Difference-Contribution Strategy for Seeding 2D Streamlines

Abstract

This paper presents a novel seeding strategy for streamline visualization of 2D vector field. The main idea of our approach is to capture the spatial-varying features in a vector field. Generally speaking, we measure the difference between the inflow and the outflow to evaluate the local spatial-varying feature at a specified field point. A Difference-Contribution Matrix (DCM) is then calculated to describe the global appearance of the field. We draw streamlines by choosing the local extreme points in DCM as seeds. DCM is physics-related thus reflects intrinsic characteristics of the vector field. The strategy performs well in revealing features of the vector field even with relatively few streamlines.