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LVDIF: a framework for real-time interaction with large volume data

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Abstract

The interest in real-time volume graphics has grown rapidly in the last few years, driven by the increasing demands from both academia and industry. GPU-based volume rendering has been used in a wide variety of fields, including scientific visualization, visual effects, and video games. Similarly, real-time volume editing has been used to build terrain and create visual effects during game development; it has even become an integral part of gameplay in various video games (e.g., Minecraft). Nowadays, as the size of volume data increases, processing large volume data in real time is inevitable in many modern application scenarios. However, manipulation and editing of large volume data are associated with various challenges, such as dramatically increasing memory usage and computational burden. In this paper, we present a framework for interactive manipulation and editing of large volume data to address these challenges. A robust and efficient method for large signed distance function (SDF) volume generation is presented and incorporated into the framework. Also, a complete implementation with specialized GPU optimization is introduced to demonstrate its usefulness and effectiveness—it is included in the framework as well. The framework can be an easy-to-use middleware or a plugin that is able to integrate into game engines for the development of various types of applications (e.g., video games). It can also contribute to the research looking at large volume data from a user-centered perspective (e.g., for human–computer interaction researchers).

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Notes

  1. https://unity.com/.

  2. https://iquilezles.org/www/articles/distfunctions/distfunctions.htm.

  3. https://www.7-zip.org/7z.html.

  4. https://github.com/Chaosikaros/LVDIF.

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Acknowledgements

We thank the reviewers for their valuable time and insightful comments that helped improve our paper. This research was partly funded by Xi’an Jiaotong-Liverpool University Special Key Fund (#KSF-A-03), the National Natural Science Foundation of China (#62272396), and XJTLU Research Development Fund (#RDF-21-02-065, #RDF-19-02-11).

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Authors and Affiliations

  1. Department of Computing, School of Advanced Technology, Xi’an Jiaotong-Liverpool University, Suzhou, China

    Jialin Wang, Nan Xiang, Lingyun Yu & Hai-Ning Liang

  2. Department of Computer Science, University of Liverpool, Liverpool, UK

    Jialin Wang & Navjot Kukreja

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  1. Jialin Wang
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Wang, J., Xiang, N., Kukreja, N. et al. LVDIF: a framework for real-time interaction with large volume data. Vis Comput 39, 3373–3386 (2023). https://doi.org/10.1007/s00371-023-02976-x

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