Image Based Flow Visualization Research Articles

The Design and Optimization of Ship Cabin Space Layout Based on Crowd Simulation

<p indent=0mm>In order to solve the space layout optimization problem of ship cabin efficiently, an interactive layout design and optimization method based on crowd simulation and tensor field is proposed. Firstly, the image based flow visualization algorithm is used to analyze the tensor field of the space layout domain, which calculates the eigenvector and generates the road network of ship, and obtain the cabin space layout based on the road network. Secondly, the crowd simulation algorithm is used to simulate the behavioral activities of the crowd in the cabin space, and then to evaluate the mobility and coziness of the crowd in the ship cabin space. After obtaining a series of road network of ship and results of crowd simulation, the mapping relationship between road width and road spacing in road network and mobility value and comfort value in crowd simulation results is established respectively. The results of crowd simulation are used as evaluation criterion to interactively and iteratively adjust the characteristic parameters of tensor field. The experimental results show that the proposed method effectively establishes the mapping relationship between tensor field and crowd simulation. Compared with genetic algorithm and analytic hierarchy process, it can quickly and efficiently design high-quality cabin space layout in line with human activities demand.

Flow simulation and visualization in a three-dimensional shipping information system

We develop a three-dimensional (3D) shipping information system as a case study for the integration of a dynamic flow field and a 3D virtual geographical environment. A 2D hydrodynamic model is formulated to calculate the waterway depth and velocity distribution by using real-time hydrologic monitoring data. The parallel OpenMP computations take 4min on a 20-core computer. The image-based flow visualization method is used to produce a 2D dynamic flow field on a curved surface, and the integration of dynamic flow fields with a 3D virtual geographical environment was achieved with the OpenSceneGraph rendering engine. Compared with a traditional 2D navigation map, the combination of a flow simulation and a visualization module can integrate flow velocity magnitude and distribution, and enhance ship navigation safety. This functionality will aid the display of integrated scientific information, and will have potential applications within 3D information systems in many domains.

Image-Space Texture-Based Output-Coherent Surface Flow Visualization

Image-space line integral convolution (LIC) is a popular scheme for visualizing surface vector fields due to its simplicity and high efficiency. To avoid inconsistencies or color blur during the user interactions, existing approaches employ surface parameterization or 3D volume texture schemes. However, they often require expensive computation or memory cost, and cannot achieve consistent results in terms of both the granularity and color distribution on different scales. This paper introduces a novel image-space surface flow visualization approach that preserves the coherence during user interactions. To make the noise texture under different viewpoints coherent, we propose to precompute a sequence of mipmap noise textures in a coarse-to-fine manner for consistent transition, and map the textures onto each triangle with randomly assigned and constant texture coordinates. Further, a standard image-space LIC is performed to generate the flow texture. The proposed approach is simple and GPU-friendly, and can be easily combined with various texture-based flow visualization techniques. By leveraging viewpoint-dependent backward tracing and mipmap noise phase, our method can be incorporated with the image-based flow visualization (IBFV) technique for coherent visualization of unsteady flows. We demonstrate consistent and highly efficient flow visualization on a variety of data sets.

Interactive Tensor Field Design and Visualization on Surfaces

Designing tensor fields in the plane and on surfaces is a necessary task in many graphics applications, such as painterly rendering, pen-and-ink sketching of smooth surfaces, and anisotropic remeshing. In this article, we present an interactive design system that allows a user to create a wide variety of symmetric tensor fields over 3D surfaces either from scratch or by modifying a meaningful input tensor field such as the curvature tensor. Our system converts each user specification into a basis tensor field and combines them with the input field to make an initial tensor field. However, such a field often contains unwanted degenerate points which cannot always be eliminated due to topological constraints of the underlying surface. To reduce the artifacts caused by these degenerate points, our system allows the user to move a degenerate point or to cancel a pair of degenerate points that have opposite tensor indices. These operations provide control over the number and location of the degenerate points in the field. We observe that a tensor field can be locally converted into a vector field so that there is a one-to-one correspondence between the set of degenerate points in the tensor field and the set of singularities in the vector field. This conversion allows us to effectively perform degenerate point pair cancellation and movement by using similar operations for vector fields. In addition, we adapt the image-based flow visualization technique to tensor fields, therefore allowing interactive display of tensor fields on surfaces. We demonstrate the capabilities of our tensor field design system with painterly rendering, pen-and-ink sketching of surfaces, and anisotropic remeshing.

ISA and IBFVS: image space-based visualization of flow on surfaces

We present a side-by-side analysis of two recent image space approaches for the visualization of vector fields on surfaces. The two methods, Image Space Advection (ISA) and Image-Based Flow Visualization for Curved Surfaces (IBFVS) generate dense representations of time-dependent vector fields with high spatio-temporal correlation. While the 3D vector fields are associated with arbitrary surfaces represented by triangular meshes, the generation and advection of texture properties is confined to image space. Fast frame rates are achieved by exploiting frame-to-frame coherency and graphics hardware. In our comparison of ISA and IBFVS, we point out the strengths and weaknesses of each approach and give recommendations as to when and where they are best applied.

Image based flow visualization

A new method for the visualization of two-dimensional fluid flow is presented. The method is based on the advection and decay of dye. These processes are simulated by defining each frame of a flow animation as a blend between a warped version of the previous image and a number of background images. For the latter a sequence of filtered white noise images is used: filtered in time and space to remove high frequency components. Because all steps are done using images, the method is named Image Based Flow Visualization ( IBFV ). With IBFV a wide variety of visualization techniques can be emulated. Flow can be visualized as moving textures with line integral convolution and spot noise. Arrow plots, streamlines, particles, and topological images can be generated by adding extra dye to the image. Unsteady flows, defined on arbitrary meshes, can be handled. IBFV achieves a high performance by using standard features of graphics hardware. Typically fifty frames per second are generated using standard graphics cards on PCs. Finally, IBFV is easy to understand, analyse, and implement.