Jing Nathan Yan, Tianqi Liu, Justin Chiu, Jiaming Shen, Zhen Qin, Yue Yu, Charumathi Lakshmanan, Yair Kurzion, Alexander Rush, Jialu Liu, Michael Bendersky. Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2024.

We introduce a new approach for mapping texture on volumetric iso-surfaces and parametric surfaces. Our approach maps 2D images on surfaces while maintaining continuity and preserving the size of the mapped images on the models. Our approach is fully automatic. It eliminates the need for manual mapping of texture maps. We use the curvature of a surface at a point in order to continuously vary the scale of the mapped image. This makes our approach dependent only on local attributes of a point (position, normal and its derivatives) and independent of the global shape and topology of an object. Our method can map high resolution images on low resolution volumes, hence enhancing the visual appearance of rendered volume data. We describe a general framework useful for all surface types that have a C/sup 1/ continuous normal. We demonstrate the new method for painting volume data and for mapping cavities on volume data.

This paper advocates the use of a group of renderers rather than any specific rendering method. We describe a bundle containing four alternative approaches to visualizing volume data. One new approach uses realistic volumetric gas rendering techniques to produce photo-realistic images and animations. The second uses ray casting that is based on a simpler illumination model and is mainly centered around a versatile new tool for the design of transfer functions. The third method employs a simple illumination model and rapid rendering mechanisms to provide efficient preview capabilities. The last one reduces data magnitude by displaying the most visible components and exploits rendering hardware to provide real time browsing capabilities. We show that each rendering tool provides a unique service and demonstrate the combined utility of our group of volume renderers in computational fluid dynamic (CFD) visualization. While one tool allows the explorer to render rapidly for navigation through the data, another tool allows one to emphasize data features (e.g., shock waves), and yet another tool allows one to realistically render the data. We believe that only through the deployment of groups of renderers will the scientist be well served and equipped to form numerous perspectives of the same dataset, each providing different insights into the data.>

The paper describes three alternative volume rendering approaches to visualizing computational fluid dynamics (CFD) data. One new approach uses realistic volumetric gas rendering techniques to produce photo-realistic images and animations from scalar CFD data. The second uses ray casting that is based an a sampler illumination model and is mainly centered around a versatile new tool for the design of transfer functions. The third method employs a simple illumination model and rapid rendering mechanisms to provide efficient preview capabilities. These tools provide a large range of volume rendering capabilities to be used by the CFD explorer to render rapidly for navigation through the data, to emphasize data features (e.g., shock waves) with a specific transfer function, or to present a realistic rendition of the model.>