Chi Xiong

dblp:185/9479 · DBLP profile ↗
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3ranked-venue papers
0as first author
2since 2021 · last 2021
0000-0002-6230-6334ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Graphics, computer vision, multimedia, augmented reality and games · 3 · 2 since 2021Applied, interdisciplinary, general and emerging computing · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer graphics and multimedia
1 paper
Visualization and visual analytics · 50% Geometric modeling and processing · 50%
Interdisciplinary, comprehensive, and emerging computing
2 papers
Computational science and engineering · 100%

Topics — the 3 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Visualization and visual analytics
scientific visualization
0.512021
Vectorizing Quantum Turbulence Vortex-Core Lines for Real-Time Visualization · IEEE Trans. Vis. Comput. Graph. 2021
Geometric modeling and processing
vectorization
0.512021
Vectorizing Quantum Turbulence Vortex-Core Lines for Real-Time Visualization · IEEE Trans. Vis. Comput. Graph. 2021
Computational science and engineering
scientific visualization
0.312018
Towards High-Quality Visualization of Superfluid Vortices · IEEE Trans. Vis. Comput. Graph. 2018

Methods — techniques the papers use, named apart from their topics

iterative graph reduction · 1.0graph-based data structure · 1.0density-guided local optimization · 1.0velocity circulation · 0.3orthogonal-plane strategy · 0.3
YearPublicationVenuePosition
2021 Joint Spinal Centerline Extraction and Curvature Estimation with Row-Wise Classification and Curve Graph Network
Long Huo, Bin Cai 0006, Pengpeng Liang, Zhiyong Sun 0002, Chi Xiong, Chaoshi Niu, Erkang Cheng
MICCAI (5)5
2021 Vectorizing Quantum Turbulence Vortex-Core Lines for Real-Time Visualization
abstract
Vectorizing vortex-core lines is crucial for high-quality visualization and analysis of turbulence. While several techniques exist in the literature, they can only be applied to classical fluids. As quantum fluids with turbulence are gaining attention in physics, extracting and visualizing vortex-core lines for quantum fluids is increasingly desirable. In this article, we develop an efficient vortex-core line vectorization method for quantum fluids enabling real-time visualization of high-resolution quantum turbulence structure. From a dataset obtained through simulation, our technique first identifies vortex nodes based on the circulation field. To vectorize the vortex-core lines interpolating these vortex nodes, we propose a novel graph-based data structure, with iterative graph reduction and density-guided local optimization, to locate sub-grid-scale vortex-core line samples more precisely, which are then vectorized by continuous curves. This vortex-core representation naturally captures complex topology, such as branching during reconnection. Our vectorization approach reduces memory consumption by orders of magnitude, enabling real-time visualization performance. Different types of interactive visualizations are demonstrated to show the effectiveness of our technique, which could help further research on quantum turbulence.
Daoming Liu, Chi Xiong, Xiaopei Liu
IEEE Trans. Vis. Comput. Graph.2
2018 Towards High-Quality Visualization of Superfluid Vortices
abstract
Superfluidity is a special state of matter exhibiting macroscopic quantum phenomena and acting like a fluid with zero viscosity. In such a state, superfluid vortices exist as phase singularities of the model equation with unique distributions. This paper presents novel techniques to aid the visual understanding of superfluid vortices based on the state-of-the-art non-linear Klein-Gordon equation, which evolves a complex scalar field, giving rise to special vortex lattice/ring structures with dynamic vortex formation, reconnection, and Kelvin waves, etc. By formulating a numerical model with theoretical physicists in superfluid research, we obtain high-quality superfluid flow data sets without noise-like waves, suitable for vortex visualization. By further exploring superfluid vortex properties, we develop a new vortex identification and visualization method: a novel mechanism with velocity circulation to overcome phase singularity and an orthogonal-plane strategy to avoid ambiguity. Hence, our visualizations can help reveal various superfluid vortex structures and enable domain experts for related visual analysis, such as the steady vortex lattice/ring structures, dynamic vortex string interactions with reconnections and energy radiations, where the famous Kelvin waves and decaying vortex tangle were clearly observed. These visualizations have assisted physicists to verify the superfluid model, and further explore its dynamic behavior more intuitively.
Xiaopei Liu, Chi Xiong, Xuemiao Xu, Chi-Wing Fu
IEEE Trans. Vis. Comput. Graph.3