Mesh compression: Theory and practice.

Three-dimensional meshes (3D meshes, for short) are fast becoming an emerging media type, used in a variety of application domains such as engineering design, manufacture, architecture, bio-informatics, medicine, entertainment, commerce, science, defense, etc. The volume of data of this media type that is being circulated on the internet is increasing very rapidly and is being used as frequently as other media types like text, audio (1D), images and video (2D). Hence, 3D meshes need good processing and visualization methods. Also, the sizes of these meshes are much greater than the other media types mentioned above and often exceeds the memory and bandwidth available for their storage and transmission. Compression schemes for such large 3D meshes have become a subject of intense study lately. Meshes are either made up of triangles or quadrilaterals. Meshes made up of only triangles are called triangle meshes and meshes made up of quadrilaterals are called quadrilateral meshes (quad meshes, for short). A mesh is described by specifying its geometry (vertex coordinates) and its connectivity (adjacencies of the triangles or quadrilaterals). Previous research on mesh compression has been mostly for triangle meshes. Quad meshes were traditionally handled by first triangulating them and then applying triangle mesh compression techniques. In order to avoid this additional triangulation step, a direct technique is proposed for compressing and decompressing the connectivity of quad meshes. This technique takes a quad mesh as input and encodes its connectivity as a sequence of opcodes which can be restored back to the quad mesh, using the decompression technique. A data structure called EdgeTable is introduced to aid in the traversal of a quad mesh during compression. Also, a technique based on constrained Delaunay triangulation for reconstructing the connectivity of a 2D mesh from its geometry and a minimum set of edges is proposed. Source: Masters Abstracts International, Volume: 44-03, page: 1393. Thesis (M.Sc.)--University of Windsor (Canada), 2005

Supporting the use of algorithmic design in architecture: An empirical study of reuse of design knowledge

This thesis tests the reuse of design knowledge as a method to support learning and use of algorithmic design in architecture. The use of algorithmic design systems and programming environments offer architects immense opportunities, providing a powerful means to create geometries and allowing dynamic design exploration, but it can also impose substantial challenges. Architects often struggle with adopting algorithmic design methods (translating a design idea into an algorithm of actions), as well as with the implementation of programming languages, the latter often proving frustrating and creating barriers for both novice and advanced software users. The proposition explored in this thesis is that the reuse of design knowledge can improve architects’ ability to use algorithmic design systems, and reduce the barriers for using programming. This study explores and compares two approaches as a means of accessing and reusing existing design solutions. The first approach is the reuse of abstract algorithmic ‘Design Patterns’. The second is the reuse of algorithmic solutions from specific design cases (Case-Based Design). The research was set up as an experimental comparative study between three test groups: one group using Design Patterns, a second group using Case-Based Design, and the control group. A total of 126 designers participated in the study providing sufficient numbers within each group to permit rigorous studies of the statistical significance of the observed differences. Results of this study illustrate that the systematic inclusion of the Design Patterns approach to the learning strategy of programming in architecture and design, proves to be highly beneficial. The use of abstract solutions improves designers’ ability to overcome programming barriers, and helps architects to adopt algorithmic design methods. The use of Design Patterns also encourages design exploration and experimentation. The use of the Case-Based Design approach seems to be more effective after designers and architects, who are novices in programming, gain more experience with the tool. It encourages more focused reasoning, oriented to the realisation of a particular (originally intended) design outcome. The contribution of this research is to provide empirical evidence that the reuse of abstract and case-based algorithmic solutions can be very beneficial. Results of this study illustrate that both reuse methods can be strategically integrated into design education and architectural practice, supporting learning and use of algorithmic design systems in architecture. The study also identifies potential weaknesses of each approach, proposing areas which could be addressed by future studies