Visual Computing Trends 2017


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We would like to invite you to participate in the Visual Computing Trends Symposium 2017.

The symposium will give you an overview of future developments in Visual Computing by top-level invited experts. You will learn about key open challenges and scientific and industrial trends. Participants are encouraged to participate in extended discussions on core technological issues.

Participation is free, however advance registration is required (limited number of participants!). Please register at

Venue, Accommodation

Tech Gate Vienna
Donau-City-Straße 1
1220 Wien

Public Transport:
U1 | Station Kaisermühlen - Vienna International Center, Exit Schüttaustraße.
Two minutes walk to TechGate.

By Car:
A22, Exit Vienna International Center, follow the signs to TechGate Parking Garage

A list of Hotels and other Accomodations can be found at


  • 08:30 Registration
  • 09:00 Opening and Welcome
    Werner Purgathofer, TU Wien
    Gerd Hesina, VRVis
  • 09:10 Helwig Hauser, University of Bergen, Norway
    "The Future of Big Data Visualization"
    10:00 Discussion
  • 10:30 Coffee Break
  • 11:00 Nadia Magnenat Thalmann, University of Geneva, Switzerland, and Nanyang Technological University, Singapore
    "The Future of Social Robots: Will they become our Companions of Tomorrow?"
    11:50 Discussion
  • 12:20 Lunch
  • 13:15 Eugene Fiume, University of Toronto and Simon Fraser University
    "The Future of Computational Reality"
    14:05 Discussion
  • 14:35 Coffee Break
  • 15:00 George Drettakis, INRIA Sophia-Antipolis, France
    "Is Simulation (still) the Future of Rendering, or will it be Capture and Learning?"
    15:50 Discussion
  • 16:20 Panel Discussion with all speakers
    Moderation: Silvia Miksch, TU Wien
  • 17:30 End

Abstracts of the talks and brief biographies

Prof. Dr. Helwig Hauser: "The Future of Big Data Visualization"

For several decades, already, we experience the newly emerged Information Age, truly revolutionalizing the modern world. Rapidly improving technology enables the steadily expanding acquisition, processing, and transmission of data, leading to new opportunities in business, recreation, etc. The past 10 to 15 years have brought a particularly fast acceleration of this process due to the transition from analog solutions to the Digital Age, bringing along, also, the new term of Big Data. While the term Big Data is also seen as "over-hyped", or "over-used", it still points our attention at an interesting observation: Is the Information Age getting out of hands? Are we already overwhelmed by the Volume, the Velocity, and the Variety of Big Data?

Visualization has always had the ambition to provide effective and efficient insight into all sorts of data---in particular, where traditional methods seemed overwhelmed, and the argument that our own human visual system can efficiently transmit a lot of information from the world to the brain has been used repeatedly to sell visualization as a promising solution for the expanding Information Age. Today, visualization is certainly established as one key technology in the Big Data business. Still, we should ask, what limitations visualization will meet and when. How much information can a human observer appreciate through visualization and at which rate? And what to do, when these boundaries are to be further extended?

It is certainly interesting to think about the Future of Big Data Visualization and it is likely that this future will impact many or even most of us significantly. Still, we should not forget that prediction is difficult, in particular when it concerns the future (Nils Bohr et al.)!

About Helwig Hauser
Since 2007, Helwig Hauser is professor in visualization at the University of Bergen in Norway, where he leads a research group on visualization at the Department of Computer Science. He has more than 20 years of experience in visualization and is an internationally respected member of the international research community. As one particular interest within visualization - tightly related to the topic of big data visualization - Helwig Hauser has been researching new solutions for the interactive and iterative visual data exploration and analysis for over 15 years.
More information and related publications can be found at

Prof. Dr. Nadia Magnenat Thalmann, "The Future of Social
Robots: will they become our Companions of Tomorrow?"

Today, we are able to see social robots that look and behave more and more like humans. What is the research needed to consider them as companions? Will they replace humans? What are their capabilities? What is the future with humanoid robots in our daily life? This talk will address all these questions. It will also show the making of the Social Humanoid Robot Nadine. See

About Nadia Magnenat Thalmann
Nadia Magnenat Thalmann is Professor and Director of the Institute for Media Innovation, Nanyang Technological University, Singapore. She is also the Founder and Director of the MIRALab, an interdisciplinary lab in Human Computer Animation, University of Geneva, Switzerland. Her research domains are Social Robots, mixed realities and medical simulation. In Singapore, she has developed the robot Nadine alike of herself that is able to speak, recognize people and gestures, express mood and emotions, and remember actions. All over her career, she has received several artistic and scientific Awards, among them the 2012 Humboldt Research Award and two Doctor Honoris Causa (from University of Hanover in Germany and from the University of Ottawa in Canada). She is Editor-in-Chief of the Journal The Visual Computer (Springer-Verlag) and is a Member of the Swiss Academy of Engineering Sciences.

Prof. Dr. Eugene Fiume, "The Future of Computational Reality"

The goal of computational reality is to synthesize virtual experiences that are visually indistinguishable from direct physical experience. I will argue in my talk that this involves scientific and technical challenges that are currently considerably beyond our understanding, capabilities, and perhaps even our competence. A deeper understanding of how humans process and interpret sense data will be required to build models of how humans construct "reality", recognising that these constructions are the products of an evolutionary process that favours survival over physical accuracy. Constructing models of accuracy that can objectively tell us when a simulation is "good enough" is a fundamental problem of computer graphics that will require deep insights into human perception, psychology and anthropology. It is a surprisingly under-appreciated issue, particularly given the recent resurgence of new technologies and content for augmented and virtual reality.

About Eugene Fiume
Eugene Fiume is Professor and past Chair of the Department of Computer Science at the University of Toronto, where he also co-directs the Dynamic Graphics Project. He is Director of the Masters of Science in Applied Computing programme, is Principal Investigator of a $6M CFI/ORF project on the construction of a digital media and systems lab, and is a Fellow of the Royal Society of Canada.

Eugene's research interests include most aspects of realistic computer graphics, including computer animation, modelling natural phenomena, and illumination, as well as strong interests in internet based imaging, image repositories, software systems and parallel algorithms. He has written two books and (co-)authored over 130 papers on these topics.His industrial interests include technology transfer in the Information Technology area, internet-based applications, digital media, wireless and multimedia systems, web-based services, large-scale computation, and the interaction of information technology and business.
More information can be found at

Prof. Dr. George Drettakis, "Is Simulation (still) the Future of Rendering, or will it be Capture and Learning?"

In this talk we will examine recent evolutions in traditional, simulation-based rendering, and those in capture and learning based solutions. Based on several concrete examples, we will discuss the fundamental issues behind the contemporary quest for visual realism, which, as always, relate to accurate and realistic visual rendition of geometry, materials and illumination. We will first discuss the enormous progress of traditional forward simulation based methods, especially for illumination algorithms. We will then consider one remaining major challenge, which is the provision of accurate geometry and materials needed for these algorithms to run, and the fact that this is currently still done with manual labor and heuristics. We will see how recent work using capture and learning try to overcome this challenge, and discuss whether in some cases such approaches actually render illumination algorithms superfluous. We will close with questions on how these seemingly opposing approaches -- simulation vs. capture and learning -- could potentially come together, bringing us closer to the holy grail of easy-to-create, completely realistic imagery in real-time.

About George Drettakis
George Drettakis graduated from the Dept. of Computer Science in Crete, Greece, and obtained an M.Sc. and a Ph.D., (1994) at the Dept. of C.S. (Dynamic Graphics Project) at the University of Toronto, Canada, under the supervision of Eugene Fiume. He was an ERCIM postdoctoral fellow in Grenoble, Barcelona and Bonn (94-95). He obtained a permanent INRIA researcher position in the iMAGIS group in Grenoble in 1995, and the degree of "Habilitation" at the University of Grenoble (1999). In 2000 he founded the REVES research group at INRIA Sophia-Antipolis, which he headed from 2002 until Dec. 2015. Since July 2016 he heads the follow-up group GRAPHDECO. He became an INRIA Senior Researcher 2003; and DR1 (full professor equivalent) in 2008. He received the Eurographics (EG) Outstanding Technical Contributions award in 2007 and is an EG fellow. He is an associate editor for ACM Transactions on Graphics, was technical papers chair of SIGGRAPH Asia 2010, associate editor and co-editor in chief of IEEE Trans. on Computer Graphics and Visualization (2011-2015) and leads the EG working group on Rendering. He has worked on many different topics in computer graphics, with an emphasis on rendering. He initially concentrated on lighting and shadow computation and subsequently worked on 3D audio, perceptually-driven algorithms, virtual reality and 3D interaction. In recent years he has worked on image-based rendering and relighting, textures, weathering and perception for graphics.