Out-of-core simplification with appearance preservation for computer game applications
Drastic growth in computer simulations complexity and 3D scanning technology has boosted the size of geometry data sets. Before this, conventional (incore) simplification techniques are sufficient in data reduction to accelerate graphics rendering. However, powerful graphics workstation also unable...
Saved in:
| Main Author: | |
|---|---|
| Format: | Thesis |
| Language: | English |
| Published: |
2006
|
| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/5347/1/TanKimHeokMFSKSM2006.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Drastic growth in computer simulations complexity and 3D scanning technology has boosted the size of geometry data sets. Before this, conventional (incore) simplification techniques are sufficient in data reduction to accelerate graphics rendering. However, powerful graphics workstation also unable to load or even generates the smooth rendering of these extremely large data. In this thesis, out-ofcore simplification algorithm is introduced to overcome the limitation of conventional technique. Meanwhile, preservation on surface attributes such as normals, colors and textures, which essential to bring out the beauty of 3D object, are also discussed. The first process is to convert the input data into a memory efficient format. Next, datasets are organized in an octree structure and later partitioned meshes are kept in secondary memory (hard disk). Subsequently, submeshes are simplified using a new variation of vertex clustering technique. In order to maintain the surface attributes, a proposed vertex clustering technique that collapses all triangles in every leaf node using the generalized quadric error metrics is introduced. Unlike any other vertex clustering methods, the knowledge of neighbourhood between nodes is unnecessary and the node simplification is performed independently. This simplification is executed recursively until a desired levels of detail is achieved. During run-time, the visible mesh is rendered based on the distance criterion by extracting the required data from the previously generated octree structure. The evaluated experiments show that the simplification is greatly controlled by octree s subdivision level and end node size. The finer the octree, thus the finer mesh will be generated. Overall, the proposed algorithm is capable in simplifying large datasets with pleasant quality and relatively fast. The system is run efficiently on low cost personal computer with small memory footprint. |
|---|