CGAL is a Computational Geometry Algorithms Library written in C++, which is being developed by research groups in Europe and Israel. The goal is to make the large body of geometric algorithms developed in the field of computational geometry available for industrial application. We discuss the major design goals for CGAL, which are correctness, flexibility, ease-of-use, efficiency, and robustness, and present our approach to reach these goals. Generic programming using templates in C++ plays a central role in the architecture of CGAL. We give a short introduction to generic programming in C++, compare it to the object-oriented programming paradigm, and present examples where both paradigms are used effectively in CGAL. Moreover, we give an overview of the current structure of the CGAL-library and consider software engineering aspects in the CGAL-project. Copyright c ○ 1999 John Wiley & Sons, Ltd. KEY WORDS: computational geometry; software library; C++; generic programming;

In many applications it is important that one can view a scene at different levels of detail. A prime example is flight simulation: a high level of detail is needed when flying low, whereas a low level of detail suffices when flying high. More precisely, one would like to visualize the part of the scene that is close at a high level of detail, and the part that is far away at a low level of detail. We propose a hierarchy of detail levels for a polyhedral terrain (or, triangulated irregular network) that allows this: given a view point, it is possible to select the appropriate level of detail for each part of the terrain in such a way that the parts still fit together continuously. The main advantage of our structure is that it uses the Delaunay triangulation at each level, so that triangles with very small angles are avoided. This is the first method that uses the Delaunay triangulation and still allows to combine different levels into a single representation. Keywords: Computational ...

Introduction Geometric problems arise in many areas. Computer graphics, robotics, manufacturing, and geographic information systems are some examples. Often the same geometric subproblems are to be solved. Hence a library providing solutions for core problems in geometric computing has a wide range of applications and can be very useful. The success of LEDA [16], a library of efficient data types and algorithms, has shown that the existence of a library can make a tremendous difference for taking advanced techniques in data structures and algorithms from theory to practice. The field of computational geometry is now very close to a state where it can provide such a library of geometric algorithms. Over the past twenty years many algorithms for geometric problems have been developed by computational geometers. Many of these algorithms clearly have no direct impact for geometric computing in practice, because they are efficient compared to other solutions only for huge problem i

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