Zhanping Liu

An Advanced Evenly-Spaced Streamline Placement Algorithm

This paper presents an advanced evenly-spaced streamline placement algorithm for fast, high-quality, and robust layout of flow lines. A fourth-order Runge-Kutta integrator with adaptive step size and error control is employed for rapid accurate streamline advection. Cubic Hermite polynomial interpolation with large sample-spacing is adopted to create fewer evenly-spaced samples along each streamline to reduce the amount of distance checking. We propose two methods to enhance placement quality. Double queues are used to prioritize topological seeding and to favor long streamlines to minimize discontinuities. Adaptive distance control based on the local flow variance is explored to reduce cavities. Furthermore, we propose a universal, effective, fast, and robust loop detection strategy to address closed and spiraling streamlines. Our algorithm is an order-of-magnitude faster than Jobard and Lefers algorithm with better placement quality and over 5 times faster than Mebarki et al.s algorithm with comparable placement quality, but with a more robust solution to loop detection

Accelerated unsteady flow line integral convolution

Unsteady flow line integral convolution (UFLIC) is a texture synthesis technique for visualizing unsteady flows with high temporal-spatial coherence. Unfortunately, UFLIC requires considerable time to generate each frame due to the huge amount of pathline integration that is computed for particle value scattering. This paper presents accelerated UFLIC (AUFLIC) for near interactive (1 frame/second) visualization with 160,000 particles per frame. AUFLIC reuses pathlines in the value scattering process to reduce computationally expensive pathline integration. A flow-driven seeding strategy is employed to distribute seeds such that only a few of them need pathline integration while most seeds are placed along the pathlines advected at earlier times by other seeds upstream and, therefore, the known pathlines can be reused for fast value scattering. To maintain a dense scattering coverage to convey high temporal-spatial coherence while keeping the expense of pathline integration low, a dynamic seeding controller is designed to decide whether to advect, copy, or reuse a pathline. At a negligible memory cost, AUFLIC is 9 times faster than UFLIC with comparable image quality

Results of a user study on 2D hurricane visualization

We present the results from a user study looking at the ability of observers to mentally integrate wind direction and magnitude over a vector field. The data set chosen for the study is an MM5 (PSU/NCAR Mesoscale Model) simulation of Hurricane Lili over the Gulf of Mexico as it approaches the southeastern United States. Nine observers participated in the study. This study investigates the effect of layering on the observers ability to determine the magnitude and direction of a vector field. We found a tendency for observers to underestimate the magnitude of the vectors and a counter‐clockwise bias when determining the average direction of a vector field. We completed an additional study with two observers to try to uncover the source of the counter‐clockwise bias. These results have direct implications to atmospheric scientists, but may also be able to be applied to other fields that use 2D vector fields.

Robust Loop Detection for Interactively Placing Evenly Placed Streamlines

The authors present a robust and fast loop-detection strategy to interactively place dense, uncluttered, evenly spaced streamlines, which help visualize complex flows. Although loop detection is critical to streamline placement, few researchers have addressed this issue. In this paper an effective, robust, and fast loop-detection strategy for creating evenly spaced streamlines is described. At a negligible additional cost, it allows interactive streamline placement for complex flows on an ordinary PC.

AUFLIC: an accelerated algorithm for Unsteady Flow Line Integral Convolution

UFLIC (Unsteady Flow Line Integral Convolution) is an effective texture synthesis technique to visualize unsteady flow with enhanced temporal coherence, but it is time-consuming to generate. This paper presents an accelerated algorithm, called AUFLIC (Accelerated UFLIC), to speed up the UFLIC generation. Our algorithm saves, re-uses, and updates pathlines in the value scattering processes. A flexible seeding strategy is introduced so that a seed particle may be directly extracted from the previous scattering processes to make best use of the saved pathline so as to reduce computationally expensive pathline integration calculations. A dynamic activation-deactivation scheme is employed to maintain the fewest necessary pathlines. Avoiding excessive pathlines achieves acceleration and nearly-constant memory consumption. With very low memory cost, AUFLIC cuts UFLIC generation time nearly in half without any image quality degradation.

A 2D Flow Visualization User Study Using Explicit Flow Synthesis and Implicit Task Design

This paper presents a 2D flow visualization user study that we conducted using new methodologies to increase the objectiveness. We evaluated grid-based variable-size arrows, evenly spaced streamlines, and line integral convolution (LIC) variants (basic, oriented, and enhanced versions) coupled with a colorwheel and/or rainbow color map, which are representative of many geometry-based and texture-based techniques. To reduce data-related bias, template-based explicit flow synthesis was used to create a wide variety of symmetric flows with similar topological complexity. To suppress task-related bias, pattern-based implicit task design was employed, addressing critical point recognition, critical point classification, and symmetric pattern categorization. In addition, variable-duration and fixed-duration measurement schemes were utilized for lightweight precision-critical and heavyweight judgment-intensive flow analysis tasks, respectively, to record visualization effectiveness. We eliminated outliers and used the Ryan REGWQ post-hoc homogeneous subset tests in statistical analysis to obtain reliable findings. Our study shows that a texture-based dense representation with accentuated flow streaks, such as enhanced LIC, enables intuitive perception of the flow, while a geometry-based integral representation with uniform density control, such as evenly spaced streamlines, may exploit visual interpolation to facilitate mental reconstruction of the flow. It is also shown that inappropriate color mapping (e.g., colorwheel) may add distractions to a flow representation.

A Texture-Based Hardware-Independent Technique for Time-Varying Volume Flow Visualization

Existing texture-based 3D flow visualization techniques, e.g., volume Line Integral Convolution (LIC), are either limited to steady flows or dependent on special-purpose graphics cards. In this paper we present a texture-based hardware-independent technique for time-varying volume flow visualization. It is based on our Accelerated Unsteady Flow LIC (AUFLIC) algorithm (Liu and Moorhead, 2005), which uses a flow-driven seeding strategy and a dynamic seeding controller to reuse pathlines in the value scattering process to achieve fast time-dependent flow visualization with high temporal-spatial coherence. We extend AUFLIC to 3D scenarios for accelerated generation of volume flow textures. To address occlusion, lack of depth cuing, and poor perception of flow directions within a dense volume, we employ magnitude-based transfer functions and cutting planes in volume rendering to clearly show the flow structure and the flow evolution.Existing texture-based 3D flow visualization techniques, e.g., volume Line Integral Convolution (LIC), are either limited to steady flows or dependent on special-purpose graphics cards. In this paper we present a texture-based hardware-independent technique for time-varying volume flow visualization. It is based on our Accelerated Unsteady Flow LIC (AUFLIC) algorithm (Liu and Moorhead, 2005), which uses a flow-driven seeding strategy and a dynamic seeding controller to reuse pathlines in the value scattering process to achieve fast time-dependent flow visualization with high temporal-spatial coherence. We extend AUFLIC to 3D scenarios for accelerated generation of volume flow textures. To address occlusion, lack of depth cuing, and poor perception of flow directions within a dense volume, we employ magnitude-based transfer functions and cutting planes in volume rendering to clearly show the flow structure and the flow evolution.

Interactive view-driven evenly spaced streamline placement

This paper presents an Interactive View-Driven Evenly Spaced Streamline placement algorithm (IVDESS) for 3D explorative visualization of large complex planar or curved surface flows. IVDESS rapidly performs accurate streamline integration in 3D physical space, i.e., the flow field, while achieving high quality streamline density control in 2D view space, i.e., the output image. The correspondence between the two spaces is established by using a projection-unprojection pair constituted through geometric surface rendering. An inter-frame physical-space seeding strategy based on streamline reuse+lengthening is adopted, on top of intra-frame view-space seeding, to not only enable coherent flow navigation but also speedup placement generation. IVDESS employs a view-sensitive streamline representation that is well suited for streamline reuse, lengthening, and rendering. In addition, it avoids temporal incoherence caused by streamline splitting and jaggy lines caused by unprojection errors. Our algorithm can run at interactive frame rates (9FPS for placement generation) to allow for 3D exploration of surface flows with smooth evolution of high-density (1%) evenly spaced streamlines in a large window (990 x 700 pixels) on an ordinary PC without either pre-processing or GPU support.

Visualization of confocal microscopic biomolecular data

Biomolecular visualization facilitates insightful interpretation of molecular structures and complex mechanisms underlying bio-chemical processes. Effective visualization techniques are required to deal with confocal microscopic biomolecular data in which intricate structures, fine features, and obscure patterns might be overlooked without sophisticated data processing and image synthesis. This paper presents major challenges in visualizing confocal microscopic biomolecular data, followed by a survey of related work. We then introduce a case study conducted to investigate the interaction between two proteins contained in a budding yeast saccharomyces cerevisiae by embedding custom modules in Amira. The multi-channel confocal microscopic volume data was first processed using an exponential operator to correct z-drop artifacts introduced during data acquisition. Channel correlation was then exploited to extract the overlap between the proteins as a new channel to represent the interaction while a statistical method was employed to compute the intensity of interaction to locate hot spots. To take advantage of crisp surface representation of region boundaries by iso-surfaces and visually pleasing translucent delineation of dense volumes by volume rendering, we adopted hybrid rendering that incorporates these two methods to display clear-cut protein boundaries, amorphous interior materials, and the scattered interaction in the same view volume with suppressed and highlighted parts selected by the user. The highlighted overlap helped biologists learn where the interaction happens and how it spreads, particularly when the volume was investigated in an immersive Cave Automatic Virtual Environment (CAVE) for intuitive comprehension of the data.