Computer Graphics & Visual Computing (CGVC 2019)

A special issue of Computers (ISSN 2073-431X).

Deadline for manuscript submissions: closed (20 January 2020) | Viewed by 17722

Special Issue Editors


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Guest Editor
School of Computer Science and Electronic Engineering, Bangor University, Bangor LL57 1UT, UK
Interests: interactive data visualization; visual analytics
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E-Mail Website
Guest Editor
Department of Computer Science, College of Science, Swansea University, Singleton Park, Swansea SA2 8PP, UK
Interests: visual analytics; machine learning; digital geometry processing; pattern recognition and vision; multi-dimensional data analysis; information retrieval and indexing
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
School of Computer Science and Electronic Engineering, Bangor University, Dean Street, Bangor LL57 1UT, Gwynedd, UK
Interests: medical imaging (X-ray imaging, CT, positron emission tomography, ultrasound, MRI); evolutionary algorithms; inverse problems; computer graphics; GPU programming; image and signal processing
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Computer Graphics & Visual Computing (CGVC) 2019, hosted by Bangor University in the UK, 12–13 September 2019, is the 37th annual gathering on computer graphics, visualisation, and visual computing, organised by the Eurographics UK Chapter. For more information about the conference, please use this link: http://www.eguk.org.uk/CGVC2019/

Selected papers that are presented at the conference are invited to be submitted as extended versions to this Special Issue of the journal Computers after the conference. Submitted papers should be extended to the size of regular research or review articles, with a 50% extension of new results. All submitted papers will undergo a standard peer-review procedure. Accepted papers will be published in open access format in Computers and will be collected on this Special Issue website. There is no page limitation.

Please prepare and format your paper according to the Instructions for Authors. Use the LaTeX or Microsoft Word template file of the journal (both are available from the Instructions for Authors page). Manuscripts should be submitted online via our susy.mdpi.com editorial system.

Prof. Jonathan Roberts
Dr. Gary KL Tam
Dr. Franck P. Vidal
Guest Editors

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Published Papers (3 papers)

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Research

16 pages, 18341 KiB  
Article
Accelerating Surface Tension Calculation in SPH via Particle Classification and Monte Carlo Integration
by Fernando Zorilla, Marcel Ritter, Johannes Sappl, Wolfgang Rauch and Matthias Harders
Computers 2020, 9(2), 23; https://doi.org/10.3390/computers9020023 - 29 Mar 2020
Cited by 6 | Viewed by 4850
Abstract
Surface tension has a strong influence on the shape of fluid interfaces. We propose a method to calculate the corresponding forces efficiently. In contrast to several previous approaches, we discriminate to this end between surface and non-surface SPH particles. Our method effectively smooths [...] Read more.
Surface tension has a strong influence on the shape of fluid interfaces. We propose a method to calculate the corresponding forces efficiently. In contrast to several previous approaches, we discriminate to this end between surface and non-surface SPH particles. Our method effectively smooths the fluid interface, minimizing its curvature. We make use of an approach inspired by Monte Carlo integration to estimate local normals as well as curvatures, based on which the force can be calculated. We compare different sampling schemes for the Monte Carlo approach, for which a Halton sequence performed best. Our overall technique is applicable, but not limited to 2D and 3D simulations, and can be coupled with any common SPH formulation. It outperforms prior approaches with regard to total computation time per time step in dynamic scenes. Additionally, it is adjustable for higher quality in small scale scenes with dominant surface tension effects. Full article
(This article belongs to the Special Issue Computer Graphics & Visual Computing (CGVC 2019))
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20 pages, 4487 KiB  
Article
Virtual Forestry Generation: Evaluating Models for Tree Placement in Games
by Benjamin Williams, Panagiotis D. Ritsos and Christopher Headleand
Computers 2020, 9(1), 20; https://doi.org/10.3390/computers9010020 - 13 Mar 2020
Cited by 3 | Viewed by 5546
Abstract
A handful of approaches have been previously proposed to generate procedurally virtual forestry for virtual worlds and computer games, including plant growth models and point distribution methods. However, there has been no evaluation to date which assesses how effective these algorithms are at [...] Read more.
A handful of approaches have been previously proposed to generate procedurally virtual forestry for virtual worlds and computer games, including plant growth models and point distribution methods. However, there has been no evaluation to date which assesses how effective these algorithms are at modelling real-world phenomena. In this paper, we tackle this issue by evaluating three algorithms used in the generation of virtual forests—a randomly uniform point distribution method (control), a plant competition model, and an iterative random point distribution technique. Our results show that a plant competition model generated more believable content when viewed from an aerial perspective. Interestingly, however, we also found that a randomly uniform point distribution method produced forestry which was rated higher in playability and photorealism, when viewed from a first-person perspective. We conclude that the objective of the game designer is important to consider when selecting an algorithm to generate forestry, as the algorithms produce forestry that is perceived differently. Full article
(This article belongs to the Special Issue Computer Graphics & Visual Computing (CGVC 2019))
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25 pages, 44465 KiB  
Article
Hash-Based Hierarchical Caching and Layered Filtering for Interactive Previews in Global Illumination Rendering
by Thorsten Roth, Martin Weier, Pablo Bauszat, André Hinkenjann and Yongmin Li
Computers 2020, 9(1), 17; https://doi.org/10.3390/computers9010017 - 4 Mar 2020
Cited by 1 | Viewed by 6171
Abstract
Modern Monte-Carlo-based rendering systems still suffer from the computational complexity involved in the generation of noise-free images, making it challenging to synthesize interactive previews. We present a framework suited for rendering such previews of static scenes using a caching technique that builds upon [...] Read more.
Modern Monte-Carlo-based rendering systems still suffer from the computational complexity involved in the generation of noise-free images, making it challenging to synthesize interactive previews. We present a framework suited for rendering such previews of static scenes using a caching technique that builds upon a linkless octree. Our approach allows for memory-efficient storage and constant-time lookup to cache diffuse illumination at multiple hitpoints along the traced paths. Non-diffuse surfaces are dealt with in a hybrid way in order to reconstruct view-dependent illumination while maintaining interactive frame rates. By evaluating the visual fidelity against ground truth sequences and by benchmarking, we show that our approach compares well to low-noise path-traced results, but with a greatly reduced computational complexity, allowing for interactive frame rates. This way, our caching technique provides a useful tool for global illumination previews and multi-view rendering. Full article
(This article belongs to the Special Issue Computer Graphics & Visual Computing (CGVC 2019))
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