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N-Dimensional Surface Reconstruction From A Noisy Normal Vector Field

M. Donias, Olivier Lavialle, Guillaume Zinck
2012 Zenodo  
CONCLUSION We have developed a method to reconstruct an implicit hypersurface of a N -dimensional vector space from a normal vector field generally supposed to be unreliable and noisy.  ...  Methods to reconstruct a surface from a normal vector field are developed in literature.  ... 
doi:10.5281/zenodo.42961 fatcat:jo4jzepphjc57heojzu74qafmi

Surface-from-Gradients: An Approach Based on Discrete Geometry Processing

Wuyuan Xie, Yunbo Zhang, Charlie C.L. Wang, Ronald C.-K. Chung
2014 2014 IEEE Conference on Computer Vision and Pattern Recognition  
In this paper, we propose an efficient method to reconstruct surface-from-gradients (SfG). Our method is formulated under the framework of discrete geometry processing.  ...  Unlike the existing SfG approaches, we transfer the continuous reconstruction problem into a discrete space and efficiently solve the problem via a sequence of least-square optimization steps.  ...  Mathematically, a gradient field generated from a three-dimensional surface should be integrable -that is the integral along any closed path should be equal to zero and integration results should be independent  ... 
doi:10.1109/cvpr.2014.282 dblp:conf/cvpr/XieZWC14 fatcat:7wwv3cdq5rgkdgby7p2nls3yey

Scatterometer image reconstruction from aperture-filtered samples

Brent A. Williams, David G. Long
2010 2010 IEEE International Geoscience and Remote Sensing Symposium  
A reconstruction estimator based on maximum a posteriori probability (MAP) estimation is proposed to recover the conventional samples from noisy aperture-filtered samples.  ...  Backscatter imaging is approached as the inversion of a noisy aperturefiltered sampling operation.  ...  The σ 0 measurements represent noisy aperture-filtered samples of the two-dimensional σ 0 field.  ... 
doi:10.1109/igarss.2010.5654148 dblp:conf/igarss/WilliamsL10 fatcat:mftiwjwzfzex7jegvzq3nxf7sm

Learning modified indicator functions for surface reconstruction

Dong Xiao, Siyou Lin, Zuoqiang Shi, Bin Wang
2021 Computers & graphics  
Surface reconstruction is a fundamental problem in 3D graphics. In this paper, we propose a learning-based approach for implicit surface reconstruction from raw point clouds without normals.  ...  We design a novel deep neural network to perform surface integral and learn the modified indicator functions from un-oriented and noisy point clouds.  ...  [3, 5] apply a smooth filter to the normal field. Lu et al. [7] utilize a modified Gauss formula to construct a relatively smooth function near the surface.  ... 
doi:10.1016/j.cag.2021.10.017 fatcat:wwgf2ednfvfwfoagiwzf6jkpve

Robust flow field reconstruction from limited measurements via sparse representation [article]

Jared Callaham and Kazuki Maeda and Steven L. Brunton
2019 arXiv   pre-print
In many applications it is important to estimate a fluid flow field from limited and possibly corrupt measurements.  ...  Based on these results, sparse representation is a promising framework for extracting useful information from complex flow fields with realistic measurements.  ...  Acknowledgements We gratefully acknowledge funding support from the Air Force Office of Scientific Research (FA9550-18-1-0200 & FA9550-16-1-0650) and the Army Research Office (W911NF-17-1-0422).  ... 
arXiv:1810.06723v2 fatcat:eq7gdbtjnbh3xkwa2kemdbgmme

SSD: Smooth Signed Distance Surface Reconstruction

F. Calakli, G. Taubin
2011 Computer graphics forum (Print)  
We introduce a new variational formulation for the problem of reconstructing a watertight surface defined by an implicit equation, from a finite set of oriented points; a problem which has attracted a  ...  In addition, rather than first extending the oriented points to a vector field within the bounding volume, and then approximating the vector field by a gradient field in the least squares sense, here the  ...  As a result, the vector field samples are first extended to a continuous three dimensional vector field v(x) defined on the volume V .  ... 
doi:10.1111/j.1467-8659.2011.02058.x fatcat:p47iz37xfnfzfe6bj7xc3kmhx4

Multi-level hermite variational interpolation and quasi-interpolation

Shengjun Liu, Guido Brunnett, Jun Wang
2013 The Visual Computer  
reconstruction, and leads to a fast and stable surface reconstruction from scattered points.  ...  In addition, we present a multilevel quasi-interpolation method which directly uses normal vectors to construct non-zero constraints and avoids solving any linear system, a common step of variational surface  ...  We also thank Michael Kazhdan and Hugues Hoppe for providing their screened Poisson reconstruction implementation, Yutaka Ohtake and his colleagues for providing their multi-level CSRBF reconstruction  ... 
doi:10.1007/s00371-013-0801-9 fatcat:fkb5sq4b7bc4hhub4hqdedrjzm

Poisson Surface Reconstruction [article]

Michael Kazhdan, Matthew Bolitho, Hugues Hoppe
2006 Symposium on geometry processing : [proceedings]. Symposium on Geometry Processing  
We show that surface reconstruction from oriented points can be cast as a spatial Poisson problem.  ...  Experimenting with publicly available scan data, we demonstrate reconstruction of surfaces with greater detail than previously achievable.  ...  The gradient of the smoothed indicator function is equal to the vector field obtained by smoothing the surface normal field: ∇ χ M * F (q 0 ) = ∂ M Fp (q 0 ) N ∂ M (p)d p. (1) Proof: To prove this, we  ... 
doi:10.2312/sgp/sgp06/061-070 fatcat:ggh4a7xxcbahxfh3emcsmpp5au

Surface reconstruction with higher-order smoothness

Rongjiang Pan, Vaclav Skala
2011 The Visual Computer  
This work proposes a method to reconstruct surfaces with higher-order smoothness from noisy 3D measurements.  ...  The key idea is to find a function whose higher-order derivatives are regularized and whose gradient is best aligned with a vector field defined by the input point set.  ...  From the orientations for the data points, a vector field 3 : F R Ω → encoding the normal directions is estimated by a smoothing filter.  ... 
doi:10.1007/s00371-011-0604-9 fatcat:fn344ppnojft5aqpjka47e2pfy

Mesh-based Multi-view Normal Integration with Energy Minimization Using Surface Reflectance Properties

Wichayut Eaksarayut, Pitchaya Sitthi-amorn, Borom Tunwattanapong, Nuttapong Chentanez
2018 Journal of WSCG  
The integration requires normal vector field from multiple viewpoints, which we can derive from surface reflectance.  ...  We propose a technique to reconstruct a general 3D object using surface reflectance information from multiple viewpoints.  ...  [5] introduced a new technique that can reconstructs 3D surface using normal vector information from multiple viewpoints.  ... 
doi:10.24132/jwscg.2018.26.2.3 fatcat:gy4vpyjc4bgsfmvpk42imi4tcq

Surface Recovery: Fusion of Image and Point Cloud

Siavash Hosseinyalamdary, Alper Yilmaz
2015 2015 IEEE International Conference on Computer Vision Workshop (ICCVW)  
In this paper, we propose two surface recovery approaches based on geometry and brightness of the surface.  ...  However, cost-effective laser scanners provide noisy and low resolution point cloud and they are prone to systematic errors.  ...  The brightness changes indicate the changes in normal direction of the surface at these points [26] , such as |I(x) − I(x ′ )| ≃ arccos( n ⊤ X n X ′ ), (7) where n x and n X ′ are normal vectors to the  ... 
doi:10.1109/iccvw.2015.32 dblp:conf/iccvw/Hosseinyalamdary15 fatcat:emkutvwpurapbjwohrw34dnr5i

Neural-IMLS: Learning Implicit Moving Least-Squares for Surface Reconstruction from Unoriented Point Clouds [article]

Zixiong Wang, Pengfei Wang, Qiujie Dong, Junjie Gao, Shuangmin Chen, Shiqing Xin, Changhe Tu, Wenping Wang
2021 arXiv   pre-print
Surface reconstruction from noisy, non-uniform, and unoriented point clouds is a fascinating yet challenging problem in computer vision and graphics.  ...  We prove that when the couple of SDFs coincide, our neural network can predict a signed implicit function whose zero level-set serves as a good approximation to the underlying surface.  ...  We assume that f is an unsigned distance field whose zero-level surface has a 3-dimensional measure (volume) of 0.  ... 
arXiv:2109.04398v2 fatcat:vxgmmptimvhlre5n5nck5dwaoq

3D surface modeling from curves

D TUBI
2004 Image and Vision Computing  
A strategy for updating the reconstructed surface during data acquisition is described as well. Curves are accumulated in a volumetric structure in which a vector field is built and updated.  ...  This paper presents a novel approach for reconstructing a surface from a set of arbitrary, unorganized and intersecting curves.  ...  The reconstructed surface can be extracted from the vector field f (p) using the Marching Cubes algorithm.  ... 
doi:10.1016/s0262-8856(04)00059-9 fatcat:f325yacmtncj7nmljco2jzhhy4

3D surface modeling from curves

Dragan Tubić, Patrick Hébert, Denis Laurendeau
2004 Image and Vision Computing  
A strategy for updating the reconstructed surface during data acquisition is described as well. Curves are accumulated in a volumetric structure in which a vector field is built and updated.  ...  This paper presents a novel approach for reconstructing a surface from a set of arbitrary, unorganized and intersecting curves.  ...  The reconstructed surface can be extracted from the vector field f (p) using the Marching Cubes algorithm.  ... 
doi:10.1016/j.imavis.2004.03.006 fatcat:v2pxix3urrb2voqqed52tjhb64

Reduction of artifacts in dental cone beam CT images to improve the three dimensional image reconstruction

Issa Ibraheem
2012 Journal of Biomedical Science and Engineering  
The modified projection data, using synthetically Radon Transformation, were then used to reconstruct a new back projected CBCT image.  ...  It deals with reconstructed CBCT dicom images and can effectively reduce such metal artifacts.  ...  We can use this fact to determine surface normal vector n if the magnitude of the gradient g is nonzero.  ... 
doi:10.4236/jbise.2012.58052 fatcat:vdhikxrhjnhbhccs52kgvohqre
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