Telea, AlexandruWijk, Jarke J. vanDavid S. Ebert and Jean M. Favre and Ronald Peikert2014-01-302014-01-3020013-211-83674-81727-5296https://doi.org/10.2312/VisSym/VisSym01/165-174Voronoi diagrams are an important data structure in computer science. However well studied mathematically, understanding such diagrams for different metrics, orders, and site shapes is a complex task. We propose a new method to visualize k-order diagrams and give an efficient adaptive implementation for this method. The algorithm is easy to customize for different metrics and site shapes. Its real-time performance makes it suitable for interactive planning and analysis of complex Voronoi configurations in 2D.We illustrate the method for different combinations of metrics and site shapes.