Point set surfaces

By Marc Alexa, Johannes Behr, Daniel Cohen-Or, Shachar Fleishman, David Levin, Cláudio T. Silva. Proceedings Visualization, 2001. VIS '01., 2001

892 citations recorded by the source corpus.

Subfields: Computational Mechanics, Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/116330dd43db80853ffde828100854d89b8916aa

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computational Mechanics

1. Daniel Cohen-Or
2. Markus H. Gross
3. Leif Kobbelt
4. Niloy J. Mitra
5. Leonidas J. Guibas
6. Olga Sorkine-Hornung
7. Mark Pauly
8. Cláudio T. Silva

In Computer Graphics and Computer-Aided Design

1. Daniel Cohen-Or
2. Markus H. Gross
3. Leif Kobbelt
4. Niloy J. Mitra
5. Mark Pauly
6. Leonidas J. Guibas
7. Olga Sorkine-Hornung
8. Cláudio T. Silva

In Computer Vision and Pattern Recognition

1. Luc Van Gool
2. Daniel Cohen-Or
3. Ming-Hsuan Yang
4. Jitendra Malik
5. Leonidas J. Guibas
6. Dacheng Tao
7. Xiaogang Wang
8. Trevor Darrell

Citations in the corpus

• Multi‐scale Feature Extraction on Point‐Sampled Surfaces (2003, background): “To display such models, numerous point-based rendering systems have been developed, e.g., [20, 21, 25, 1].”
• Shape modeling with point-sampled geometry (2003, methodology): “The projection of onto is then given as (for more details see [Alexa et al. 2001]).”
• Pointshop 3D: an interactive system for point-based surface editing (2002, methodology): “Our approach is similar in spirit to the construction of point set surfaces introduced in [Alexa 2001], in that both methods use local parameterizations and polynomials to approximate the surface.”
• Parallel Poisson Surface Reconstruction (2009, methodology): “For function continuity, the influence of several nearby points can be blended together, for instance using moving least squares [15, 16].”
• Provable surface reconstruction from noisy samples (2004, methodology): “A number of algorithms, though not with any theoretical guarantees, have been proposed for the problem [1,6,7,18,20,21].”
• Computing and Rendering Point Set Surfaces (2003, methodology): “In addition to giving more implementation details for the rendering method from [1], we give a justification that builds on the error bounds introduced here.”
• 1 An End-to-End Framework for Evaluating Surface Reconstruction (2011, methodology): “2008], to locally fitting functions and moving least squares methods [Alexa et al. 2001; Ohtake et al. 2003; Ohtake et al. 2005b; Fleishman et al. 2005].”
• Interpolating and approximating implicit surfaces from polygon soup (2004, methodology): “The moving least-squares method has been used by other researchers to define a surface as the fixed-point of an iterative parametric fit procedure—for example, see [Alexa et al., 2001].”
• Fusion of depth maps with multiple scales (2011, background): “It is worth noting that Point Set Surfaces [Alexa et al. 2001] based on Moving Least Squares [Levin 1998] can produce implicit functions, which can be evaluated over a hierarchy with respect to approximation error, the local feature size, or even local scale information.”
• A review of algorithms for filtering the 3D point cloud (2017, positive): “Alexa handled noise problem by iteratively projecting the points onto the MLS surface [19,60] defined by two steps (see Fig.”