Keynotes and Award Presentations


Title: A digital world to thrive in – How the Internet of Things can make the ‚invisible hand‘ work

Speaker: Dirk Helbing, ETH Zurich

Abstract: Managing data-rich societies wisely and reaching sustainable development are among the greatest challenges of the 21st century. We are faced with existential threats and huge opportunities. If we don’t act now, large parts of our society will not be able to economically benefit from the digital revolution. This could lead to mass unemployment and social unrest. It is time to create the right framework for the digital society to come.

Dirk Helbing

Bio: Dirk Helbing is Professor of Computational Social Science at the Department of Humanities, Social and Political Sciences and affiliate of the Computer Science Department at ETH Zurich. He earned a PhD in physics and was Managing Director of the Institute of Transport & Economics at Dresden University of Technology in Germany. He is internationally known for his work on pedestrian crowds, vehicle traffic, and agent-based models of social systems. Furthermore, he coordinates the FuturICT Initiative (, which focuses on the understanding of techno-socio-economic systems, using smart data. His work is documented in hundreds of scientific articles, keynote lectures and media reports worldwide. Helbing is an elected member of the prestigious German Academy of Sciences “Leopoldina” and worked for the World Economic Forum’s Global Agenda Council on Complex Systems. He is also co-founder of the Physics of Socio-Economic Systems Division of the German Physical Society and of ETH Zurich’s Risk Center. In January 2014 Prof. Helbing received a honorary PhD from Delft University of Technology (TU Delft). Since June 2016 he is affiliate professor at the faculty of Technology, Policy and Management at TU Delft, where he leads the PhD school in „Engineering Social Technologies for a Responsible Digital Future“.

Title: Visual Analytics for Multimedia: Challenges and Opportunities

Speaker: Jack van Wijk, Eindhoven University of Technology

Abstract: Understanding huge multimedia collections is a big challenge. Given a set of hundreds of thousands or millions of images, how to understand its contents and how to find images that are relevant for the task at hand? The use of a tight integration of automated methods, visualization and interaction, known as visual analytics, is probably the only way to go, combining the strengths of man and machine. An overview of trends in data visualization and visual analytics is given, and examples of recent work in multimedia analytics are presented. Exploiting meta-data, using interaction with relatively simple visual representations, and alignment with the work flow of users are promising routes, but scalability and evaluation are still challenging issues.

Jack van Wijk

Bio: Jack (Jarke J.) van Wijk is full professor in visualization at the Department of Mathematics and Computer Science of Eindhoven University of Technology (TU/e). He received a MSc degree in industrial design engineering in 1982 and a PhD degree in computer science in 1986, both from Delft University of Technology. He has worked for ten years at the Netherlands Energy Research Foundation ECN. He joined Eindhoven University of Technology in 1998, where he became a full professor of visualization in 2001. His main research interests are information visualization and visual analytics, with a focus on the development of new methods for the interactive exploration of large data-sets. The work of his group has led to two start-up companies: MagnaView BV and SynerScope BV. He has (co-)authored more than 150 papers in visualization and computer graphics and received six best paper awards. He received the IEEE Visualization Technical Achievement Award in 2007 and the Eurographics 2013 Outstanding Technical Contributions Award.

Award presentations

ACM SIGMM Award for Outstanding Technical Contributions to Multimedia Computing, Communications and Applications

The 2016 winner of the prestigious ACM Special Interest Group on Multimedia (SIGMM) award for Outstanding Technical Contributions to Multimedia Computing, Communications and Applications is Prof. Dr. Alberto del Bimbo. The award is given in recognition of his outstanding, pioneering and continued research contributions in the areas of multimedia processing, multimedia content analysis, and multimedia applications, his leadership in multimedia education, and his outstanding and continued service to the community.

Prof. del Bimbo was among the very few who pioneered the research in image and video content-based retrieval in the late 80’s. Since that time, for over 25 years, he has been among the most visionary and influential researchers in Europe and world-wide in this field. His research has influenced several generations of researchers that are now active in some of the most important research centers world-wide. Over the years, he has made significant innovative research contributions.

In the early times of the discipline he explored all the modalities for retrieval by visual similarity of images and video. In his early paper Visual Image Retrieval by Elastic Matching of User Sketches published in IEEE Trans. on Pattern Analysis and Machine Intelligence in 1997, he presented one of the first and top performing methods for image retrieval by shape similarity from user’s sketches. He also published in IEEE Trans. on Pattern Analysis and Machine Intelligence and IEEE Trans. on Multimedia his original research on representations for spatial relationships between image regions based on spatial logic. This ground-breaking research was accompanied by the definition of efficient index structures to permit retrieval from large datasets. He was one of the first to address this large datasets aspect that has now become very important for the research community.

Since the early 2000s, with the advancement of 3D imaging technologies and the availability of a new generation of acquisition devices capable of capturing the geometry of 3D objects in the three-dimensional physical space, Prof. del Bimbo and his team initiated research in 3D content based retrieval that has now become increasingly popular in mainstream research. Again, he was among the very first researchers to initiate this research. Particularly, he focused on 3D face recognition extending the weighted walkthrough representation of spatial relationships between image regions to model the 3D relationships between facial stripes. His solution of 3D Face Recognition Using Iso-geodesic Stripes scored the best performance at SHREC Shape Retrieval Contest in 2008, and was published in IEEE Trans. on Pattern Analysis and Machine Intelligence, in 2010. At CVPR’15 he presented a novel idea for representing 3D textured mesh manifolds using Local Binary Patterns, that is highly effective for 3D face retrieval. This was the first attempt to combine 3D geometry and photometric texture into a single unified representation. In 2016 he has co-authored a forward looking survey on content-based image retrieval in the context of social image platforms, that has appeared on ACM Computing Surveys. It includes an extensive treatise of image tag assignment, refinement and tag-based retrieval and explores the differences between traditional image retrieval and retrieval with socially generated images.

One very important aspect of his contribution to the community is Professor del Bimbo’s educational impact during his career. He was the author of the monograph, Visual Information Retrieval, published by Morgan Kaufmann in 1999 which became one of the most cited and influential books from the early years of image and video content-based retrieval. Many young researchers have used this book as the main reference in their studies, and their career has been shaped by the ideas discussed in this book. Being the first and sole book on that subject in the early times of the discipline, it played a key role to develop content-based retrieval from a research niche to a largely populated field of research and to make it central to Multimedia research.

Professor del Bimbo has an extraordinary and long-lasting track record of services to the scientific community through the last 20 years. As the General Chair he organized two of the most successful conferences in Multimedia, namely IEEE ICMCS’99, the Int’l Conf. on Multimedia Computing and Systems (now renamed IEEE ICME) and ACM MULTIMEDIA’10. The quality and success of these conferences were highly influential to attract new young researchers in the field and form the present research community. Since 2016, he is the Editor-in-Chief for ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM).

ACM SIGMM Rising Star Award 2016

Dr. Bart Thomee received his Ph.D. from Leiden University in 2010. In his thesis, he focused on multimedia search and exploration, specifically targeting artificial imagination and duplicate detection. On the topic of artificial imagination, he aimed to more rapidly understand the user’s search intent by generating imagery that resemble the ideal image the user is looking for. Using the synthesized images as queries instead of existing images from the database boosted the relevance of the image results by up to 23%. On the topic of duplicate detection, he designed descriptors to compactly represent web-scale image collections and to accurately detect transformed versions of the same image. This work led to an Outstanding Paper Citation at ACM Conference on Multimedia Information Retrieval 2008.

In 2011, he jointed Yahoo Labs, where Dr. Thomee ‘s interests grew into geographic computing in Multimedia. He began characterizing spatiotemporal regions from labeled (e.g. tagged) georeferenced media, for which he devised a technique based on scale-space theory that could process billions of georeferenced labels in a matter of hours. This work was published at WWW 2013 and became a reference example at Yahoo for how to disambiguate multi-language and multi-meaning labels from media with noisy annotations.

He also started to use an overlooked piece of information that is found in most camera phone images: compass information. He developed a technique to accurately pinpoint the locations and surface area of landmarks, solely based on the positions and orientations of photos taken of them which may have been taken hundreds of yards to miles away.

Dr. Thomee’s recent work on the YFCC100M dataset has had important impacts on the multimedia and SIGMM research community. This new dataset was real in size and structure to fuel and change the landscape of research in Multimedia. What started as an initiative to release a geo-Flickr dataset, Dr. Thomee quickly saw the broader impact and worked rapidly to scale the size. He had to push the limits of openness without violating licensing terms, copyright, or privacy. He worked closely with many lawyers to overturn the default, restrictive terms of use by making it also available to non-academics all over the world. He coordinated and led the efforts to share the data and effort horizontally with ICSI, LLNL, and Amazon Open Data. It was highlighted in the 2016 February issue of the Communications of ACM (CACM). The dataset has been requested over 1200 times in just a few months and cited many times since launch. Dr. Thomee has continued by releasing expansion packs to the YFCC100M. This dataset is expected to impact Multimedia research significantly over the future years.

Dr. Thomee has also been an exemplary community member of the Multimedia community. For example, he organized the ImageCLEF photo annotation task (2012-2013) and MediaEval placing task (2013-2016) as well as designed the ACM Grand Challenge on Event Summarization (2015) and on Tag & Caption Prediction (2016).

In summary, Dr. Bart Thomee receives the 2016 ACM SIGMM Rising Star Award Thomee for significant contributions in the areas of geo-multimedia computing, media evaluation, and open datasets for research.

SIGMM Award for Outstanding Ph.D. Thesis in Multimedia Computing, Communications and Applications 2016

ACM Special Interest Group on Multimedia (SIGMM) is pleased to present the 2016 SIGMM Outstanding Ph.D. Thesis Award to Dr. Christoph Kofler. The award committee considers Dr. Kofler’s dissertation entitled “User Intent in Online Video Search” worthy of the recognition as the thesis is the first to innovatively consider a user’s intent in multimedia search yielding significantly improved results in satisfying the information need of the user. The work has high originality and is expected to have significant impact, especially in boosting the search performance for multimedia data.

Dr. Kofler’s thesis systematically explores a user’s video search intent that is behind a user’s information need in three steps: (1) analyzing a real-world transaction log produced by a large video search engine to understand why searches fail, (2) understanding the possible intents of users behind video search and uploads, and (3) designing an intent-aware video search result optimization approach that re-ranks initial video search results so as to yield the highest potential to satisfy the users’ search intent.

The effectiveness of the framework developed in the thesis has been successfully justified by a thorough range of experiments. The thesis topic itself is highly topical and the framework makes groundbreaking contributions to our understanding and knowledge in the area of users’ information seeking, user intent, user satisfaction, and multimedia search engine usability. The publications related to the thesis clearly demonstrate the impact of this work across several research disciplines including multimedia, web, and information retrieval. Overall, the committee recognizes that the thesis has significant impact and makes considerable contributions to the multimedia community.

Bio of Awardee: Dr. Christoph Kofler is a software engineer and data scientist at Bloomberg L.P., NY, USA. He holds a Ph.D. degree from Delft University of Technology, The Netherlands, and an M.Sc. and B.Sc. degree from Klagenfurt University, Austria – all in Computer Science. His research interests include the broad fields of multimedia and text-based information retrieval with focus on search intent inference and its applications for search results optimization throughout the entire search engine pipeline (indexing, ranking, query formulation). In addition to “what” a user is looking for using search, Dr. Kofler is particularly interested in the “why” component behind the search and in the related opportunities for improving the efficiency and effectiveness of information retrieval systems. Dr. Kofler has co-authored more than 20 scientific publications with predominant focus on venues such as ACM Multimedia, IEEE Transactions on Multimedia, and ACM Computing Surveys. He has been a task co-organizer of the MediaEval Benchmark initiative. He received the Grand Challenge Best Presentation Award at ACM Multimedia and the Best Paper nomination at the European Conference on Information Retrieval. Dr. Kofler is a recipient of the Google Doctoral Fellowship in Information Retrieval (Video Search). He has held positions at Microsoft Research, Beijing, China; Columbia University, NY, USA; and Google, NY, USA.