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SCI Publications

2014


C.D. Hansen, M. Chen, C.R. Johnson, A.E. Kaufman, H. Hagen (Eds.). “Scientific Visualization: Uncertainty, Multifield, Biomedical, and Scalable Visualization,” Mathematics and Visualization, Springer, 2014.
ISBN: 978-1-4471-6496-8



T. Hollt, A. Magdy, P. Zhan, G. Chen, G. Gopalakrishnan, I. Hoteit, C.D. Hansen, M. Hadwiger. “Ovis: A Framework for Visual Analysis of Ocean Forecast Ensembles,” In IEEE Transactions on Visualization and Computer Graphics (TVCG), Vol. PP, No. 99, pp. 1. 2014.
DOI: 10.1109/TVCG.2014.2307892

ABSTRACT

We present a novel integrated visualization system that enables interactive visual analysis of ensemble simulations of the sea surface height that is used in ocean forecasting. The position of eddies can be derived directly from the sea surface height and our visualization approach enables their interactive exploration and analysis. The behavior of eddies is important in different application settings of which we present two in this paper. First, we show an application for interactive planning of placement as well as operation of off-shore structures using real-world ensemble simulation data of the Gulf of Mexico. Off-shore structures, such as those used for oil exploration, are vulnerable to hazards caused by eddies, and the oil and gas industry relies on ocean forecasts for efficient operations. We enable analysis of the spatial domain, as well as the temporal evolution, for planning the placement and operation of structures. Eddies are also important for marine life. They transport water over large distances and with it also heat and other physical properties as well as biological organisms. In the second application we present the usefulness of our tool, which could be used for planning the paths of autonomous underwater vehicles, so called gliders, for marine scientists to study simulation data of the largely unexplored Red Sea.

Keywords: Ensemble Visualization, Ocean Visualization, Ocean Forecast, Risk Estimation



Y. Wan, H. Otsuna, K. Kwan, C.D. Hansen. “Real-Time Dense Nucleus Selection from Confocal Data,” In Proceedings of the Eurographics Workshop on Visual Computing for Biology and Medicine, 2014.

ABSTRACT

Selecting structures from volume data using direct over-the-visualization interactions, such as a paint brush, is perhaps the most intuitive method in a variety of application scenarios. Unfortunately, it seems difficult to design a universal tool that is effective for all different structures in biology research. In [WOCH12b], an interactive technique was proposed for extracting neural structures from confocal microscopy data. It uses a dual-stroke paint brush to select desired structures directly from volume visualizations. However, the technique breaks down when it was applied to selecting densely packed structures with condensed shapes, such as nuclei from zebrafish eye development research. We collaborated with biologists studying zebrafish eye development and adapted the paint brush tool for real-time nucleus selection from volume data. The morphological diffusion algorithm used in the previous paint brush is restricted to gradient descending directions for improved nucleus boundary definition. Occluded seeds are removed using backward ray-casting. The adapted paint brush is then used in tracking cell movements in a time sequence dataset of a developing zebrafish eye.



L. Zhou, C.D. Hansen. “GuideME: Slice-guided Semiautomatic Multivariate Exploration of Volumes,” In Proceedings of the Eurographics Conference on Visualization (EuroVis) 2014, Vol. 33, No. 3, 2014.

ABSTRACT

Multivariate volume visualization is important for many applications including petroleum exploration and medicine. State-of-the-art tools allow users to interactively explore volumes with multiple linked parameter-space views. However, interactions in the parameter space using trial-and-error may be unintuitive and time consuming. Furthermore, switching between different views may be distracting. In this paper, we propose GuideME: a novel slice-guided semiautomatic multivariate volume exploration approach. Specifically, the approach comprises four stages: attribute inspection, guided uncertainty-aware lasso creation, automated feature extraction and optional spatial fine tuning and visualization. Throughout the exploration process, the user does not need to interact with the parameter views at all and examples of complex real-world data demonstrate the usefulness, efficiency and ease-of-use of our method.


2013


C. Brownlee, T. Ize, C.D. Hansen. “Image-parallel Ray Tracing using OpenGL Interception,” In Proceedings of the Eurographics Symposium on Parallel Graphics and Visualization (EGPGV 2013), pp. 65--72. 2013.

ABSTRACT

CPU Ray tracing in scientific visualization has been shown to be an efficient rendering algorithm for large-scale polygonal data on distributed-memory systems by using custom integrations which modify the source code of existing visualization tools or by using OpenGL interception to run without source code modification to existing tools. Previous implementations in common visualization tools use existing data-parallel work distribution with sort-last compositing algorithms and exhibited sub-optimal performance scaling across multiple nodes due to the inefficiencies of data-parallel distributions of the scene geometry. This paper presents a solution which uses efficient ray tracing through OpenGL interception using an image-parallel work distribution implemented on top of the data-parallel distribution of the host program while supporting a paging system for access to non-resident data. Through a series of scaling studies, we show that using an image-parallel distribution often provides superior scaling performance which is more independent of the data distribution and view, while also supporting secondary rays for advanced rendering effects.



A. Grosset, M. Schott, G.-P. Bonneau, C.D. Hansen. “Evaluation of Depth of Field for Depth Perception in DVR,” In Proceedings of the 2013 IEEE Pacific Visualization Symposium (PacificVis), pp. 81--88. 2013.

ABSTRACT

In this paper we present a user study on the use of Depth of Field for depth perception in Direct Volume Rendering. Direct Volume Rendering with Phong shading and perspective projection is used as the baseline. Depth of Field is then added to see its impact on the correct perception of ordinal depth. Accuracy and response time are used as the metrics to evaluate the usefulness of Depth of Field. The onsite user study has two parts: static and dynamic. Eye tracking is used to monitor the gaze of the subjects. From our results we see that though Depth of Field does not act as a proper depth cue in all conditions, it can be used to reinforce the perception of which feature is in front of the other. The best results (high accuracy & fast response time) for correct perception of ordinal depth occurs when the front feature (out of the two features users were to choose from) is in focus and perspective projection is used.



T. Höllt, A. Magdy, G. Chen, G. Gopalakrishnan, I. Hoteit, C.D. Hansen, M. Hadwiger. “Visual Analysis of Uncertainties in Ocean Forecasts for Planning and Operation of Off-Shore Structures,” In Proceedings of 2013 IEEE Pacific Visualization Symposium (PacificVis), Note: Received Honerable Mention, pp. 185--192. 2013.

ABSTRACT

We present a novel integrated visualization system that enables interactive visual analysis of ensemble simulations used in ocean forecasting, i.e, simulations of sea surface elevation. Our system enables the interactive planning of both the placement and operation of off-shore structures. We illustrate this using a real-world simulation of the Gulf of Mexico. Off-shore structures, such as those used for oil exploration, are vulnerable to hazards caused by strong loop currents. The oil and gas industry therefore relies on accurate ocean forecasting systems for planning their operations. Nowadays, these forecasts are based on multiple spatio-temporal simulations resulting in multidimensional, multivariate and multivalued data, so-called ensemble data. Changes in sea surface elevation are a good indicator for the movement of loop current eddies, and our visualization approach enables their interactive exploration and analysis. We enable analysis of the spatial domain, for planning the placement of structures, as well as detailed exploration of the temporal evolution at any chosen position, for the prediction of critical ocean states that require the shutdown of rig operations.

Keywords: Uncertainty, Ensemble Simulation, Risk Estimate



T. McLoughlin, M.W. Jones, R.S. Laramee, R. Malki, I. Masters, C.D. Hansen. “Similarity Measures for Enhancing Interactive Streamline Seeding,” In IEEE Transactions on Visualization and Computer Graphics (TVCG), Vol. 19, No. 8, pp. 1342--1353. 2013.
ISSN: 1077-2626
DOI: 10.1109/TVCG.2012.150
PubMed ID: 23744264

ABSTRACT

Streamline seeding rakes are widely used in vector field visualization. We present new approaches for calculating similarity between integral curves (streamlines and pathlines). While others have used similarity distance measures, the computational expense involved with existing techniques is relatively high due to the vast number of euclidean distance tests, restricting interactivity and their use for streamline seeding rakes. We introduce the novel idea of computing streamline signatures based on a set of curve-based attributes. A signature produces a compact representation for describing a streamline. Similarity comparisons are performed by using a popular statistical measure on the derived signatures. We demonstrate that this novel scheme, including a hierarchical variant, produces good clustering results and is computed over two orders of magnitude faster than previous methods. Similarity-based clustering enables filtering of the streamlines to provide a nonuniform seeding distribution along the seeding object. We show that this method preserves the overall flow behavior while using only a small subset of the original streamline set. We apply focus + context rendering using the clusters which allows for faster and easier analysis in cases of high visual complexity and occlusion. The method provides a high level of interactivity and allows the user to easily fine tune the clustering results at runtime while avoiding any time-consuming recomputation. Our method maintains interactive rates even when hundreds of streamlines are used.



M. Schott, T. Martin, A.V.P. Grosset, S.T. Smith, C.D. Hansen. “Ambient Occlusion Effects for Combined Volumes and Tubular Geometry,” In IEEE Transactions on Visualization and Computer Graphics (TVCG), Vol. 19, No. 6, Note: Selected as Spotlight paper for June 2013 issue, pp. 913--926. 2013.
DOI: 10.1109/TVCG.2012.306

ABSTRACT

This paper details a method for interactive direct volume rendering that computes ambient occlusion effects for visualizations that combine both volumetric and geometric primitives, specifically tube shaped geometric objects representing streamlines, magnetic field lines or DTI fiber tracts. The algorithm extends the recently presented Directional Occlusion Shading model to allow the rendering of those geometric shapes in combination with a context providing 3D volume, considering mutual occlusion between structures represented by a volume or geometry. Stream tube geometries are computed using an effective spline based interpolation and approximation scheme that avoids self intersection and maintains coherent orientation of the stream tube segments to avoid surface deforming twists. Furthermore, strategies to reduce the geometric and specular aliasing of the stream tubes are discussed.

Keywords: Volume rendering, ambient occlusion, stream tubes



Y. Wan, H. Otsuna, C.D. Hansen. “Synthetic Brainbows,” In Computer Graphics Forum, Vol. 32, No. 3pt4, pp. 471--480. 2013.
DOI: 10.1111/cgf.12134

ABSTRACT

Brainbow is a genetic engineering technique that randomly colorizes cells. Biological samples processed with this technique and imaged with confocal microscopy have distinctive colors for individual cells. Complex cellular structures can then be easily visualized. However, the complexity of the Brainbow technique limits its applications. In practice, most confocal microscopy scans use different florescence staining with typically at most three distinct cellular structures. These structures are often packed and obscure each other in rendered images making analysis difficult. In this paper, we leverage a process known as GPU framebuffer feedback loops to synthesize Brainbow-like images. In addition, we incorporate ID shuffling and Monte-Carlo sampling into our technique, so that it can be applied to single-channel confocal microscopy data. The synthesized Brainbow images are presented to domain experts with positive feedback. A user survey demonstrates that our synthetic Brainbow technique improves visualizations of volume data with complex structures for biologists.



L. Zhou, C.D. Hansen. “Transfer Function Design based on User Selected Samples for Intuitive Multivariate Volume Exploration,” In Proceedings of the 2013 IEEE Pacific Visualization Symposium (PacificVis), pp. 73--80. 2013.
ISSN: 2165-8765
DOI: 10.1109/PacificVis.2013.6596130

ABSTRACT

Multivariate volumetric datasets are important to both science and medicine. We propose a transfer function (TF) design approach based on user selected samples in the spatial domain to make multivariate volumetric data visualization more accessible for domain users. Specifically, the user starts the visualization by probing features of interest on slices and the data values are instantly queried by user selection. The queried sample values are then used to automatically and robustly generate high dimensional transfer functions (HDTFs) via kernel density estimation (KDE). Alternatively, 2D Gaussian TFs can be automatically generated in the dimensionality reduced space using these samples. With the extracted features rendered in the volume rendering view, the user can further refine these features using segmentation brushes. Interactivity is achieved in our system and different views are tightly linked. Use cases show that our system has been successfully applied for simulation and complicated seismic data sets.



L. Zhou, C.D. Hansen. “Interactive rendering and efficient querying for large multivariate seismic volumes on consumer level PCs,” In Proceedings of the 2013 IEEE Symposium on Large-Scale Data Analysis and Visualization (LDAV), pp. 117--118. 2013.
DOI: 10.1109/LDAV.2013.6675167

ABSTRACT

We present a volume visualization method that allows interactive rendering and efficient querying of large multivariate seismic volume data on consumer level PCs. The volume rendering pipeline utilizes a virtual memory structure that supports out-of-core multivariate multi-resolution data and a GPU-based ray caster that allows interactive multivariate transfer function design. A Gaussian mixture model representation is precomputed and nearly interactive querying is achieved by testing the Gaussian functions against user defined transfer functions on the GPU in the runtime. Finally, the method has been tested on a multivariate 3D seismic dataset which is larger than the size of the main memory of the testing machine.


2012


C. Brownlee, T. Fogal, C.D. Hansen. “GLuRay: Ray Tracing in Scientific Visualization Applications using OpenGL Interception,” In Proceedings of the Eurographics Symposium on Parallel Graphics and Visualization (2012), Edited by H. Childs and T. Kuhlen and F. Marton, pp. 41--50. 2012.
DOI: 10.2312/EGPGV/EGPGV12/041-050

ABSTRACT

Ray tracing in scientific visualization allows for substantial gains in performance and rendering quality with large scale polygonal datasets compared to brute-force rasterization, however implementing new rendering architectures into existing tools is often costly and time consuming. This paper presents a library, GLuRay, which intercepts OpenGL calls from many common visualization applications and renders them with the CPU ray tracer Manta without modification to the underlying visualization tool. Rendering polygonal models such as isosurfaces can be done identically to an OpenGL implementation using provided material and camera properties or superior rendering can be achieved using enhanced settings such as dielectric materials or pinhole cameras with depth of field effects. Comparative benchmarks were conducted on the Texas Advanced Computing Center’s Longhorn cluster using the popular visualization packages ParaView, VisIt, Ensight, and VAPOR. Through the parallel ren- dering package ParaView, scaling up to 64 nodes is demonstrated. With our tests we show that using OpenGL interception to accelerate and enhance visualization programs provides a viable enhancement to existing tools with little overhead and no code modification while allowing for the creation of publication quality renderings using advanced effects and greatly improved large-scale software rendering performance within tools that scientists are currently using.

Keywords: kaust, scidac



C. Brownlee, J. Patchett, L.-T. Lo, D. DeMarle, C. Mitchell, J. Ahrens, C.D. Hansen. “A Study of Ray Tracing Large-scale Scientific Data in Parallel Visualization Applications,” In Proceedings of the Eurographics Symposium on Parallel Graphics and Visualization (2012), Edited by H. Childs and T. Kuhlen and F. Marton, pp. 51--60. 2012.

ABSTRACT

Large-scale analysis and visualization is becoming increasingly important as supercomputers and their simulations produce larger and larger data. These large data sizes are pushing the limits of traditional rendering algorithms and tools thus motivating a study exploring these limits and their possible resolutions through alternative rendering algorithms . In order to better understand real-world performance with large data, this paper presents a detailed timing study on a large cluster with the widely used visualization tools ParaView and VisIt. The software ray tracer Manta was integrated into these programs in order to show that improved performance could be attained with software ray tracing on a distributed memory, GPU enabled, parallel visualization resource. Using the Texas Advanced Computing Center’s Longhorn cluster which has multi-core CPUs and GPUs with large-scale polygonal data, we find multi-core CPU ray tracing to be significantly faster than both software rasterization and hardware-accelerated rasterization in existing scientific visualization tools with large data.

Keywords: kaust, scidac



G. Chen, V. Kwatra, L.-Y. Wei, C.D. Hansen, E. Zhang. “Design of 2D Time-Varying Vector Fields,” In IEEE Transactions on Visualization and Computer Graphics TVCG, Vol. 18, No. 10, pp. 1717--1730. 2012.
DOI: 10.1109/TVCG.2011.290



M. Kim, G. Chen, C.D. Hansen. “Dynamic particle system for mesh extraction on the GPU,” In Proceedings of the 5th Annual Workshop on General Purpose Processing with Graphics Processing Units, London, England, GPGPU-5, ACM, New York, NY, USA pp. 38--46. 2012.
ISBN: 978-1-4503-1233-2
DOI: 10.1145/2159430.215943

ABSTRACT

Extracting isosurfaces represented as high quality meshes from three-dimensional scalar fields is needed for many important applications, particularly visualization and numerical simulations. One recent advance for extracting high quality meshes for isosurface computation is based on a dynamic particle system. Unfortunately, this state-of-the-art particle placement technique requires a significant amount of time to produce a satisfactory mesh. To address this issue, we study the parallelism property of the particle placement and make use of CUDA, a parallel programming technique on the GPU, to significantly improve the performance of particle placement. This paper describes the curvature dependent sampling method used to extract high quality meshes and describes its implementation using CUDA on the GPU.

Keywords: CUDA, GPGPU, particle systems, volumetric data mesh extraction



T. Martin, G. Chen, S. Musuvathy, E. Cohen, C.D. Hansen. “Generalized Swept Mid-structure for Polygonal Models,” In Proceedings of Eurographics 2012, Vol. 31, No. 2 part 4, pp. 805--814. 2012.
DOI: 10.1111/j.1467-8659.2012.03061.x

ABSTRACT

We introduce a novel mid-structure called the generalized swept mid-structure (GSM) of a closed polygonal shape, and a framework to compute it. The GSM contains both curve and surface elements and has consistent sheet-by-sheet topology, versus triangle-by-triangle topology produced by other mid-structure methods. To obtain this structure, a harmonic function, defined on the volume that is enclosed by the surface, is used to decompose the volume into a set of slices. A technique for computing the 1D mid-structures of these slices is introduced. The mid-structures of adjacent slices are then iteratively matched through a boundary similarity computation and triangulated to form the GSM. This structure respects the topology of the input surface model is a hybrid mid-structure representation. The construction and topology of the GSM allows for local and global simplification, used in further applications such as parameterization, volumetric mesh generation and medical applications.

Keywords: scidac, kaust



M. Schott, T. Martin, A.V.P. Grosset, C. Brownlee, Thomas Hollt, B.P. Brown, S.T. Smith, C.D. Hansen. “Combined Surface and Volumetric Occlusion Shading,” In Proceedings of Pacific Vis 2012, pp. 169--176. 2012.
DOI: 10.1109/PacificVis.2012.6183588

ABSTRACT

In this paper, a method for interactive direct volume rendering is proposed that computes ambient occlusion effects for visualizations that combine both volumetric and geometric primitives, specifically tube shaped geometric objects representing streamlines, magnetic field lines or DTI fiber tracts. The proposed algorithm extends the recently proposed Directional Occlusion Shading model to allow the rendering of those geometric shapes in combination with a context providing 3D volume, considering mutual occlusion between structures represented by a volume or geometry.

Keywords: scidac, vacet, kaust, nvidia



Y. Wan, H. Otsuna, C.-B. Chien, C.D. Hansen. “FluoRender: An Application of 2D Image Space Methods for 3D and 4D Confocal Microscopy Data Visualization in Neurobiology Research,” In Proceedings of Pacific Vis 2012, Incheon, Korea, pp. 201--208. 2012.
DOI: 10.1109/PacificVis.2012.6183592

ABSTRACT

2D image space methods are processing methods applied after the volumetric data are projected and rendered into the 2D image space, such as 2D filtering, tone mapping and compositing. In the application domain of volume visualization, most 2D image space methods can be carried out more efficiently than their 3D counterparts. Most importantly, 2D image space methods can be used to enhance volume visualization quality when applied together with volume rendering methods. In this paper, we present and discuss the applications of a series of 2D image space methods as enhancements to confocal microscopy visualizations, including 2D tone mapping, 2D compositing, and 2D color mapping. These methods are easily integrated with our existing confocal visualization tool, FluoRender, and the outcome is a full-featured visualization system that meets neurobiologists' demands for qualitative analysis of confocal microscopy data.

Keywords: scidac



Y. Wan, H. Otsuna, C.-B. Chien, C.D. Hansen. “Interactive Extraction of Neural Structures with User-Guided Morphological Diffusion,” In Proceedings of the IEEE Symposium on Biological Data Visualization, pp. 1--8. 2012.
DOI: 10.1109/BioVis.2012.6378577

ABSTRACT

Extracting neural structures with their fine details from confocal volumes is essential to quantitative analysis in neurobiology research. Despite the abundance of various segmentation methods and tools, for complex neural structures, both manual and semi-automatic methods are ineffective either in full 3D or when user interactions are restricted to 2D slices. Novel interaction techniques and fast algorithms are demanded by neurobiologists to interactively and intuitively extract neural structures from confocal data. In this paper, we present such an algorithm-technique combination, which lets users interactively select desired structures from visualization results instead of 2D slices. By integrating the segmentation functions with a confocal visualization tool neurobiologists can easily extract complex neural structures within their typical visualization workflow.