The State of the Art in Flow Visualization, part 1: Direct, Texture-based, and Geometric Techniques

Flow visualization has been a very attractive part of visualization research for a long time. Usually very large datasets need to be processed, which often consist of multivariate data with a large number of sample locations, often arranged in multiple time steps. Recently, the steadily increasing performance of computers again has become a driving factor for a reemergence in flow visualization, especially in techniques based on feature extraction, vector field clustering, and topology extraction. In this article and a companion paper 69, the state of the art in flow visualization (FlowVis) is presented. In this paper, direct (or global) flow visualization such as hedgehog plots, texture-based flow visualization such as line integral convolution, and geometric flow visualization such as stream lines is discussed. Part 2 of this report 69 focusses on feature-based flow visualization in detail. In this paper, also an attempt of categorizing FlowVis solutions is presented which is incorporated as a structure for part 1 (this paper). FlowVis fundamentals are shortly addressed as well as conclusions and future prospects.