Visibility-Consistent Thin Surface Reconstruction Using Multi-ScaleKernels ś Supplemental Material

SAMIR AROUDJ, PATRICK SEEMANN, FABIAN LANGGUTH,STEFAN GUTHE, and MICHAEL GOESELE, TU Darmstadt, Germany

ACM Reference Format:

Samir Aroudj, Patrick Seemann, Fabian Langguth, Stefan Guthe, and Michael

Goesele. 2017. Visibility-Consistent Thin Surface Reconstruction UsingMulti-

Scale Kernels ś Supplemental Material. ACM Trans. Graph. 36, 6, Article 187

ś Supplemental Material (November 2017), 3 pages.

https://doi.org/10.1145/nnnnnnn.nnnnnnn

This supplemental material demonstrates results not shown in the

main paper. We compare our TSR approach against Poisson Surface

Reconstruction (PSR) [Kazhdan and Hoppe 2013], Floating Scale

Surface Reconstruction (FSSR) [Fuhrmann and Goesele 2014], Point

Fusion (PFS) [Ummenhofer and Brox 2015], Smooth Signed Distance

Surface Reconstruction (SSD) [Calakli and Taubin 2011], Surface Re-

construction from Multi-resolution Points (SURFMRS) [Mücke et al.

2011] and CMPMVS [Jancosek and Pajdla 2011]. Note that we never

cull back faces. Additionally, back faces of colorless reconstructions

are rendered in yellow. All datasets are described in the main paper.

REFERENCESFatih Calakli and Gabriel Taubin. 2011. SSD: Smooth Signed Distance Surface Recon-

struction. CGF 30, 7 (2011).Simon Fuhrmann and Michael Goesele. 2014. Floating Scale Surface Reconstruction.

ACM TOG 33, 4 (2014).Michal Jancosek and Tomás Pajdla. 2011. Multi-View Reconstruction PreservingWeakly-

Supported Surfaces. In CVPR.Michael Kazhdan and Hugues Hoppe. 2013. Screened Poisson Surface Reconstruction.

ACM TOG 32, 3 (2013).Patrick Mücke, Ronny Klowsky, and Michael Goesele. 2011. Surface Reconstruction

from Multi-resolution Sample Points. In VMV.Benjamin Ummenhofer and Thomas Brox. 2015. Global, Dense Multiscale Reconstruc-

tion for a Billion Points. In ICCV.

Received May 2017; revised August 2017; final version September 2017;

accepted September 2017

© 2017 Association for Computing Machinery.This is the author’s version of the work. It is posted here for your personal use. Not forredistribution. The definitive Version of Record was published in ACM Transactions onGraphics, https://doi.org/10.1145/nnnnnnn.nnnnnnn.

(a) Ground Truth (b) FSSR (c) PFS (d) SSD

(e) CMPMVS (f) SURFMRS (g) PSR (h) TSR

-10 10

Fig. 1. For the City scene, our approach is the only one that accurately

reconstructs it.

ACM Transactions on Graphics, Vol. 36, No. 6, Article 187 ś Supplemental Material. Publication date: November 2017.

https://doi.org/10.1145/nnnnnnn.nnnnnnnhttps://doi.org/10.1145/nnnnnnn.nnnnnnn

187 ś Supplemental Material:2 • Aroudj, S. et al

(a) Image (b) Points (c) FSSR (d) PFS (e) PSR (f) SSD (g) CMPMVS (h) TSR

Fig. 2. Shelltower front side views comparison. There is a clear trade-off between well supported thin structures not being reconstructed (FSSR and CMPMVS)

vs. hallucinated geometry (PFS, PSR and SSD). Only TSR reconstructs thin structures without adding hallucinated geometry.

(a) Image (b) Points (c) FSSR (d) PFS (e) PSR (f) SSD (g) CMPMVS (h) TSR

Fig. 3. Shell closeups from Fig. 2. TSR is the only one reconstructing it without holes (CMPMVS) or hallucinated geometry (FSSR, PFS, PSR, SSD).

(a) Image (b) Points (c) PFS (d) PSR (e) SSD (f) FSSR (g) CMPMVS (h) TSR

Fig. 4. Orchid comparison. The top row shows the front with vertex colors while the bottom row shows the back without vertex colors. The renderings with

colors emphasize the quality of the TSR reconstruction compared to all other results, especially when looking at the leaves towards the bottom of the plant.

ACM Transactions on Graphics, Vol. 36, No. 6, Article 187 ś Supplemental Material. Publication date: November 2017.

Visibility-Consistent Thin Surface Reconstruction Using Multi-Scale Kernels ś Supplemental Material • 187 ś Supplemental Material:3

σ = 0.05 σ = 0.1 σ = 0.15 σ = 0.2 σ = 0.25 σ = 0.3 σ = 0.35

Fig. 5. Robustness experiment using input point clouds (top) of the synthetic wedge with varying noise and corresponding TSR reconstructions (bottom).

Point clouds were generated with increasing noise (√d · N(0, σ )) using ray traced depth maps of the wedge.

Noise-free

Noisy(σ=0.05)

Points Crust i = 1 i = 2 i = 3 i = 4 i = 10

Fig. 6. Progress for the synthetic wedge (expanded version of Fig. 5 in the main paper). Note that the refinement quickly reduces surface errors. Sharp features

become more accurate with each iteration. However, their quality improves slower than the quality of other surface parts.

ACM Transactions on Graphics, Vol. 36, No. 6, Article 187 ś Supplemental Material. Publication date: November 2017.

References