IEEE Computer Graphics and Applications最新文献

We introduce a workflow for the visual assessment of interobserver variability in medical image segmentation. Image segmentation is a crucial step in the diagnosis, prognosis, and treatment of many diseases. Despite the advancements in autosegmentation, clinical practice widely relies on manual delineations performed by radiologists. Our work focuses on designing a solution for understanding the radiologists' thought processes during segmentation and for unveiling reasons that lead to interobserver variability. To this end, we propose a visual analysis tool connecting multiple radiologists' delineation processes with their outcomes, and we demonstrate its potential in a case study.

We present an interactive visual analysis tool for analyzing the spread of wildfires and what influences their evolution. Multiple time-varying 3-D scalar and vector fields are investigated and related to each other to identify causes of atypical fire spread. We present a visual analysis approach that allows for a comparative analysis of multiple runs of a simulation ensemble on different levels of detail. Overview visualizations combined with volume renderings and flow visualizations provide an intuitive understanding of the fire spread.

Material appearance is largely determined by complex light attenuation processes. The distinct bluish colorations that can be observed when light is transmitted through snow are among the most striking outcomes of these processes. In this article, we present a method for the predictive rendering of this phenomenon taking into account the variability of snow's physical and morphological characteristics. To achieve that, we employ an approach centered on the effective use of spectral transmittance data obtained using a first-principles light transport model for snow. The suitability of the proposed method to rendering applications is illustrated through the synthesis of images depicting the bluish appearance of snow under different illumination conditions.

Many subsystems of Earth are constantly monitored in space and time and undergo continuous anthropogenic interventions. However, research into this transformation remains largely inaccessible to the public due to the complexity of the Big Data generated by models and Earth observation. To overcome this barrier, we present the Leipzig Explorer of Earth Data Cubes (lexcube.org), an interactive Earth data visualization that allows users to explore terabyte-scale datasets with minimal latency through space, time, variables, and model variants. With over 2800 users and 163,000 API requests since its public release in May 2022, lexcube.org is a novel interactive data cube visualization that embraces the concept of "data cubes," enabling an equal treatment of space and time. We expect this development to be particularly relevant for the emerging exascale Digital Twins of Earth, as interactive visualizations in real-time could remove access barriers and help democratize Earth system sciences.

This article describes the design and evaluation of a virtual field trip on the topic of radioactive waste management research for university education. We created an interactive virtual tour through the Mont Terri underground research laboratory by enhancing the virtual experiment information system, designed for domain experts, with background information, illustrations, tasks, tests, and an improved user interface. To put the tour's content into context, a conventional introductory presentation on the final disposal of radioactive waste was added. A user study with 22 participants proved a good perceived usability of the virtual tour and the virtual field trip's ability to transfer knowledge. These results suggest a benefit of employing virtual field trips in geoscientific university courses. In addition, it is conceivable to use the virtual field trip as a tool for science communication in the context of participatory processes during nuclear waste disposal site selection processes.

This article presents an interactive panoramic ray tracing method for rendering real-time realistic lighting and shadow effects when virtual objects are inserted in 360$^{circ }$∘ RGBD videos. First, we approximate the geometry of the real scene. We propose a sparse sampling ray generation method to speed up the tracing process by reducing the number of rays that need to be emitted in ray tracing. After that, an irradiance estimation channel is introduced to generate noisy Monte Carlo images. Finally, the final result is smoothed and synthesized by interpolation, temporal filtering, and differential rendering. We tested our method in a number of natural and synthesized scenes and compared our method with results from ground truth and image-based illumination methods. The results show that our method can generate visually realistic frames for dynamic virtual objects in 360$^{circ }$∘ RGBD videos in real time, making the rendering results more natural and believable.

Computing occluding contours is often a crucial step in stroke-based artistic 3-D stylization for movies, video games, and visualizations. However, many existing applications use only simple curve stylization techniques, such as thin black lines or hand-animated strokes. This is because sophisticated procedural stylization requires accurate curve topology, which has long been an unsolved research problem. This article describes a recent theoretical breakthrough in the topology problem. Specifically, the new theory points out that existing contour algorithms often generate curves that cannot have any valid visibility, and new algorithms show how to correct the problem. This article surveys classes of algorithms that can compute contours accurately and identifies new research opportunities.