Real-time Line-based Flow Visualization

We present in this paper a method that uses densely distributed streamlines to achieve real-time 2D flow visualization with better visual quality than produced by texturebased methods. We call the method a line-based flow visualization (LBFV) method because it uses a dense set of line segments as basic rendering primitives. Streamlines are commonly used for flow visualization, and they provide more effective visualization of global features of flow data than texture-based methods, due to its integral definition. However, existing streamline-based methods use relatively sparsely distributed streamlines and thus produce lower resolution than texture-based methods. In our method densely distributed streamlines are computed using particle advection, with initial particle positions determined by a novel algorithm, and we use hardware-assisted image blending to render the streamlines efficiently for real-time visualization. Specifically, line segments representing particle advection in the current frame are blended with the image of the previous frame to achieve fast rendering (40-100 fps) as well as the natural decaying effect of the wakes of streamlines. Several intuitive parameters, such as the line width, line color, the total number of particles, and the time step for particle advection, can easily be tuned for producing various visual results. Experimental examples are presented to demonstrate the effectiveness of our method and to compare it with the conventional LIC (Line Integral Convolution) method and the IBFV (image-based flow visualization) method.