Guoning Chen - Academia.edu (original) (raw)

Papers by Guoning Chen

Computer Graphics Forum, 2021

We introduce the curve complexity heuristic (CCH), a KD‐tree construction strategy for 3D curves,... more We introduce the curve complexity heuristic (CCH), a KD‐tree construction strategy for 3D curves, which enables interactive exploration of neighborhoods in dense and large line datasets. It can be applied to searches of k‐nearest curves (KNC) as well as radius‐nearest curves (RNC). The CCH KD‐tree construction consists of two steps: (i) 3D curve decomposition that takes into account curve complexity and (ii) KD‐tree construction, which involves a novel splitting and early termination strategy. The obtained KD‐tree allows us to improve the speed of existing neighborhood search approaches by at least an order of magnitude (i. e., 28×for KNC and 12×for RNC with 98% accuracy) by considering local curve complexity. We validate this performance with a quantitative evaluation of the quality of search results and computation time. Also, we demonstrate the usefulness of our approach for supporting various applications such as interactive line queries, line opacity optimization, and line abst...

ACM Transactions on Graphics, Jul 27, 2015

Computer Graphics Forum, Apr 11, 2017

IEEE Transactions on Visualization and Computer Graphics, Jul 1, 2016

ACM Transactions on Graphics, Nov 20, 2017

Computer Graphics Forum, 2017

Springer eBooks, Nov 14, 2011

ABSTRACT Asymmetric tensor fields present new challenges for visualization techniques such as hyp... more ABSTRACT Asymmetric tensor fields present new challenges for visualization techniques such as hyperstreamline placement and glyph packing. This is because the physical behaviors of the tensors are fundamentally different inside real domains where eigenvalues are real and complex domains where eigenvalues are complex. We present a hybrid visualization approach in which hyperstreamlines are used to illustrate the tensors in the real domains while glyphs are employed for complex domains. This enables an effective visualization of the flow patterns everywhere and also provides a more intuitive illustration of elliptical flow patterns in the complex domains. The choice of the types of representation for different types of domains is motivated by the physical interpretation of asymmetric tensors in the context of fluid mechanics, i.e., when the tensor field is the velocity gradient tensor. In addition, we encode the tensor magnitude to the size of the glyphs and density of hyperstreamlines. We demonstrate the effectiveness of our visualization techniques with real-world engine simulation data.

Streamline seeding algorithms have a long and rich history dating back over two decades. And in r... more Streamline seeding algorithms have a long and rich history dating back over two decades. And in recent years algorithms for stream surface placement have been developed. However, stream ribbons have been generally overlooked. We present, to our knowledge, the first stream ribbon seeding strategy. Stream ribbons are a tool for visualizing vector fields and are a common extension of streamlines with the added benefit of conveying a fluid’s twisting motion along the direction of flow. Presented in this short paper is a novel strategy for seeding stream ribbons in vector fields. The strategy exploits the flow’s local helicity, an important property of flow identified over 40 years ago, to guide ribbon seeding. Seed points are prioritised based on a derived helicity field. A selection of user options including adjusting ribbon width, separating distance, and ribbon length filtering are applied to support visualization and cater to the users interests. A filtering method is also presented...