The development of level of detail (LOD) technique in 3D computer graphics application - Ismail, Nor Anita Fairos; Daman, Daut; Mohd. Rahim, Mohd. Shafry (Faculty of Computer Science and Information System, 2009)
Drastic growth in computer simulation complexity and 3D scanning technology has boosted the size of geometry data sets used in visualization. Conventional (in-core) simplification techniques are sufficient in data reduction to accelerate graphics rendering. However, some powerful graphics workstations are sometimes unable to load or even generate the smooth rendering of these extremely large data. In this thesis, out-of-core simplification algorithm is introduced to overcome the limitation of conventional technique. Surface attributes such as normals, colors and textures, which are essentials to bring out the beauty of 3D object are preserved and discussed. The first process is to convert the input data into a memory efficient format. Next, the datasets are organized in an octree structure and later the 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 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 octrees subdivision level and end node size. The finer the octree, the finer will be the mesh being generated. Overall, the proposed algorithm is capable in simplifying large viii datasets with pleasant quality and relatively fast. The system can run efficiently on low cost personal computer with small memory footprint.