Vector Field Visualization using Markov Random Field Texture Synthesis

After synthesizing a new height field with similar statistical prop- erties using standard 2D texture synthesis methods, they ren- der a gray image given a desired view and

Now that we have a representative vector proxy for each region of the mesh, a distortion error is defined that deter- mines how close the simplification is to our original flow

We specifically address issues for parallel GPU-based vector field visualization, such as reduced locality of memory accesses caused by particle tracing, dynamic load balancing

Given the texture on the source model and the guidance field on the target mesh, we use constrained synthesis to generate a texture with appropriate variation.. We adapt two

Each plot shows measurements for a 2D data set (Benard convection) and a 2.5D data set (a spher- ical object with a vector field given on a 3D texture). Fig- ure 4a) reports timings

[LvWJH04] present a side-by-side comparison between two image space based methods for visualization of vector fields on surfaces: Im- age Space Advection (ISA) [LJH03] and Image

In previous work, it is usually created using a potential field function or repulsive force field function [LWM ∗ 03, CSYB05].This section explains the vector field creation al-

Figure 4: Comparison of different scalar fields of the bending energy with our characteristic scalar field:(a) underlying vector field as line integral convolution