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Computer Graphics 2 (SS2008)
| Instructor: | Prof. Dr. Marc Alexa |
|---|---|
| Contact | Mathias Eitz |
| Course structure: | Integrated event (IV) - 4 SWS |
| Room: | MA 041 |
| Date: | Thursday 2pm - 6pm Start : 17 Apr 2008 |
| Description: | Modeling: Parametric curves and surfaces, Implicit curves and surfaces Triangular meshes: Compression, simplification, multiresolution models Modul CG2 - Modeling in Computer Graphics |
| Comments: | Prerequisites: Programming skills in an oo-language Algorithms and data structures OpenGL Linear Algebra Analysis |
News
- 12.07.08: Grades for the third and fourth practice sheet
- 07.07.08: The CG2 exams from 2004 and 2005 for preparation.
- 26.06.08: Check the page of Michael Garland for more information about surface simplification using quadric error metrics
- 20.06.08: Grades for the second practice sheet online
- 30.05.08: Grades for the first practice sheet online
- 07.05.08: Some performance figures of a C++ Octree/KdTree implementation to compare your own implementation against (querying the 25 nearest neighbors on the dragon model ~0.5 Mio points): Octree (max depth 10, bucket size 10): ~150μs; Kd Tree (bucket size: 10): ~30μs
- 05.08: Final list of groups
- 02.05.08: Here is the list of groups
Exercise 4: 16.06.08 - 10.07.08
- © Computer Graphics, TUB
Simplification and subdivision of triangles meshes
The provided implementations should be regarded as information only, do not use them as templates for your implementation.
Exercise 3: 29.05.08 - 19.06.08
- © Computer Graphics, TUB
Approximation and polygonization of implicit surfaces
Caveat: Normals of the horse, hound, rhino and snail dataset need to be flipped.
Exercise 2: 09.05.08 - 29.05.08
- © Computer Graphics, TUB
Approximation of heightfields
A paper about LS, WLS and MLS which might be helpful for solving the exercise.
You might want to use the Newmat10 library for solving linear systems.
You should be able to handle large files (1M points) in a reasonable amount of time.
Exercise 1: 17.04.08 - 08.05.08
- © Computer Graphics, TUB
Hierarchical spatial data structures
Additional models with more than one million points can be downloaded from the Stanford 3D Scanning Repository and the AIM@SHAPE Shape Repository
Slides
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