KWAN-LIU MA


PUBLICATIONS

(A more complete list can be seen at DBLP.)

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Scalable Parallel Distance Field Construction for Large-Scale Applications

Hongfeng Yu, Jinrong Xie, Kwan-Liu Ma, Hemanth Kolla, and Jacqueline H. Chen

IEEE Transactions on Visualization and Computer Graphics
(Presented at VIS 2015)
Volume 21, Number 10, 2015, pp. 1187-1200

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Computing distance fields is fundamental to many scientific and engineering applications. Distance fields can be used to direct analysis and reduce data. In this paper, we present a highly scalable method for computing 3D distance fields on massively parallel distributed memory machines. A new distributed spatial data structure, named parallel distance tree, is introduced to manage the level sets of data and facilitate surface tracking over time, resulting in significantly reduced computation and communication costs for calculating the distance to the surface of interest from any spatial locations ...

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High performance heterogeneous computing for collaborative visual analysis

Kelvin Li, Jia-Kai Chou, and Kwan-Liu Ma

In Proceedings of Sympoisum on Visualization in High Performance Computing
(with SIGGRAPH Asia 2015)
2015

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Visual analysis of large and complex data often requires multiple analysts with diverse expertise and different perspectives to collaborate in order to reveal hidden structures and gain insight in the data. While collaborative visualization allows multiple users to collectively work on the same analytic task, the user side computing devices can be used to share the computation workload for demanding ...

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Volume Rendering with Data Parallel Visualization Frameworks for Emerging High Performance Computing Architectures

Hendrik Schroots and Kwan-Liu Ma

In Proceedings of Symposium on Visualization in High Performance Computing
(with ACM SIGGRAPH Asia 2015)
2015

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Future exascale computing is demanding more and more parallelism
from current software if peak computation rates are to be
realized. However, exploiting this additional parallelism is not trivial.
One approach is to identify finer grained parallelism using data
parallel primitives (DPP). Visualization frameworks such as Dax
and VTK-m are being developed using DPP for this purpose. Our
work presents an exploratory study of how volume rendering maps
to current and future super computing architectures ...

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An Efficient Framework for Generating Storyline Visualizations from Streaming Data

Yuzuru Tanahashi, Chien-Hsin Hsueh, and Kwan-Liu Ma

IEEE Transactions on Visualization and Computer Graphics
(Presented at VIS 2015)
Volume 21, Number 6, 2015, pp. 730-742

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This paper presents a framework for visualizing streaming data. The framework has three components: a new data management scheme for processing and storing the incoming data, a layout construction algorithm specifically designed for incrementally generating storyline visualization from streaming data, and a layout refinement algorithm for improving the legibility of the visualization.
...

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Scalable Visualization of Discrete Velocity Decompositions Using Spatially Organized Histograms

Tyson Neuroth, Franz Sauer, Weixing Wang, Stephane Ethier, and Kwan-Liu Ma

In Proceedings of IEEE LDAV 2015
(Best Paper Honorable Mention Award)
October, 2015

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Visualizing the velocity decomposition of a group of objects has applications to many studied data types, such as Lagrangian-based flow data or geospatial movement data. Traditional visualization techniques are often subject to a trade-off between visual clutter and loss of detail, especially in a large scale setting. The use of 2D velocity histograms can alleviate these issues. While they have ...

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Visual Characterization of Personal Bibliographic Data Using a Botanical Tree Design

Tsai Ling Fung and Kwan-Liu Ma

In Proceedings of IEEE VIS 2015 Workshop on Personal Visualization: Exploring Data in Everyday Life
2015

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This paper presents a preliminary study on egocentric visualization of a bibliographic database. The visualization design is based on a botanic tree metaphor, resulting in a visually interesting and infor- mation rich depiction of one’s research career in terms of publica- tion records. The case studies reveal both the strengths and limita- tions of the current design. ...

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Revealing the Fog-of-War: A Visualization-directed, Uncertainty-aware Approach for Exploring High-dimensional Data

Yang Wang and Kwan-Liu Ma

In Proceedings of IEEE International Conference on BigData 2015
October, 2015

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Dimensionality Reduction (DR) is a crucial tool to facilitate high-dimensional data analysis. As the volume and the variety of features used to describe a phenomenon keeps increasing, DR has become not only desirable but paramount. However, DR can result in unreliable depictions of data. The uncertainties involved in DR may stem from the selection of methods, parameter configurations, and the ...

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Fast Uncertainty-driven Large-scale Volume Feature Extraction on Desktop PCs

Jinrong Xie, Franz Sauer, and Kwan-Liu Ma

In Proceedings of IEEE LDAV 2015
(Best Paper Honorable Mentioned Award)
October, 2015

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The ability to efficiently and accurately extract features of interest is an extremely important tool in the field of scientific visualization as it allows researchers to isolate regions based on their domain knowledge. However, the increasing size of large-scale datasets often forces users to rely on distributed computing environments which have many drawbacks in terms of interaction and convenience. Many ...

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Integrating Predictive Analytics into a Spatiotemporal Epidemic Simulation

Chris Bryan, Xue Wu, Susan Mniszeqski, and Kwan-Liu Ma

In Proceedings of Proceedings of IEEE VAST 2015
2015

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For large simulations, it may not be feasible to test over the entire parameter space, due to time or resource constraints. One solution is to take a granular sampling of the input space and use simpler predictive models (emulators) in between. In this paper, we introduce a workflow and system emulation building, running, and analysis for a large disease simulator. ...

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In Incremental Layout Method for Visualizing Online Dynamic Graphs

Tarik Crnovrsanin, Jacqueline Chu, and Kwan-Liu Ma

In Proceedings of the 23rd International Symposium on Graph Drawing and Network Visualization
(Best Paper Award)
September, 2015

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Graphs provide a visual means for examining relation data and force-directed methods are often used to lay out graphs for viewing. Making sense of a dynamic graph as it evolves over time is challenging, and previous force-directed methods were designed for static graphs. In this paper, we present an incremental version of a multilevel multi-pole layout method with a refinement scheme incorporated, which enables us to visualize online dynamic networks while maintaining a mental map of the graph structure. ...

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Design and Effects of Personal Visualizations

Shimin Wang, Yuzuru Tanahashi, Nick Leaf, and Kwan-Liu Ma

IEEE Computer Graphics and Applications
Volume 35, Number 4, 2015, pp. 82-

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In an effort to determine what elements need to be considered when designing personal visualizations, this research study explores how users react to different personal visualization designs. The authors present three distinct personal visualization designs (Timeline, Spark, and Bouquet) for visualizing Facebook user data. In a scenario-based user study, they interview participants to evaluation each design's utility, exploring the visualization of the users' own data, comparing two personal visualizations, and analyzing a series of personal visualizations ...

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Stock Lamp: An Engagement-Versatile Visualization Design

Yuzuru Tanahashi and Kwan-Liu Ma

In Proceedings of CHI 2015
(Best of CHI Honorable Mention Award)
ACM, April, 2015

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Design methodologies for information visualizations are typically
based on the assumption that the users will be fully engaged in the visual exploration of the displayed information. However, recent research suggests that there is an increasing diversity in how users engage with modern visualizations, and that the traditional design theories do not always satisfy the varied users needs. In this paper, we present a new design concept, engagement-versatile design, for visualizations that target users with a variety of engagement styles ...

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Advanced Lighting for Unstructured-Grid Data Visualization

Min Shih, Yubo Zhang, and Kwan-Liu Ma

In Proceedings of PacificVis 2015
April, 2015

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The benefits of using advanced illumination models in volume visualization have been demonstrated by many researchers. Interactive volume rendering incorporated with advanced lighting has been achieved with GPU acceleration for regular-grid volume data, making volume visualization even more appealing as a tool for 3D data exploration. This paper presents an interactive illumination strategy, which is specially designed and optimized for volume visualization of unstructured-grid data ...

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Spherical Layout and Rendering Methods for Immersive Graph Visualization

Oh-Hyun Kwon, Chris Muelder, Kyungwon Lee, and Kwan-Liu Ma

In Proceedings of IEEE PacificVis 2015 -- Vis Notes
(Best VisNote Paper Award)
April, 2015

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While virtual reality has been researched in many ways for spatial
and scientific visualizations, comparatively little has been explored
for visualizations of more abstract kinds of data. In particular, stereoscopic and VR environments for graph visualization have
only been applied as limited extensions to standard 2D techniques
(e.g. using stereoscopy for highlighting). In this work, we explore a
new, immersive approach for graph visualization, designed specifically for virtual reality environments ...

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Content-Aware Model Resizing with Symmetry-Preservation

Chunxia Xiao, Liqiang Jin, Yongwei Nie, Renfang Wang, Hanqiu Sun, and Kwan-Liu Ma

The Visual Computer
Volume 31, Number 2, 2015, pp. 155-167

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This paper presents a new model resizing approach intended for preservation of important geometric content and geometric symmetries of the model to be resized. We first extract high-level symmetric regions and other low-level salient regions from the input model. Then, we map the extracted low-level and high-level geometry information to a protective tetrahedral mesh around the model, and we define a symmetry-preserving and content-aware resizing function on the tetrahedral mesh using 3D mean value coordinates space deformation ...