Winter Term 2017

CSC2521 [Topics in Computer Graphics: Geometry Processing]

Prof. Alec Jacobson

W 3–5 BA 5187 (via BA 5166)

The class is aimed at preparing students for working with geometric data via
understanding fundamental theoretical concepts. Students should have a
background in *Linear Algebra* and *Computer Programming*. Previous
experience with *Numerical Methods*, *Differential Equations*, and *Differential
Geometry* is appreciated but not required.

Extending traditional signal processing, *geometry processing* interprets
three-dimensional curves and surfaces as signals. Just as audio and image
signal data can be filtered, denoised and decomposed spectrally, so can the
geometry of a three-dimensional curve or surface.

In this course, we study the algorithms and mathematics behind fundamental operations for interpreting and manipulating geometric data. These essential tools enable: geometric modeling for computer aided design, life-like animations for computer graphics, reliable physical simulations, and robust scene representations for computer vision.

Topics include: discrete curves and surfaces, curvature computation, surface reconstruction from point clouds, surface smoothing and denoising, mesh simplification, parameterization, symmetry detection, shape deformation and animation.

In lecture we will cover the mathematical background and visual intuition of
the week’s topic. At home, students will ** read academic papers** and complete a
small

- Students should understand, derive, and implement solutions to the prominent challenges that arise in geometry processing applications.
- Students should create a final creative project showcasing their implementation of the different processing algorithms.
- Students should develop an understanding of the mathematical underpinnings of geometry processing including useful discretized operators and energies.
- Students should develop a working knowledge of libigl to develop these algorithms without worrying about the grunt-work of OpenGL viewers, quadrature, etc.

Students should have already taken **Linear Algebra** and **Calculus**.

Students should have already taken **Introduction to Computer Science** and
should be *proficient* in computer programming (in any language) and should
feel comfortable programming in **C++**.

While knowledge of **Partial Differential Equations** *is not required*, it will
certainly be very handy for derivations. A quick survey will be posted to help
students evaluate their readiness on these topics.

On the programming side, we will be coding mainly in **C++** and using a
libigl, an open-source geometry processing
library. We will be using Eigen for computational
linear algebra, and Cmake for building the coding
assignments.

Much of the framing for our techniques will be looking at the continuous analogue of our problem and discretizing it in an intrinsic way, preserving continuous theorems as much as possible. We will discretize continuous operators like the Laplacian and the Gradient, and we will find adequate representations of concepts like normal vectors and curvature. Perhaps surprisingly we will see that there are many choices of discretization, each with their own benefits and downsides, prompting us to choose appropriately for the particular application.

Lecture Date | Tentative Topic |
---|---|

Wednesday, 11/01/2017 | Geometry Processing Pipeline, shapes, surface representations, tangents and normals, Polygon Mesh Processing [Botsch et al. 2008] HW 00 assigned, due 17/01/2017 |

Wednesday, 18/01/2017 | Acquisition & reconstruction, discrete topology, meshes, characteristic function, scattered data interpolation, spatial gradient, “Poisson surface reconstruction” [Kazhdan et al. 2006] HW 01 assigned due 29/01/2017 |

Wednesday, 25/01/2017 | Alignment & registration Hausdorff distance, point-to-plane distance, iterative closest point, orthogonal Procrustes problem, sampling points on surfaces “Object modelling by registration of multiple range images” [Chen & Medioni 1991] “A method for registration of 3-D shapes” [Besl & McKay 1992] “Efficient Variants of the ICP Algorithm” [Rusinkiewicz & Levoy 2001] “Sparse Iterative Closest Point” [Bouaziz et al. 2013] HW 02 assigned due 5/2/2017 |

Wednesday, 01/02/2017 | Alignment & registration continued, Surface fairing & denoising, 1D smoothing flow, 1D energy-based smoothing, PDE, Implicit Time integrationDiscrete Differential Geometry “Forum” “Curve and surface smoothing without shrinkage” [Taubin 1995] “Skeleton extraction by mesh contraction” [Au et al. 2008] “Can Mean-Curvature Flow Be Made Non-Singular” [Kazhdan et al. 2005] HW 03 assigned due 13/2/2016 |

Wednesday, 08/02/2017 | Surface parameterization, Guest lecture by Ryan Schmidt, texture mapping, mass-spring methods, graph drawing, harmonic maps, least squares conformal mapping, local parameterization, discrete exponential map, stroke parameterization “Intrinsic parameterizations of surface meshes” [Desbrun et al. 2002] “Least squares conformal maps for automatic texture atlas generation” [Lévy et al. 2002] “Spectral conformal parameterization” [Mullen et al. 2008] |

Wednesday, 15/02/2017 | Smoothing continued, Spatial Laplacian, calculus of variations, Green’s Identity HW 04 assigned, due 28/2/2017 |

Wednesday, 22/02/2017 | Retroactively decided that this is Reading Week, Surface parameterization continued, role of trace in quadratic energies, minimizing quadratic energies in libigl |

Wednesday, 01/03/2017 | Shape deformation, continuous deformation, pointwise mappings, energy-based model, handle-based deformation, local distortion mesure, gradient-based distortion, Laplacian-based distortion, as-rigid-as-possible “An intuitive framework for real-time freeform modeling” [Botsch & Kobbelt 2004] “On linear variational surface deformation methods” [Botsch & Sorkine 2008] “As-rigid-as-possible surface modeling” [Sorkine & Alexa 2007] “Bounded Biharmonic Weights for Real-Time Deformation” [Jacobson et al. 2010] HW 05 assigned due 12/3/2017 |

Wednesday, 08/03/2017 | Curvature & surface analysis Planar curves, tangents, arc-length parameterization, osculating circle, curvature, turning number theorem, discrete curvature, normal curvature, minimum/maximum/mean curvature Elementary Differential Geometry, [Barret O’Neill 1966 Discrete Differential Geometry: An Applied Introduction, SIGGRAPH Course, [Grinspun et al. 2005] |

Wednesday, 15/03/2017 | Curvature continued Principal curvature, Gauss map, Euler’s theorem, shape operator, Gaussian curvature “Computing Discrete Minimal Surfaces and Their Conjugates” [Pinkall and Polthier 1993] “Gaussian Curvature and Shell Structures” [Calladine 1986] “Discrete differential-geometry operators for triangulated 2-manifolds” [Meyer et al. 2002] HW 06 assigned, due 22/3/2017 |

Wednesday, 22/03/2017 | 3D printing, guest lecture by Nobuyuki Umetani |

Wednesday, 29/03/2017 | Signed distances, constructive solid geometry, voxelization |

Wednesday, 05/04/2017 | Final project presentations |

Cutting room floor:

Mesh decimation, simplification, remeshing,Quad meshing,Subdivision surfaces

0.007% off for every minute late.

*Polygon Mesh
Processing*.
Mario Botsch, Leif Kobbelt, Mark Pauly, Pierre Alliez, and Bruno Levy, 2008.

- 50% small assignments
- 25% final project:
- in-class presentation
- formal two-page technical extended abstract
- (less formal) in depth documentation
- it’s great if you can align with your research, but please discuss this with me early on.

- 20% participation: in class, reading papers, answering “Issues” on assignments
- 5% full-class collaborative project: improve
https://en.wikipedia.org/wiki/Geometry_processing
and related
topics
- Graded based on delta of this page between now and end of term
- Grade is shared by entire class