37-Issue 1

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https://diglib.eg.org/handle/10.2312/2632119

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Interactive Large‐Scale Procedural Forest Construction and Visualization Based on Particle Flow Simulation
(© 2018 The Eurographics Association and John Wiley & Sons Ltd., 2018) Kohek, Štefan; Strnad, Damjan; Chen, Min and Benes, Bedrich
Interactive visualization of large forest scenes is challenging due to the large amount of geometric detail that needs to be generated and stored, particularly in scenarios with a moving observer such as forest walkthroughs or overflights. Here, we present a new method for large‐scale procedural forest generation and visualization at interactive rates. We propose a hybrid approach by combining geometry‐based and volumetric modelling techniques with gradually transitioning level of detail (LOD). Nearer trees are constructed using an extended particle flow algorithm, in which particle trails outline the tree ramification in an inverse direction, i.e. from the leaves towards the roots. Reduced geometric representation of a tree is obtained by subsampling the trails. For distant trees, a new volumetric rendering technique in pixel‐space is introduced, which avoids geometry formation altogether and enables visualization of vast forest areas with millions of unique trees. We demonstrate that a GPU‐based implementation of the proposed method provides interactive frame rates in forest overflight scenarios, where new trees are constructed and their LOD adjusted on the fly.Interactive visualization of large forest scenes is challenging due to the large amount of geometric detail that needs to be generated and stored, particularly in scenarios with a moving observer such as forest walkthroughs or overflights. Here, we present a new method for large‐scale procedural forest generation and visualization at interactive rates. We propose a hybrid approach by combining geometry‐based and volumetric modelling techniques with gradually transitioning level of detail (LOD). Nearer trees are constructed using an extended particle flow algorithm, in which particle trails outline the tree ramification in an inverse direction, i.e. from the leaves towards the roots. Reduced geometric representation of a tree is obtained by subsampling the trails. For distant trees, a new volumetric rendering technique in pixel‐space is introduced, which avoids geometry formation altogether and enables visualization of vast forest areas with millions of unique trees.
A Visualization Framework and User Studies for Overloaded Orthogonal Drawings
(© 2018 The Eurographics Association and John Wiley & Sons Ltd., 2018) Didimo, Walter; Kornaropoulos, Evgenios M.; Montecchiani, Fabrizio; Tollis, Ioannis G.; Chen, Min and Benes, Bedrich
Overloaded orthogonal drawing (OOD) is a recent graph visualization style specifically conceived for directed graphs. It merges the advantages of some popular drawing conventions like layered drawings and orthogonal drawings, and provides additional support for some common analysis tasks. We present a visualization framework called , which implements algorithms and graphical features for the OOD style. Besides the algorithm for acyclic digraphs, the DAGView framework implements extensions to visualize both digraphs with cycles and undirected graphs, with the additional possibility of taking into account user preferences and constraints. It also supports an interactive visualization of clustered digraphs, based on the use of strongly connected components. Moreover, we describe an experimental user study, aimed to investigate the usability of OOD within the DAGView framework. The results of our study suggest that OOD can be effectively exploited to perform some basic tasks of analysis in a faster and more accurate way when compared to other drawing styles for directed graphs.Overloaded orthogonal drawing (OOD) is a recent graph visualization style specifically conceived for directed graphs. It merges the advantages of some popular drawing conventions like layered drawings and orthogonal drawings, and provides additional support for some common analysis tasks. We present a visualization framework called , which implements algorithms and graphical features for the OOD style. Besides the algorithm for acyclic digraphs, the DAGView framework implements extensions to visualize both digraphs with cycles and undirected graphs, with the additional possibility of taking into account user preferences and constraints.
Human Factors in Streaming Data Analysis: Challenges and Opportunities for Information Visualization
(© 2018 The Eurographics Association and John Wiley & Sons Ltd., 2018) Dasgupta, Aritra; Arendt, Dustin L.; Franklin, Lyndsey R.; Wong, Pak Chung; Cook, Kristin A.; Chen, Min and Benes, Bedrich
Real‐world systems change continuously. In domains such as traffic monitoring or cyber security, such changes occur within short time scales. This results in a streaming data problem and leads to unique challenges for the human in the loop, as analysts have to ingest and make sense of dynamic patterns in real time. While visualizations are being increasingly used by analysts to derive insights from streaming data, we lack a thorough characterization of the human‐centred design problems and a critical analysis of the state‐of‐the‐art solutions that exist for addressing these problems. In this paper, our goal is to fill this gap by studying how the state of the art in streaming data visualization handles the challenges and reflect on the gaps and opportunities. To this end, we have three contributions in this paper: (i) problem characterization for identifying domain‐specific goals and challenges for handling streaming data, (ii) a survey and analysis of the state of the art in streaming data visualization research with a focus on how visualization design meets challenges specific to change perception and (iii) reflections on the design trade‐offs, and an outline of potential research directions for addressing the gaps in the state of the art.Real‐world systems change continuously. In domains such as traffic monitoring or cyber security, such changes occur within short time scales. This results in a streaming data problem and leads to unique challenges for the human in the loop, as analysts have to ingest and make sense of dynamic patterns in real time. While visualizations are being increasingly used by analysts to derive insights from streaming data, we lack a thorough characterization of the human‐centred design problems and a critical analysis of the state‐of‐the‐art solutions that exist for addressing these problems.
Uniformization and Density Adaptation for Point Cloud Data Via Graph Laplacian
(© 2018 The Eurographics Association and John Wiley & Sons Ltd., 2018) Luo, Chuanjiang; Ge, Xiaoyin; Wang, Yusu; Chen, Min and Benes, Bedrich
Point cloud data is one of the most common types of input for geometric processing applications. In this paper, we study the point cloud density adaptation problem that underlies many pre‐processing tasks of points data. Specifically, given a (sparse) set of points sampling an unknown surface and a target density function, the goal is to adapt to match the target distribution. We propose a simple and robust framework that is effective at achieving both local uniformity and precise global density distribution control. Our approach relies on the Gaussian‐weighted graph Laplacian and works purely in the points setting. While it is well known that graph Laplacian is related to mean‐curvature flow and thus has denoising ability, our algorithm uses certain information encoded in the graph Laplacian that is orthogonal to the mean‐curvature flow. Furthermore, by leveraging the natural scale parameter contained in the Gaussian kernel and combining it with a simulated annealing idea, our algorithm moves points in a multi‐scale manner. The resulting algorithm relies much less on the input points to have a good initial distribution (neither uniform nor close to the target density distribution) than many previous refinement‐based methods. We demonstrate the simplicity and effectiveness of our algorithm with point clouds sampled from different underlying surfaces with various geometric and topological properties.Point cloud data is one of the most common types of input for geometric processing applications. In this paper, we study the point cloud density adaptation problem that underlies many pre‐processing tasks of points data. Specifically, given a (sparse) set of points sampling an unknown surface and a target density function, the goal is to adapt to match the target distribution. We propose a simple and robust framework that is effective at achieving both local uniformity and precise global density distribution control. Our approach relies on the Gaussian‐weighted graph Laplacian and works purely in the points setting. While it is well known that graph Laplacian is related to mean‐curvature flow and thus has denoising ability, our algorithm uses certain information encoded in the graph Laplacian that is orthogonal to the mean‐curvature flow. Furthermore, by leveraging the natural scale parameter contained in the Gaussian kernel and combining it with a simulated annealing idea, our algorithm moves points in a multi‐scale manner.
A Survey on Multimodal Medical Data Visualization
(© 2018 The Eurographics Association and John Wiley & Sons Ltd., 2018) Lawonn, K.; Smit, N.N.; Bühler, K.; Preim, B.; Chen, Min and Benes, Bedrich
Multi‐modal data of the complex human anatomy contain a wealth of information. To visualize and explore such data, techniques for emphasizing important structures and controlling visibility are essential. Such fused overview visualizations guide physicians to suspicious regions to be analysed in detail, e.g. with slice‐based viewing. We give an overview of state of the art in multi‐modal medical data visualization techniques. Multi‐modal medical data consist of multiple scans of the same subject using various acquisition methods, often combining multiple complimentary types of information. Three‐dimensional visualization techniques for multi‐modal medical data can be used in diagnosis, treatment planning, doctor–patient communication as well as interdisciplinary communication. Over the years, multiple techniques have been developed in order to cope with the various associated challenges and present the relevant information from multiple sources in an insightful way. We present an overview of these techniques and analyse the specific challenges that arise in multi‐modal data visualization and how recent works aimed to solve these, often using smart visibility techniques. We provide a taxonomy of these multi‐modal visualization applications based on the modalities used and the visualization techniques employed. Additionally, we identify unsolved problems as potential future research directions.Multi‐modal data of the complex human anatomy contain a wealth of information. To visualize and explore such data, techniques for emphasizing important structures and controlling visibility are essential. Such fused overview visualizations guide physicians to suspicious regions to be analysed in detail, e.g. with slice‐based viewing. We give an overview of state of the art in multi‐modal medical data visualization techniques. Multi‐modal medical data consist of multiple scans of the same subject using various acquisition methods, often combining multiple complimentary types of information. Three‐dimensional visualization techniques for multi‐modal medical data can be used in diagnosis, treatment planning, doctor–patient communication as well as interdisciplinary communication.
Tree Growth Modelling Constrained by Growth Equations
(© 2018 The Eurographics Association and John Wiley & Sons Ltd., 2018) Yi, Lei; Li, Hongjun; Guo, Jianwei; Deussen, Oliver; Zhang, Xiaopeng; Chen, Min and Benes, Bedrich
Modelling and simulation of tree growth that is faithful to the living environment and numerically consistent to botanic knowledge are important topics for realistic modelling in computer graphics. The realism factors concerned include the effects of complex environment on tree growth and the reliability of the simulation in botanical research, such as horticulture and agriculture. This paper proposes a new approach, namely, integrated growth modelling, to model virtual trees and simulate their growth by enforcing constraints of environmental resources and tree morphological properties. Morphological properties are integrated into a growth equation with different parameters specified in the simulation, including its sensitivity to light, allocation and usage of received resources and effects on its environment. The growth equation guarantees that the simulation procedure numerically matches the natural growth phenomenon of trees. With this technique, the growth procedures of diverse and realistic trees can also be modelled in different environments, such as resource competition among multiple trees.Modelling and simulation of tree growth that is faithful to the living environment and numerically consistent to botanic knowledge are important topics for realistic modelling in computer graphics. The realism factors concerned include the effects of complex environment on tree growth and the reliability of the simulation in botanical research, such as horticulture and agriculture. This paper proposes a new approach, namely, integrated growth modelling, to model virtual trees and simulate their growth by enforcing constraints of environmental resources and tree morphological properties. Morphological properties are integrated into a growth equation with different parameters specified in the simulation, including its sensitivity to light, allocation and usage of received resources and effects on its environment. The growth equation guarantees that the simulation procedure numerically matches the natural growth phenomenon of trees.
CorrelatedMultiples: Spatially Coherent Small Multiples With Constrained Multi‐Dimensional Scaling
(© 2018 The Eurographics Association and John Wiley & Sons Ltd., 2018) Liu, Xiaotong; Hu, Yifan; North, Stephen; Shen, Han‐Wei; Chen, Min and Benes, Bedrich
Displaying small multiples is a popular method for visually summarizing and comparing multiple facets of a complex data set. If the correlations between the data are not considered when displaying the multiples, searching and comparing specific items become more difficult since a sequential scan of the display is often required. To address this issue, we introduce CorrelatedMultiples, a spatially coherent visualization based on small multiples, where the items are placed so that the distances reflect their dissimilarities. We propose a constrained multi‐dimensional scaling (CMDS) solver that preserves spatial proximity while forcing the items to remain within a fixed region. We evaluate the effectiveness of our approach by comparing CMDS with other competing methods through a controlled user study and a quantitative study, and demonstrate the usefulness of CorrelatedMultiples for visual search and comparison in three real‐world case studies.
Easy Generation of Facial Animation Using Motion Graphs
(© 2018 The Eurographics Association and John Wiley & Sons Ltd., 2018) Serra, J.; Cetinaslan, O.; Ravikumar, S.; Orvalho, V.; Cosker, D.; Chen, Min and Benes, Bedrich
Facial animation is a time‐consuming and cumbersome task that requires years of experience and/or a complex and expensive set‐up. This becomes an issue, especially when animating the multitude of secondary characters required, e.g. in films or video‐games. We address this problem with a novel technique that relies on motion graphs to represent a landmarked database. Separate graphs are created for different facial regions, allowing a reduced memory footprint compared to the original data. The common poses are identified using a Euclidean‐based similarity metric and merged into the same node. This process traditionally requires a manually chosen threshold, however, we simplify it by optimizing for the desired graph compression. Motion synthesis occurs by traversing the graph using Dijkstra's algorithm, and coherent noise is introduced by swapping some path nodes with their neighbours. Expression labels, extracted from the database, provide the control mechanism for animation. We present a way of creating facial animation with reduced input that automatically controls timing and pose detail. Our technique easily fits within video‐game and crowd animation contexts, allowing the characters to be more expressive with less effort. Furthermore, it provides a starting point for content creators aiming to bring more life into their characters.Facial animation is a time‐consuming and cumbersome task that requires years of experience and/or a complex and expensive set‐up. This becomes an issue, especially when animating the multitude of secondary characters required, e.g. in films or video‐games. We address this problem with a novel technique that relies on motion graphs to represent a landmarked database. Separate graphs are created for different facial regions, allowing a reduced memory footprint compared to the original data. This process traditionally requires a manually chosen threshold, however, we simplify it by optimizing for the desired graph compression. Motion synthesis occurs by traversing the graph, with coherent noise introduced by varying the optimal path that connects the desired nodes. Expression labels, extracted from the database, provide an intuitive control mechanism for animation. Our technique easily fits within video‐game and crowd animation contexts, allowing the characters to be more expressive with less effort.
Story Albums: Creating Fictional Stories From Personal Photograph Sets
(© 2018 The Eurographics Association and John Wiley & Sons Ltd., 2018) Radiano, O.; Graber, Y.; Mahler, M.; Sigal, L.; Shamir, A.; Chen, Min and Benes, Bedrich
We present a method for the automatic creation of fictional storybooks based on personal photographs. Unlike previous attempts that summarize such collections by picking salient or diverse photos, or creating personal literal narratives, we focus on the creation of fictional stories. This provides new value to users, as well as an engaging way for people (especially children) to experience their own photographs. We use a graph model to represent an artist‐generated story, where each node is a ‘frame’, akin to frames in comics or storyboards. A node is described by story elements, comprising actors, location, supporting objects and time. The edges in the graph encode connections between these elements and provide the discourse of the story. Based on this construction, we develop a constraint satisfaction algorithm for one‐to‐one assignment of nodes to photographs. Once each node is assigned to a photograph, a visual depiction of the story can be generated in different styles using various templates. We show results of several fictional visual stories created from different personal photo sets and in different styles.We present a method for the automatic creation of fictional storybooks based on personal photographs. Unlike previous attempts that summarize such collections by picking salient or diverse photos, or creating personal literal narratives, we focus on the creation of fictional stories. This provides new value to users, as well as an engaging way for people (especially children) to experience their own photographs. We use a graph model to represent an artist‐generated story, where each node is a ‘frame’, akin to frames in comics or storyboards. A node is described by story elements, comprising actors, location, supporting objects and time. The edges in the graph encode connections between these elements and provide the discourse of the story. Based on this construction, we develop a constraint satisfaction algorithm for one‐to‐one assignment of nodes to photographs. Once each node is assigned to a photograph, a visual depiction of the story can be generated in different styles using various templates.
Enhanced Visualization of Detected 3D Geometric Differences
(© 2018 The Eurographics Association and John Wiley & Sons Ltd., 2018) Palma, Gianpaolo; Sabbadin, Manuele; Corsini, Massimiliano; Cignoni, Paolo; Chen, Min and Benes, Bedrich
The wide availability of 3D acquisition devices makes viable their use for shape monitoring. The current techniques for the analysis of time‐varying data can efficiently detect actual significant geometric changes and rule out differences due to irrelevant variations (such as sampling, lighting and coverage). On the other hand, the effective visualization of such detected changes can be challenging when we want to show at the same time the original appearance of the 3D model. In this paper, we propose a dynamic technique for the effective visualization of detected differences between two 3D scenes. The presented approach, while retaining the original appearance, allows the user to switch between the two models in a way that enhances the geometric differences that have been detected as significant. Additionally, the same technique is able to visually hides the other negligible, yet visible, variations. The main idea is to use two distinct screen space time‐based interpolation functions for the significant 3D differences and for the small variations to hide. We have validated the proposed approach in a user study on a different class of datasets, proving the objective and subjective effectiveness of the method.The wide availability of 3D acquisition devices makes viable their use for shape monitoring. The current techniques for the analysis of time‐varying data can efficiently detect actual significant geometric changes and rule out differences due to irrelevant variations (such as sampling, lighting and coverage). On the other hand, the effective visualization of such detected changes can be challenging when we want to show at the same time the original appearance of the 3D model. In this paper, we propose a dynamic technique for the effective visualization of detected differences between two 3D scenes.
2018 Cover Image: Thingi10K
(© 2018 The Eurographics Association and John Wiley & Sons Ltd., 2018) Zhou, Qingnan; Jacobson, Alec; Chen, Min and Benes, Bedrich
Large‐Scale Pixel‐Precise Deferred Vector Maps
(© 2018 The Eurographics Association and John Wiley & Sons Ltd., 2018) Thöny, Matthias; Billeter, Markus; Pajarola, Renato; Chen, Min and Benes, Bedrich
Rendering vector maps is a key challenge for high‐quality geographic visualization systems. In this paper, we present a novel approach to visualize vector maps over detailed terrain models in a pixel‐precise way. Our method proposes a deferred line rendering technique to display vector maps directly in a screen‐space shading stage over the 3D terrain visualization. Due to the absence of traditional geometric polygonal rendering, our algorithm is able to outperform conventional vector map rendering algorithms for geographic information systems, and supports advanced line anti‐aliasing as well as slope distortion correction. Furthermore, our deferred line rendering enables interactively customizable advanced vector styling methods as well as a tool for interactive pixel‐based editing operations.Rendering vector maps is a key challenge for high‐quality geographic visualization systems. In this paper, we present a novel approach to visualize vector maps over detailed terrain models in a pixel‐precise way. Our method proposes a deferred line rendering technique to display vector maps directly in a screen‐space shading stage over the 3D terrain visualization. Due to the absence of traditional geometric polygonal rendering, our algorithm is able to outperform conventional vector map rendering algorithms for geographic information systems, and supports advanced line anti‐aliasing as well as slope distortion correction. Furthermore, our deferred line rendering enables interactively customizable advanced vector styling methods as well as a tool for interactive pixel‐based editing operations.
On the Stability of Functional Maps and Shape Difference Operators
(© 2018 The Eurographics Association and John Wiley & Sons Ltd., 2018) Huang, R.; Chazal, F.; Ovsjanikov, M.; Chen, Min and Benes, Bedrich
In this paper, we provide stability guarantees for two frameworks that are based on the notion of functional maps—the framework of shape difference operators and the one of analyzing and visualizing the deformations between shapes. We consider two types of perturbations in our analysis: one is on the input shapes and the other is on the change in . In theory, we formulate and justify the robustness that has been observed in practical implementations of those frameworks. Inspired by our theoretical results, we propose a pipeline for constructing shape difference operators on point clouds and show numerically that the results are robust and informative. In particular, we show that both the shape difference operators and the derived areas of highest distortion are stable with respect to changes in shape representation and change of scale. Remarkably, this is in contrast with the well‐known instability of the eigenfunctions of the Laplace–Beltrami operator computed on point clouds compared to those obtained on triangle meshes.In this paper, we provide stability guarantees for two frameworks that are based on the notion of functional maps—the shape difference operators introduced in [ROA*13] and the framework of [OBCCG13] which is used to analyse and visualize the deformations between shapes induced by a functional map. We consider two types of perturbations in our analysis: one is on the input shapes and the other is on the change in . In theory, we formulate and justify the robustness that has been observed in practical implementations of those frameworks.
Data Abstraction for Visualizing Large Time Series
(© 2018 The Eurographics Association and John Wiley & Sons Ltd., 2018) Shurkhovetskyy, G.; Andrienko, N.; Andrienko, G.; Fuchs, G.; Chen, Min and Benes, Bedrich
Numeric time series is a class of data consisting of chronologically ordered observations represented by numeric values. Much of the data in various domains, such as financial, medical and scientific, are represented in the form of time series. To cope with the increasing sizes of datasets, numerous approaches for abstracting large temporal data are developed in the area of data mining. Many of them proved to be useful for time series visualization. However, despite the existence of numerous surveys on time series mining and visualization, there is no comprehensive classification of the existing methods based on the needs of visualization designers. We propose a classification framework that defines essential criteria for selecting an abstraction method with an eye to subsequent visualization and support of users' analysis tasks. We show that approaches developed in the data mining field are capable of creating representations that are useful for visualizing time series data. We evaluate these methods in terms of the defined criteria and provide a summary table that can be easily used for selecting suitable abstraction methods depending on data properties, desirable form of representation, behaviour features to be studied, required accuracy and level of detail, and the necessity of efficient search and querying. We also indicate directions for possible extension of the proposed classification framework.Numeric time series is a class of data consisting of chronologically ordered observations represented by numeric values. Much of the data in various domains, such as financial, medical and scientific, are represented in the form of time series. To cope with the increasing sizes of datasets, numerous approaches for abstracting large temporal data are developed in the area of data mining. Many of them proved to be useful for time series visualization. However, despite the existence of numerous surveys on time series mining and visualization, there is no comprehensive classification of the existing methods based on the needs of visualization designers. We propose a classification framework that defines essential criteria for selecting an abstraction method with an eye to subsequent visualization and support of users' analysis tasks. We show that approaches developed in the data mining field are capable of creating representations that are useful for visualizing time series data.
CLUST: Simulating Realistic Crowd Behaviour by Mining Pattern from Crowd Videos
(© 2018 The Eurographics Association and John Wiley & Sons Ltd., 2018) Zhao, M.; Cai, W.; Turner, S. J.; Chen, Min and Benes, Bedrich
In this paper, we present a data‐driven approach to simulate realistic locomotion of virtual pedestrians. We focus on simulating low‐level pedestrians' motion, where a pedestrian's motion is mainly affected by other pedestrians and static obstacles nearby, and the preferred velocities of agents (direction and speed) are obtained from higher level path planning models. Before the simulation, collision avoidance processes (i.e. examples) are extracted from videos to describe how pedestrians avoid collisions, which are then clustered using hierarchical clustering algorithm with a novel distance function to find similar patterns of pedestrians' collision avoidance behaviours. During the simulation, at each time step, the perceived state of each agent is classified into one cluster using a neural network trained before the simulation. A sequence of velocity vectors, representing the agent's future motion, is selected among the examples corresponding to the chosen cluster. The proposed CLUST model is trained and applied to different real‐world datasets to evaluate its generality and effectiveness both qualitatively and quantitatively. The simulation results demonstrate that the proposed model can generate realistic crowd behaviours with comparable computational cost.In this paper, we present a data‐driven approach to simulate realistic locomotion of virtual pedestrians. We focus on simulating low‐level pedestrians' motion, where a pedestrian's motion is mainly affected by other pedestrians and static obstacles nearby, and the preferred velocities of agents (direction and speed) are obtained from higher level path planning models. Before the simulation, collision avoidance processes (i.e. examples) are extracted from videos to describe how pedestrians avoid collisions, which are then clustered using hierarchical clustering algorithm with a novel distance function to find similar patterns of pedestrians' collision avoidance behaviours. During the simulation, at each time step, the perceived state of each agent is classified into one cluster using a neural network trained before the simulation. A sequence of velocity vectors, representing the agent's future motion, is selected among the examples corresponding to the chosen cluster.
Olfaction and Selective Rendering
(© 2018 The Eurographics Association and John Wiley & Sons Ltd., 2018) Harvey, Carlo; Bashford‐Rogers, Thomas; Debattista, Kurt; Doukakis, Efstratios; Chalmers, Alan; Chen, Min and Benes, Bedrich
Accurate simulation of all the senses in virtual environments is a computationally expensive task. Visual saliency models have been used to improve computational performance for rendered content, but this is insufficient for multi‐modal environments. This paper considers cross‐modal perception and, in particular, if and how olfaction affects visual attention. Two experiments are presented in this paper. Firstly, eye tracking is gathered from a number of participants to gain an impression about where and how they view virtual objects when smell is introduced compared to an odourless condition. Based on the results of this experiment a new type of saliency map in a selective‐rendering pipeline is presented. A second experiment validates this approach, and demonstrates that participants rank images as better quality, when compared to a reference, for the same rendering budget.Accurate simulation of all the senses in virtual environments is a computationally expensive task. Visual saliency models have been used to improve computational performance for rendered content, but this is insufficient for multi‐modal environments. This paper considers cross‐modal perception and, in particular, if and how olfaction affects visual attention. Two experiments are presented in this paper. Firstly, eye tracking is gathered from a number of participants to gain an impression about where and how they view virtual objects when smell is introduced compared to an odourless condition.
Enhancing the Realism of Sketch and Painted Portraits With Adaptable Patches
(© 2018 The Eurographics Association and John Wiley & Sons Ltd., 2018) Lee, Yin‐Hsuan; Chang, Yu‐Kai; Chang, Yu‐Lun; Lin, I‐Chen; Wang, Yu‐Shuen; Lin, Wen‐Chieh; Chen, Min and Benes, Bedrich
Realizing unrealistic faces is a complicated task that requires a rich imagination and comprehension of facial structures. When face matching, warping or stitching techniques are applied, existing methods are generally incapable of capturing detailed personal characteristics, are disturbed by block boundary artefacts, or require painting‐photo pairs for training. This paper presents a data‐driven framework to enhance the realism of sketch and portrait paintings based only on photo samples. It retrieves the optimal patches of adaptable shapes and numbers according to the content of the input portrait and collected photos. These patches are then seamlessly stitched by chromatic gain and offset compensation and multi‐level blending. Experiments and user evaluations show that the proposed method is able to generate realistic and novel results for a moderately sized photo collection.Realizing unrealistic faces is a complicated task that requires a rich imagination and comprehension of facial structures. When face matching, warping or stitching techniques are applied, existing methods are generally incapable of capturing detailed personal characteristics, are disturbed by block boundary artefacts, or require painting‐photo pairs for training. This paper presents a data‐driven framework to enhance the realism of sketch and portrait paintings based only on photo samples. It retrieves the optimal patches of adaptable shapes and numbers according to the content of the input portrait and collected photos. These patches are then seamlessly stitched by chromatic gain and offset compensation and multi‐level blending.
Realistic Ultrasound Simulation of Complex Surface Models Using Interactive Monte‐Carlo Path Tracing
(© 2018 The Eurographics Association and John Wiley & Sons Ltd., 2018) Mattausch, Oliver; Makhinya, Maxim; Goksel, Orcun; Chen, Min and Benes, Bedrich
Ray‐based simulations have been shown to generate impressively realistic ultrasound images in interactive frame rates. Recent efforts used GPU‐based surface raytracing to simulate complex ultrasound interactions such as multiple reflections and refractions. These methods are restricted to perfectly specular reflections (i.e. following only a single reflective/refractive ray), whereas real tissue exhibits roughness of varying degree at tissue interfaces, causing partly diffuse reflections and refractions. Such surface interactions are significantly more complex and can in general not be handled by conventional deterministic raytracing approaches. However, these can be efficiently computed by Monte‐Carlo sampling techniques, where many ray paths are generated with respect to a probability distribution. In this paper, we introduce Monte‐Carlo raytracing for ultrasound simulation. This enables the realistic simulation of ultrasound‐tissue interactions such as soft shadows and fuzzy reflections. We discuss how to properly weight the contribution of each ray path in order to simulate the behaviour of a beamformed ultrasound signal. Tracing many individual rays per transducer element is easily parallelizable on modern GPUs, as opposed to previous approaches based on recursive binary raytracing. We further propose a significant performance optimization based on adaptive sampling.Ray‐based simulations have been shown to generate impressively realistic ultrasound images in interactive frame rates. Recent efforts used GPU‐based surface raytracing to simulate complex ultrasound interactions such as multiple reflections and refractions. These methods are restricted to perfectly specular reflections (i.e. following only a single reflective/refractive ray), whereas real tissue exhibits roughness of varying degree at tissue interfaces, causing partly diffuse reflections and refractions. Such surface interactions are significantly more complex and can in general not be handled by conventional deterministic raytracing approaches.
Guidelines for Quantitative Evaluation of Medical Visualizations on the Example of 3D Aneurysm Surface Comparisons
(© 2018 The Eurographics Association and John Wiley & Sons Ltd., 2018) Saalfeld, P.; Luz, M.; Berg, P.; Preim, B.; Saalfeld, S.; Chen, Min and Benes, Bedrich
Medical visualizations are highly adapted to a specific medical application scenario. Therefore, many researchers conduct qualitative evaluations with a low number of physicians or medical experts to assess the benefits of their visualization technique. Although this type of research has advantages, it is difficult to reproduce and can be subjectively biased. This makes it problematic to quantify the benefits of a new visualization technique. Quantitative evaluation can objectify research and help bringing new visualization techniques into clinical practice. To support researchers, we present guidelines to quantitatively evaluate medical visualizations, considering specific characteristics and difficulties. We demonstrate the adaptation of these guidelines on the example of comparative aneurysm surface visualizations. We developed three visualization techniques to compare aneurysm volumes. The visualization techniques depict two similar, but not identical aneurysm surface meshes. In a user study with 34 participants and five aneurysm data sets, we assessed objective measures (accuracy and required time) and subjective ratings (suitability and likeability). The provided guidelines and presentation of different stages of the evaluation allow for an easy adaptation to other application areas of medical visualization.Medical visualizations are highly adapted to a specific medical application scenario. Therefore, many researchers conduct qualitative evaluations with a low number of physicians or medical experts to assess the benefits of their visualization technique. Although this type of research has advantages, it is difficult to reproduce and can be subjectively biased. This makes it problematic to quantify the benefits of a new visualization technique. Quantitative evaluation can objectify research and help bringing new visualization techniques into clinical practice.

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