3D low-poly mesh generation for building models

doi:10.11996/JG.j.2095-302X.2023040764

Abstract

Abstract:

Within the domain of 3D virtual scenes, the usage of low-poly meshes (meshes comprised of few triangles) used in levels of detail play a pivotal role in improving the efficiency of real-time rendering. However, given detailed building models (high-poly meshes), it is difficult for the low-poly meshes generated by the existing methods to maintain good visual similarity with the high-poly meshes while achieving extremely low simplification rates, requiring the manual correction of defects. We proposed a novel method in which the user only needed to provide a few robust parameters to generate low-poly building meshes with good visual similarity and satisfying benign geometric properties such as watertightness and two-manifold. Firstly, new meshes were morphed by inverse rendering, enabling the capture of important geometric features from the high-poly meshes, so that they could have similar appearances to the high-poly meshes and retain only the large-scale appearance features. Additionally, to maintain the consistency of the mesh topology during the morphing process, we leveraged the outer hull of the voxelized high-poly meshes as the initialization of the new meshes. Secondly, to address the intersecting triangles that arose during the morphing process, we designed the alpha wrapping algorithm with topology-adaptive parameters. The algorithm ensured that the genus of the outer hull of the voxelized morphed meshes and the genus of the results remained the same, generating approximate meshes from the morphed meshes with no intersecting triangles, satisfying watertightness and two-manifold. Finally, an improved edge collapse algorithm was applied and generated meshes that were simplified to users’ target facet count. The algorithm optimized the contraction of vertex pairs on planes. We evaluated our method’s robustness and effectiveness against a dataset of building models and compared it against popular and state-of-the-art methods.

Key words: mesh simplification, triangle mesh, low-poly mesh generation, level of detail, building model

CLC Number:

TP391

YUE Ming-yu, GAO Xi-feng, BI Chong-ke. 3D low-poly mesh generation for building models[J]. Journal of Graphics, 2023, 44(4): 764-774.

Figures/Tables 7

Fig. 1 A high-poly mesh and simplified results generated by different methods ((a) The high-poly mesh with 10 081 triangles; (b) QEM with 402 triangles; (c) Simplygon with 402 triangles; (d) Our method with 290 triangles)

Fig. 2 An overview of our method ((a) The original model, also the reference mesh of the inverse rendering framework; (b) The base mesh of the inverse rendering framework, also the outer hull of the voxelized original model; (c) The mesh after being morphed; (d) The outer hull of the voxelized morphed model; (e) The mesh generated by alpha wrapping algorithm; (f) The simplified mesh)

Fig. 3 Comparison between different initial base meshes and the morphed results obtained from them ((a) The sphere mesh; (b) The mesh morphed from the sphere; (c) The outer hull of the voxelized mesh; (d) The mesh morphed from the outer hull)

Fig. 4 The result of the different values of ?? ((a) The outer hull of the voxelized morphed mesh; (b) The result with α=d/190 & δ=d/10000, and the genus is 8; (c) The result with α=d/200 & δ=d/10000, and the genus is 10; (d) The result with α=d/210 & δ=d/10000, and the genus is 10. d is the diagonal length of the bounding box of the mesh)

Fig. 5 The comparison between results, and the data under each mesh indicate the number of triangular facets, the simplification rate and the similarity error, respectively ((a) Input; (b) QEM; (c) PolyFit; (d) Simplygon reduction; (e) Simplygon remeshing; (f) Ours)

Table 1 Statistics of results on the whole data set

方法	W(%)	M(%)	$\text{N}_{\text{F}}^{\text{avg}}$	r^avg	e^avg
输入	0	11.54	17557	-	-
QEM	3.85	26.92	85	0.015 5	2805
PolyFit	0	76.92	328	0.051 1	2024
Simplygon reduction	0	0	701	0.039 8	764
Simplygon remeshing	100	100	85	0.015 7	654
Ours	100	100	85	0.015 7	485

Fig. 6 Our results are compared with those of Simplygon remeshing at different resolutions

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