EGWR: Eurographics Workshop on Rendering

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https://diglib.eg.org/handle/10.2312/378

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Browsing EGWR: Eurographics Workshop on Rendering by Subject "Applied computing"

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    Adaptive Temporal Sampling for Volumetric Path Tracing of Medical Data
    (The Eurographics Association and John Wiley & Sons Ltd., 2019) Martschinke, Jana; Hartnagel, Stefan; Keinert, Benjamin; Engel, Klaus; Stamminger, Marc; Boubekeur, Tamy and Sen, Pradeep
    Monte-Carlo path tracing techniques can generate stunning visualizations of medical volumetric data. In a clinical context, such renderings turned out to be valuable for communication, education, and diagnosis. Because a large number of computationally expensive lighting samples is required to converge to a smooth result, progressive rendering is the only option for interactive settings: Low-sampled, noisy images are shown while the user explores the data, and as soon as the camera is at rest the view is progressively refined. During interaction, the visual quality is low, which strongly impedes the user's experience. Even worse, when a data set is explored in virtual reality, the camera is never at rest, leading to constantly low image quality and strong flickering. In this work we present an approach to bring volumetric Monte-Carlo path tracing to the interactive domain by reusing samples over time. To this end, we transfer the idea of temporal antialiasing from surface rendering to volume rendering. We show how to reproject volumetric ray samples even though they cannot be pinned to a particular 3D position, present an improved weighting scheme that makes longer history trails possible, and define an error accumulation method that downweights less appropriate older samples. Furthermore, we exploit reprojection information to adaptively determine the number of newly generated path tracing samples for each individual pixel. Our approach is designed for static, medical data with both volumetric and surface-like structures. It achieves good-quality volumetric Monte-Carlo renderings with only little noise, and is also usable in a VR context.
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    PosterChild: Blend-Aware Artistic Posterization
    (The Eurographics Association and John Wiley & Sons Ltd., 2021) Chao, Cheng-Kang; Singh, Karan; Gingold, Yotam; Bousseau, Adrien and McGuire, Morgan
    Posterization is an artistic effect which converts continuous images into regions of constant color with smooth boundaries, often with an artistically recolored palette. Artistic posterization is extremely time-consuming and tedious. We introduce a blend-aware algorithm for generating posterized images with palette-based control for artistic recoloring. Our algorithm automatically extracts a palette and then uses multi-label optimization to find blended-color regions in terms of that palette. We smooth boundaries away from image details with frequency-guided median filtering. We evaluate our algorithm with a comparative user study and showcase its ability to produce compelling posterizations of a variety of inputs. Our parameters provide artistic control and enable cohesive, real-time recoloring after posterization pre-processing.