Category Data Visualization Based on Obstacle Avoidances

Abstract

Obstacle avoidance algorithm is often used in data visualization to connect lines between data items or perform route planning in 3D volume visualization. The traditional obstacle avoidance algorithm is often designed to find a shortest path between two data items. It is not suitable to be used in visualization, because it needs to achieve a more artistic and smooth effect. Well-designed visualization often provides user-friendly, effective, and efficient manipulations and interactions. In this paper, we use an obstacle avoidance algorithm to connect lines between data items, which can be used to visualize set information present in category data (or set data). Specifically, we use A-star algorithm to conduct obstacle avoidance between data items, then we make the lines more artistic and smooth by introducing a series pivot points. Finally, we visualize the data items by connecting the lines to show the category information and sub-category information or other information. Experiments show that the proposed approach is capable of revealing the set information present in category data.