| Instructors: | Prof. Dr. Marc Alexa |
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| Contact | Olivier Rouiller |
| Course structure: | Integrierte Veranstaltung (IV) – 4 SWS |
| Room: | MA 041 |
| Date: | Thursdays 14:00 – 16:00 every week Start : 11 April 2013 |
| Description: | The course introduces the basics of Geometry Processing. Mathematical models, data structures and algorithm to represent geometry on modern computer applications are presented and manipulated through practical exercises. The techniques seen in the course are fundamental for application like 3D modeling, geometry reconstruction from scanned objects, physical simulation, … |
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| Requirements: |
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| Registration: | Please send an email with your name, student id. and the name of the course to Gaëlle Fer-Arslan |
| Forum: | Isis page of the course |
Assignments
Exercise 4 : Mesh optimization
- Exercise sheet (PDF, 387,4 KB)
- Additional material:
- Surface Simplification Using Quadric Error Metrics, Michael Garland and Paul S. Heckbert
- Sqrt(3) Subdivision, Leif Kobbelt
- Smooth Subdivision Surfaces Based On Triangles, Charles Loop
Exercise 3 : Approximation and tessellation of implicit surfaces
Caveat: normals of some dataset need to be flipped.
Exercise 2 : Heightfield approximation
The technical report about least squares, weighted least squares and moving least squares by A. Nealen might be helpful for solving the exercise.
We suggest using the Newmat library or the Eigen library for solving the linear systems occuring in this exercise.
Exercise 1: Hierarchical Spatial Datastructures
Your implementation should be able to easily handle the files in pointdata_small.zip. Please also experiment with the data in pointdata_large.zip, your implementation should be able to handle this file in a reasonable amount of time.
Additional large models can be downloaded from e.g. the
Stanford 3D Scanning Repository or the AIM@SHAPE Shape Repository
- Exercise sheet (PDF, 132,3 KB)
- Example C++ framework (ZIP, 9,2 KB)
- Minimal code for a QT/OpenGL App (only tested on windows-VS2010 so far…)
- Small point data (zip, 2.9 MB)
- Large point data (zip, 57.8 MB)
Links