399 Works

Effects of Embodiment on Generic and Content-Specific Intelligent Virtual Agents as Exhibition Guides

Susanne Schmidt, Gerd Bruder & Frank Steinicke
Intelligent Virtual Agents (IVAs) received enormous attention in recent years due to significant improvements in voice communication technologies and the convergence of different research fields such as Machine Learning, Internet of Things, and Virtual Reality (VR). Interactive conversational IVAs can appear in different forms such as voice-only or with embodied audio-visual representations showing, for example, human-like contextually related or generic three-dimensional bodies. In this paper, we analyzed the benefits of different forms of virtual agents...

A Novel Approach for Cooperative Motion Capture (COMOCAP)

Gregory Welch, Tianren Wang, Gary Bishop & Gerd Bruder
Conventional motion capture (MOCAP) systems, e.g., optical systems, typically perform well for one person, but less so for multiple people in close proximity. Measurement quality can decline with distance, and even drop out as source/sensor components are occluded by nearby people. Furthermore, conventional optical MOCAP systems estimate body posture using a global estimation approach employing cameras that are fixed in the environment, typically at a distance such that one person or object can easily occlude...

Viewpoint Selection for Liquid Animations

Chihiro Suzuki & Takashi Kanai
We propose a viewpoint selection method for time-varying liquid shapes in order to select the best viewpoint for liquid animations. First, viewpoint evaluation is performed by a combination of three evaluation terms; occlusion term, spatial feature term, and temporal feature term, and the viewpoint having the maximum evaluation value is selected as the “best viewpoint”. Through various experiments, it was confirmed that the results of this method is consistent with human intuition and that it...

HTC Vive Pro Time Performance Benchmark for Scientific Research

Morgan Le Chénéchal & Jonas Chatel Goldman
Widespread availability of consumer-level virtual reality (VR) devices creates a venue for their massive use in psychology and neuroscience research. The application of VR to scientific research however poses significant constraints on system performance and stability. In particular, studies with multimodal measurement of human behavior and physiology require precise hardwaresoftware synchronization with precise event labeling (within 10 milliseconds). Previous works investigating suitability of VR systems for research have mainly focused on benchmarking performance in spatial...

Evolutionary Lines for Flow Visualization

Wito Engelke & Ingrid Hotz
In this work we explore evolutionary algorithms for selected a visualization application. We demonstrate its potential using an example from flow visualization showing promising first results. Evolutionary algorithms, as guided search approach, find close-to-optimal solutions with respect to some fitness function in an iterative process using biologically motivated mechanisms like selection, mutation and recombination. As such, they provide a powerful alternative to filtering methods commonly used in visualization where the space of possible candidates is...

Atalaya3D: Making Universities' Cultural Heritage Accessible Through 3D Technologies

Francisco Javier Melero, Jorge Revelles & Maria Luisa Bellido
This work was carried out over the past eight years through the Atalaya3D project, which aims to make the cultural heritage of the ten public Andalusian universities accessible. Since 2010, the project has been a pioneer in the field of 3D scanning of sculptures and historical sites, opening up restricted areas virtually through 3D web displays. Moreover, in addition to the website, a mobile app allows visitors to browse these institutions' vast heritage and examine...

3D Reconstruction and Transparent Visualization of Indonesian Cultural Heritage from a Single Image

Jiao Pan, Liang Li, Hiroshi Yamaguchi, Kyoko Hasegawa, Fadjar I. Thufail, Bra Mantara & Satoshi Tanaka
Herein, we propose a method for three-dimensional (3D) reconstruction of cultural heritage based on deep learning, which we apply to the reliefs of the Buddhist temple heritage of Borobudur Temple, in Indonesia. Some parts of the Borobudur reliefs have been hidden by stone walls and are not visible following the reinforcements during the Dutch rule. Today, only gray-scale photos of those hidden parts are displayed in the Borobudur Museum. First, we reconstruct 3D point clouds...

Visual Assessment of Vascular Torsion using Ellipse Fitting

Gabriel Mistelbauer, Martin Zettwitz, Rüdiger Schernthaner, Dominik Fleischmann, Christian Teutsch & Bernhard Preim
Blood vessels are well explored and researched in medicine and visualization. However, the investigation of vascular torsion has yet been unexplored. In order to understand the development and current state of a single blood vessel or even multiple connected ones, properties of vascular structures have to be analyzed. In this paper we assess the torsion of blood vessels in order to better understand their morphology. The aim of this work is to quantitatively gauge blood...

A Visual Interface for Feature Subset Selection Using Machine Learning Methods

Diego Rojo, Laura Raya, Manuel Rubio-Sánchez & Alberto Sánchez
Visual representation of information remains a key part of exploratory data analysis. This is due to the high number of features in datasets and their increasing complexity, together with users' ability to visually understand information. One of the most common operations in exploratory data analysis is the selection of relevant features in the available data. In multidimensional scenarios, this task is often done with the help of automatic dimensionality reduction algorithms from the machine learning...

Semantic Screen-Space Occlusion for Multiscale Molecular Visualization

Thomas Bernhard Koch, David Kouril, Tobias Klein, Peter Mindek & Ivan Viola
Visual clutter is a major problem in large biological data visualization. It is often addressed through the means of level of detail schemes coupled with an appropriate coloring of the visualized structures. Ambient occlusion and shadows are often used to improve the depth perception. However, when used excessively, these techniques are sources of visual clutter themselves. In this paper we present a new approach to screen-space illumination algorithms suitable for use in illustrative visualization. The...

Reduction of CPU-GPU Synchronization Overhead for Accelerating Implicit Clothing Simulator

Sangbin Lee, Donghan Ryu & Hyeong-Seok Ko
When trying to make the conjugate gradient (CG) method exploit GPU technology, this paper notes that the communication between CPU and GPU to transfer the residual value and waiting for the CPU's decision whether to continue further iterations is a new source of delay that has been overlooked and turns out not negligible. By examining the residual decrease pattern in log scale, this paper proposes so-called the Secant Lazy Residual Evaluation (Secant LRE) method to...

EuroVA 2018: Frontmatter

Christian Tominski & Tatiana Von Landesberger

Analysis of Spatio-temporal Data in Virtual Historic Spaces

Georgios Artopoulos & Panayiotis Charalambous
This paper presents a virtual reality workflow for citizen engagement in the management of neglected historic sites in contested cities, such as Nicosia, Cyprus, the last divided capital of Europe. It is contextualized in an ongoing research for the use of interactive visualization technologies for co-creation and co-management design practices in public space management. We demonstrate initial results from tracking the movement and gaze of users in VR walkthroughs of a historic site with and...

Atomic Accessibility Radii for Molecular Dynamics Analysis

Norbert Lindow, Daniel Baum & Hans-Christian Hege
In molecular structure analysis and visualization, the molecule's atoms are often modeled as hard spheres parametrized by their positions and radii. While the atom positions result from experiments or molecular simulations, for the radii typically values are taken from literature. Most often, van der Waals (vdW) radii are used, for which diverse values exist. As a consequence, different visualization and analysis tools use different atomic radii, and the analyses are less objective than often believed....

Shape Analysis Techniques for the Ayia Irini Case Study

Andreas Scalas, Valentina Vassallo, Michela Mortara, Michela Spagnuolo & Sorin Hermon
The typical approach for archaeological analysis is mainly qualitative and, as such, subjective. Even when some measures are reported in the documentation of artefacts, they are often approximate or ambiguous. Conversely, the quantitative approach is based on objective metrics to produce replicable results and, coupled with digital tools, can assist the qualitative analysis in archaological research with no risk of damage. In this paper, we present a geometric-quantitative approach for the analysis of archaeological finds...

Recovering 3D Indoor Floor Plans by Exploiting Low-cost Spherical Photography

Giovanni Pintore, Fabio Ganovelli, Ruggero Pintus, Roberto Scopigno & Enrico Gobbetti
We present a novel approach to automatically recover, from a small set of partially overlapping panoramic images, an indoor structure representation in terms of a 3D floor plan registered with a set of 3D environment maps. Our improvements over previous approaches include a new method for geometric context extraction based on a 3D facets representation, which combines color distribution analysis of individual images with sparse multi-view clues, as well as an efficient method to combine...

ICL Multispectral Light Stage: Building a Versatile LED Sphere with Off-the-shelf Components

Christos Kampouris & Abhijeet Ghosh
We describe the design and implementation of a versatile multispectral light stage (LED sphere) consisting of 168 RGB and color temperature controllable white (W+) lamps, respectively. The light stage is powered with two sets of off-the-shelf programmable MR16 LED lamps producing RGB and color temperature controllable white (2700K - 5700K) illumination. The design is heavily inspired by various USC-ICT light stages, particularly Light Stages 3, 5 and X. However, unlike a typical geodesic (subdivided icosahedron)...

Image Inpainting for High-Resolution Textures using CNN Texture Synthesis

Pascal Laube, Michael Grunwald, Matthias O. Franz & Georg Umlauf
Deep neural networks have been successfully applied to problems such as image segmentation, image super-resolution, coloration and image inpainting. In this work we propose the use of convolutional neural networks (CNN) for image inpainting of large regions in high-resolution textures. Due to limited computational resources processing high-resolution images with neural networks is still an open problem. Existing methods separate inpainting of global structure and the transfer of details, which leads to blurry results and loss...

Identifying Similar Eye Movement Patterns with t-SNE

Michael Burch
In this paper we describe an approach based on the t-distributed stochastic neighbor embedding (t-SNE) focusing on projecting high-dimensional eye movement data to two dimensions. The lower-dimensional data is then represented as scatterplots reflecting the local structure of the high-dimensional eye movement data and hence, providing a strategy to identify similar eye movement patterns. The scatterplots can be used as means to interact with and to further annotate and analyze the data for additional properties...

Geodesic-based 3D Shape Retrieval Using Sparse Autoencoders

Lorenzo Luciano & Abdessamad Ben Hamza
In light of the increased processing power of graphics cards and the availability of large-scale datasets, deep neural networks have shown a remarkable performance in various visual computing applications. In this paper, we propose a geometric framework for unsupervised 3D shape retrieval using geodesic moments and stacked sparse autoencoders. The key idea is to learn deep shape representations in an unsupervised manner. Such discriminative shape descriptors can then be used to compute the pairwise dissimilarities...

A Visual Analytics Approach for Traffic Flow Prediction Ensembles

Kezhi Kong, Yuxin Ma, Chentao Ye, Junhua Lu, Xiqun Chen, Wei Zhang & Wei Chen
Traffic flow prediction plays a significant role in Intelligent Transportation Systems (ITS). Due to the variety of prediction models, the prediction results form an intricate structure of ensembles and hence leave a challenge of understanding and evaluating the ensembles from different perspectives. In this paper, we propose a novel visual analytics approach for analyzing the predicted ensembles. Our approach models the uncertainty of different traffic flow prediction results. The variations of space, time, and network...

Matrix Bidirectional Path Tracing

Chakravarty Reddy Alla Chaitanya, Laurent Belcour, Toshiya Hachisuka, Simon Premoze, Jacopo Pantaleoni & Derek Nowrouzezahrai
Sampled paths in Monte Carlo ray tracing can be arbitrarily close to each other due to its stochastic nature. Such clumped samples in the path space tend to contribute little toward an accurate estimate of each pixel. Bidirectional light transport methods make this issue further complicated since connecting paths of sampled subpaths can be arbitrarily clumped again. We propose a matrix formulation of bidirectional light transport that enables stratification (and low-discrepancy sampling) in this connection...

Muscle Simulation with Extended Position Based Dynamics

Marco Romeo, Carlos Monteagudo & Daniel Sánchez-Quirós
Recent research on muscle simulation for Visual Effects relies on numerical methods such as the Finite Element Method or Finite Volume Method. These approaches produce realistic results, but require high computational time and are complex to set up. On the other hand Position Based Dynamics offers a fast and controllable solution to simulate surfaces and volumes, but there is no literature on how to implement constraints that could be used to realistically simulate muscles for...

Integrated Volume Visualisation of Archaeological Ground Penetrating Radar Data

Alexander Bornik, Mario Wallner, Alois Hinterleitner, Geert Verhoeven & Wolfgang Neubauer
The non-invasive prospection of our archaeological heritage is one of the main tasks of modern archaeology and often provides the necessary bases for further activities, such as special protection or intensified research. Geophysical prospections using ground-penetrating radar (GPR) are an invaluable tool for the non-destructive exploration of archaeological monuments still buried in the ground. However, the analysis and interpretation of the data sets generated in this way is a time-consuming and complex process and requires...

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