meshes of LIRIS/EPFL general-purpose. (a) Armadillo;(b) Venus;(c) Dinosaur;(d) Rockerarm
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图 2. LIRIS_Mask原始三维网格。(a) Armadillo;(b) Dinosaur;(c) Lion Head;(d) Bimba
Fig. 2. Original 3D meshes of LIRIS_Mask. (a) Armadillo;(b) Dinosaur;(c) Lion Head;(d) Bimba
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表 1全参考三维网格客观质量评价方法
Table1. FR 3D mesh objective quality assessment method
| Type | Principle | Method |
|---|
| FR | Geometric distance | HD[20], RMS[21] | | Geometric Laplacian | GL1[22], GL2[23] | | Network structure | MSDM[14] | | Multi-scale/structure | MSDM2[24] | | Dihedral angle | DAME[25] | | Curvature | TPDM[26], Dong[27] |
|
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表 2半参考三维网格客观质量评价方法
Table2. RR 3D mesh objective quality assessment method
| Type | Principle | Method |
|---|
| RR | Global roughness | 3DWPM1[28], 3DWPM2[29] | | Local roughness | FMPD[30] | | Statistical distribution/Dihedral angle | KLD Gamma[31]KLD Weibull[31] |
|
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表 3无参考三维网格客观质量评价方法
Table3. NR 3D mesh objective quality assessment method
| Type | Principle | Method |
|---|
| NR | Statistical distribution/Dihedral angle | NR-SVR[32] | | Mean curvature/Dihedral angle | NR-SVR[33] | | Dihedral angle | NR-SVR[11] | | Shape index/Curvedness/Vertex scatter/Area | NR-SVR[34] | | Graph spectral features/Spatial features | BMQA-GSES[35] |
|
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表 4不同方法在LIRIS/EPFL general-purpose数据库上的性能比较
Table4. Performance comparison of different methods on LIRIS/EPFL general-purpose database
| Type | Method | PLCC /% | SROCC /% |
|---|
| FR | HD[20] | 11.4 | 13.8 | | RMS[21] | 28.1 | 26.8 | | GL1[22] | 35.5 | 33.1 | | GL2[23] | 42.4 | 39.3 | | MSDM[14] | 75.0 | 73.9 | | MSDM2[24] | 81.4 | 80.4 | | DAME[25] | 75.2 | 76.6 | | TPDM[26] | 84.1 | 80.4 | | Dong[27] | 87.7 | 86.6 | | RR | 3DWPM1[28] | 61.8 | 69.3 | | 3DWPM2[29] | 49.6 | 49.0 | | FMPD[30] | 83.5 | 81.9 | | KLD Gamma[31] | 74.0 | 71.6 | | KLD Weibull[31] | 74.1 | 71.7 | | NR | NR-SVR[32] | 87.8 | 81.5 | | NR-SVR[33] | 82.7 | 83.6 | | NR-SVR[11] | 86.8 | 84.6 | | NR-SVR[34] | 87.8 | 81.9 | | BMQA-GSES[35] | 90.5 | 87.9 |
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表 5不同方法在LIRIS_Mask数据库上的性能比较
Table5. Performance comparison of different methods on LIRIS_Mask database
| Type | Method | PLCC /% | SROCC /% |
|---|
| FR | HD[20] | 20.2 | 26.6 | | RMS[21] | 41.2 | 48.8 | | GL1[22] | 39.6 | 42.0 | | GL2[23] | 38.3 | 40.1 | | MSDM[14] | 69.2 | 65.2 | | MSDM2[24] | 87.3 | 89.6 | | DAME[25] | 58.6 | 68.1 | | TPDM[26] | 88.6 | 90.0 | | Dong[27] | 92.6 | 92.5 | | RR | 3DWPM1[28] | 31.9 | 29.4 | | 3DWPM2[29] | 42.7 | 37.4 | | FMPD[30] | 80.8 | 80.2 | | KLD Gamma[31] | 64.0 | 74.3 | | KLD Weibull[31] | 74.6 | 66.6 | | NR | NR-SVR[32] | 91.2 | 90.4 | | NR-SVR[33] | 85.4 | 88.2 | | NR-SVR[11] | 89.1 | 91.1 | | NR-SVR[34] | 90.1 | 60.0 |
|
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林瑶瑶, 郁梅, 何周燕, 蒋刚毅. 三维网格客观质量评价[J]. 激光与光电子学进展, 2021, 58(2): 0200003. Yaoyao Lin, Mei Yu, Zhouyan He, Gangyi Jiang. Objective Quality Assessment for Three-Dimensional Meshes[J]. Laser & Optoelectronics Progress, 2021, 58(2): 0200003.
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