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Item 2D Points Curve Reconstruction Survey and Benchmark(The Eurographics Association and John Wiley & Sons Ltd., 2021) Ohrhallinger, Stefan; Peethambaran, Jiju; Parakkat, Amal Dev; Dey, Tamal Krishna; Muthuganapathy, Ramanathan; Bühler, Katja and Rushmeier, HollyCurve reconstruction from unstructured points in a plane is a fundamental problem with many applications that has generated research interest for decades. Involved aspects like handling open, sharp, multiple and non-manifold outlines, run-time and provability as well as potential extension to 3D for surface reconstruction have led to many different algorithms. We survey the literature on 2D curve reconstruction and then present an open-sourced benchmark for the experimental study. Our unprecedented evaluation of a selected set of planar curve reconstruction algorithms aims to give an overview of both quantitative analysis and qualitative aspects for helping users to select the right algorithm for specific problems in the field. Our benchmark framework is available online to permit reproducing the results and easy integration of new algorithms.Item FloodVis: Visualization of Climate Ensemble Flood Projections in Virtual Reality(The Eurographics Association, 2022) Oyshi, Marzan Tasnim; Maleska, Verena; Schanze, Jochen; Bormann, Franziskus; Dachselt, Raimund; Gumhold, Stefan; Dutta, Soumya; Feige, Kathrin; Rink, Karsten; Zeckzer, DirkAnthropogenic greenhouse gas emissions are leading to accelerating climate change, forcing politicians and administrations to take actions to mitigate climate change and adapt to its impacts, such as changes in flood regimes. For European countries, an increasing frequency and severity of extreme rainfall and flood events is expected. However, studies on future flood risks caused by climate change are associated with various uncertainties. The risk simulations are elaborate as they consider (i) climate data ensembles (temperature, precipitation), (ii) hydrological modeling (flood generation), (iii) hydrodynamic modeling (flood conveyance), and (iv) vulnerability modeling (damage assessment) involving a huge amount of data and their handling with Big Data methods. The results are difficult to understand for decision makers. Therefore, FloodVis offers a means of visualizing possible future flood risks in Virtual Reality (VR). The presentation of the results in a VR especially supports the user in understanding the complexity of the dynamics of the risk system enabling the feeling of presence. In FloodVis the user enters into a virtual surrounding to interact with the data, examine the temporal evolution, and compare alternative development pathways. Critical structures that require improved protection can be identified. The user can follow the inundation process in hourly resolution. We evaluated FloodVis through an online and offline user study on the context of whether VR can provide a better visualization of ensemble flood risk data and whether the sense of presence in VR can influence the decision making and help to raise awareness.Item An End-to-end Framework for 3D Capture and Human Digitization with a Single RGB Camera(The Eurographics Association, 2020) Silva, Luiz José Schirmer; Silva, Djalma S. da; Velho, Luiz; Lopes, Hélio; Ritschel, Tobias and Eilertsen, GabrielWe present a low cost and accessible end-to-end framework for 3D modeling and texture capture of Humans using deep neural networks and a single RGB camera. We generate a texture atlas considering a set of multi-view images. We also capture data to generate 3D shape models and finally combine it with the generated textures to obtain a full 3D reconstruction of the human body that can be used in a game engine.Item A Virtual Geographic Environment for the Exploration of Hydro-Meteorological Extremes(The Eurographics Association, 2021) Rink, Karsten; Sen, Özgür Ozan; Hannemann, Marco; Ködel, Uta; Nixdorf, Erik; Weber, Ute; Werban, Ulrike; Schrön, Martin; Kalbacher, Thomas; Kolditz, Olaf; Dutta, Soumya and Feige, Kathrin and Rink, Karsten and Zeckzer, DirkWe propose a Virtual Geographic Environment for the exploration of hydro-meteorological events. Focussing on the catchment of the Müglitz River in south-eastern Germany, a large collection of observation data acquired via a wide range of measurement devices has been integrated in a geographical reference frame for the region. Results of area-wide numerical simulations for both groundwater and soil moisture have been added to the scene and allow for the exploration of the delayed consequences of transient phenomena such as heavy rainfall events and their impact on the catchment scale. Implemented in a framework based on Unity, this study focusses on the concurrent visualisation and synchronised animation of multiple area wide datasets from different environmental compartments. The resulting application allows to explore the region of interest during specific hydrological events for an assessment of the interrelation of processes. As such, it offers the opportunity for knowledge transfer between researchers of different domains as well as for outreach to an interested public.Item Visualization Environment for Analyzing Extreme Rainfall Events: A Case Study(The Eurographics Association, 2023) Kress, James; Afzal, Shehzad; Dasari, Hari Prasad; Ghani, Sohaib; Zamreeq, Arjan; Ghulam, Ayman; Hoteit, Ibrahim; Dutta, Soumya; Feige, Kathrin; Rink, Karsten; Zeckzer, DirkExtreme rainfall events can devastate infrastructure and public life and potentially induce substantial financial and life losses. Although weather alert systems generate early rainfall warnings, predicting the impact areas, duration, magnitude, occurrence, and characterization as an extreme event is challenging. Scientists analyze previous extreme rainfall events to examine the factors such as meteorological conditions, large-scale features, relationships and interactions between large-scale features and mesoscale features, and the success of simulation models in capturing these conditions at different resolutions and their parameterizations. In addition, they may also be interested in understanding the sources of anomalous amounts of moisture that may fuel such events. Many factors play a role in the development of these events, which vary depending on the locations. In this work, we implement a visualization environment that supports domain scientists in analyzing simulation model outputs configured to predict and analyze extreme precipitation events. This environment enables visualization of important local features and facilitates understanding the mechanisms contributing to such events. We present a case study of the Jeddah extreme precipitation event on November 24, 2022, which caused great flooding and infrastructure damage. We also present a detailed discussion about the study's results, feedback from the domain experts, and future extensions.Item Robust Method for Estimating Normals on Point Clouds Using Adaptive Neighborhood Size(The Eurographics Association, 2021) Leal, E.A.; Leal, N.E.; Silva, F. and Gutierrez, D. and RodrÃguez, J. and Figueiredo, M.Normal estimation on sampled curves or surfaces is a basic step of many algorithms in computer graphics, computer vision, and especially in recognition and reconstruction of three dimensional objects. This paper presents a simple and intuitive method for estimating normals on point based surfaces. The method is based on Robust Principal Component Analysis (RPCA) therefore is capable to deal with noisy data and outliers. In order to estimate an accurate normal on a point, our method takes a neighborhood of variable size around the point. The neighborhood size depends on local properties of the sampled surface. It is shown that the estimation of the tangent plane on a point is more accurate using a neighborhood of variable size than using a fixed one.Item 3D Visualization of Sparse Geophysical Data Representing Uncertainty(The Eurographics Association, 2021) Gonçalves, VÃtor; Dias, Paulo; Almeida, Fernando; Madeira, Joaquim; Santos, Beatriz Sousa; Silva, F. and Gutierrez, D. and RodrÃguez, J. and Figueiredo, M.Geophysical data are sparse and by nature difficult to analyze. Usually domain experts use "mental models" to infer missing data according to the surrounding data and their own knowledge. The main goal of this work is to explore the best way to represent uncertainty in geophysical data. Given the sparse nature of the represented data, it is important to provide a 3D volumetric representation of the whole subsoil, based on a geostatistical process. We use kriging interpolation to generate a structured grid from the original sparse data. However, the analysis of such an interpolated representation must be careful, since the uncertainty varies significantly according to the distance to real measurements. We use different representations to emphasize data uncertainty during the analysis stage. The different visualization techniques implemented in our prototype, as well as methods used to simultaneously visualize resistivity and uncertainty information, are presented.Item ExtremeWeatherVis: Visualizing Extreme Weather Events for Multi-City in Virtual Reality to Support Decision Making(The Eurographics Association, 2024) Oyshi, Marzan Tasnim; Schober, Danny; Burkhardt, Juliette-Michelle; Maleska, Verena; Auguszt, Tillmann; Langhans, Linus; Fuchs, Richard Karl; Gumhold, Stefan; Dutta, Soumya; Feige, Kathrin; Rink, Karsten; Nsonga, BaldwinThe occurrence and severity of extreme weather events are changing due to the impact of climate change, resulting in significant hazards to human lives and critical infrastructure. While data are abundant on the consequences of these extreme weather events, it is often challenging to communicate this data to the appropriate people in a way that resonates. In this paper, we present ExtremeWeatherVis to immersively visualize extreme weather events for multiple cities in Virtual Reality allowing user interaction with the temporal evaluation of specific events in day and night cycles from different viewpoints. The current visualization allows users to visualize potential heavy rainfall resulting in pluvial floods and heatwaves for Dresden, Bautzen, and New York. We conducted a user study, followed by a longitudinal study, to explore the effectiveness of our method in supporting decision-making by capturing participants' emotions. The emotional aspects of participants were assessed using three distinct AI models to investigate whether our method supports decision-making by enabling a sense of presence while capturing the emotions of the participants.Item A Practical Male Hair Aging Model(The Eurographics Association, 2020) Volkmann, Diego V.; Walter, Marcelo; Wilkie, Alexander and Banterle, FrancescoThe modeling and rendering of hair in Computer Graphics have seen much progress in the last few years. However, modeling and rendering hair aging, visually seen as the loss of pigments, have not attracted the same attention. We introduce in this paper a biologically inspired hair aging system with two main parts: greying of individual hairs, and time evolution of greying over the scalp. The greying of individual hairs is based on current knowledge about melanin loss, whereas the evolution on the scalp is modeled by segmenting the scalp in regions and defining distinct time frames for greying to occur. Our experimental visual results present plausible results despite the relatively simple model. We validate the results by presenting side by side our results with real pictures of men at different ages.