Angeliki Katsenou | University of Bristol | September 29, 2020 | 10:00 (CET, 08:00 UTC)

Abstract: Cisco reported in the past reports that the video data share was expected to reach 80% by the year 2023. However, due to the pandemic and recently imposed a remote work lifestyle, this figure is expected to increase even more. Except for the on-demand and conferencing services, the number of users that are generating, storing, and sharing their content usually through either social media platforms or video-sharing platforms is increasing. Meanwhile from the video coding perspective, as video technologies evolve towards improved compression performance, their complexity inversely increases.

A challenge that many video service providers face is the heterogeneity of networks and display devices for streaming, as well as dealing with a wide variety of content with different encoding performance. In the past, a fixed bit rate ladder solution based on a „fitting all“ approach has been employed. However, such a content-tailored solution is highly demanding; the computational and financial cost of constructing the convex hull per video by encoding at all resolutions and quantization levels is huge. In this talk, we present a content-agnostic approach that exploits machine learning to predict the bit rate ladder with only a small number of encodes required.

Bio: Angeliki Katsenou is a Leverhulme Early Career Fellow and is with the Visual Information Lab at the University of Bristol since 2015. She obtained her Ph.D. degree from the Department of Computer Science and Engineering, University of Ioannina, Greece (2014). She received her Diploma in Electrical and Computer Engineering and an M.Sc. degree in Signal and Image Processing from the University of Patras, Greece. She has experience in several FP7 EC-funded and EPSRC projects, such as MSCA-ITN PROVISION and EPSRC Platform Grant EP/M000885/1. Her research interests include perceptual video analysis, video compression, image/video quality, and resource allocation for video communication systems. She has also been involved with conference organization activities and is currently one of the Technical Program Co-Chairs for Picture Coding Symposium (PCS) 2021, Bristol, UK.

The review of the TEWI colloquium of Laura Toni from June 26, 2020 comprises the video and slides (below):

Abstract: A major challenge for the next decade is to design virtual and augmented reality systems (VR at large) for real-world use cases such as healthcare, entertainment, e-education, and high-risk missions. This requires VR systems to operate at scale, in a personalized manner, remaining bandwidth-tolerant whilst meeting quality and latency criteria. One key challenge to reach this goal is to fully understand and anticipate user behaviours in these mixed reality settings.

This can be accomplished only by a fundamental revolution of the network and VR systems that have to put the interactive user at the heart of the system rather than at the end of the chain. With this goal in mind, in this talk, we describe our current researches on user-centric systems. First, we describe our view-port based streaming strategies for 360-degree video. Then, we present more in details our research on of users‘ behaviour analysis, when users interact with the 360-degree content. Specifically, we describe a set of metrics that allows us to identify key behaviours among users and quantify the level of similarity of these behaviours. Specifically, we present our clique-based clustering methodology, information theory and trajectory base in-depth analysis. Finally, we conclude with an overview of the extension of this work to navigation within volumetric video sequences.

Bio: Laura Toni received the M.S. and Ph.D. degrees, both in electrical engineering, from the University of Bologna, Bologna, Italy, in 2005 and 2009, respectively. In 2007, she was a Visiting Scholar at the University of California at San Diego (UCSD), San Diego, CA, USA, and since 2009, she has been a frequent visitor to the UCSD, working on media coding and streaming technologies. Between 2009 and 2011, she was with the Tele-Robotics and Application Department, Italian Institute of Technology, investigating wireless sensor networks for robotics applications. In 2012, she was a Postdoctoral Fellow at UCSD, and between 2013 and 2016, she was a Postdoctoral Fellow in the Signal Processing Laboratory (LTS4) at École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland. Since July 2016, she has been a Lecturer in the Electronic and Electrical Engineering Department, University College London (UCL), U.K. Her research mainly involves interactive multimedia systems, decision-making strategies under uncertainty, large-scale signal processing, and communications. She received the UCL Future Leadership Award in 2016, the ACM Best 10% Paper Award in 2013, and the IEEE/IFIP Best Paper Award in 2012.

The review of the TEWI colloquium of Lucia D’Acunto from June 24, 2020 comprises the video and slides (below):

Abstract: In this talk, I will present the recent advancements on 5G for what concerns support for “the media vertical sector”, i.e., use cases involving the transmission of audiovisual content. I will begin by introducing the research that TNO has conducted on this topic in the past few years, starting with the H2020 TRIANGLE project, were we first adapted network orchestration to “communicate” with media orchestration components, such as a DASH Aware Network Element (DANE). Then, I will explain how we created media-specific 5G slices in the context of the H2020 5GINFIRE project, and what benefits media service providers can expect. I will further discuss about the advantages that edge computing offers to video production, based on our results from the H2020 FLAME project. Finally, I will give an overview of the standardization activities around this topic. I will conclude my talk with an outlook on future developments and offer some reflections on what researchers, telecom operators and service providers can expect.

Bio: Lucia D’Acunto received her PhD in 2012 from Delft University of Technology, the Netherlands, with a thesis on video streaming over peer-to-peer networks. She now works as a senior research scientist at TNO, focusing on video distribution and on the impact of future internet architectures (e.g. ICN, SDN and 5G) on it. She has led and is leading various European research projects on these topics, most notably the open call projects from the European Projects TRIANGLE, 5GINFIRE and FLAME. Since 2016, Lucia is an active participant and contributor to the 3GPP SA4 group, which focusses on mobile and 5G standardization for media applications. Lucia also serves in the organizing committees of several international conferences, usually in the roles of program chair or demo chair, and in the program committees. Lucia also regularly advises European operators on network and TV technologies and contributes to 5GPPP and NEM visions on the 5G Media Vertical and pilots. Lucia has published her research in several papers and journals and holds more than 15 patent applications.

Lucia D’Acunto | TNO | Wednesday, June 24, 2020 | 14:00 (CET, 12:00 UTC) | online (registration required for external attendees)

Abstract: In this talk, I will present the recent advancements on 5G for what concerns support for “the media vertical sector”, i.e., use cases involving the transmission of audiovisual content. I will begin by introducing the research that TNO has conducted on this topic in the past few years, starting with the H2020 TRIANGLE project, were we first adapted network orchestration to “communicate” with media orchestration components, such as a DASH Aware Network Element (DANE). Then, I will explain how we created media-specific 5G slices in the context of the H2020 5GINFIRE project, and what benefits media service providers can expect. I will further discuss about the advantages that edge computing offers to video production, based on our results from the H2020 FLAME project. Finally, I will give an overview of the standardization activities around this topic. I will conclude my talk with an outlook on future developments and offer some reflections on what researchers, telecom operators and service providers can expect.

Bio: Lucia D’Acunto received her PhD in 2012 from Delft University of Technology, the Netherlands, with a thesis on video streaming over peer-to-peer networks. She now works as a senior research scientist at TNO, focusing on video distribution and on the impact of future internet architectures (e.g. ICN, SDN and 5G) on it. She has led and is leading various European research projects on these topics, most notably the open call projects from the European Projects TRIANGLE, 5GINFIRE and FLAME. Since 2016, Lucia is an active participant and contributor to the 3GPP SA4 group, which focusses on mobile and 5G standardization for media applications. Lucia also serves in the organizing committees of several international conferences, usually in the roles of program chair or demo chair, and in the program committees. Lucia also regularly advises European operators on network and TV technologies and contributes to 5GPPP and NEM visions on the 5G Media Vertical and pilots. Lucia has published her research in several papers and journals and holds more than 15 patent applications.

Laura Toni | University College London (UCL), U.K | Friday, June 26, 2020 | 10:00 (CET, 8am UTC)

Abstract: A major challenge for the next decade is to design virtual and augmented reality systems (VR at large) for real-world use cases such as healthcare, entertainment, e-education, and high-risk missions. This requires VR systems to operate at scale, in a personalized manner, remaining bandwidth-tolerant whilst meeting quality and latency criteria. One key challenge to reach this goal is to fully understand and anticipate user behaviours in these mixed reality settings.

This can be accomplished only by a fundamental revolution of the network and VR systems that have to put the interactive user at the heart of the system rather than at the end of the chain. With this goal in mind, in this talk, we describe our current researches on user-centric systems. First, we describe our view-port based streaming strategies for 360-degree video. Then, we present more in details our research on of users‘ behaviour analysis, when users interact with the 360-degree content. Specifically, we describe a set of metrics that allows us to identify key behaviours among users and quantify the level of similarity of these behaviours. Specifically, we present our clique-based clustering methodology, information theory and trajectory base in-depth analysis. Finally, we conclude with an overview of the extension of this work to navigation within volumetric video sequences.

Bio: Laura Toni received the M.S. and Ph.D. degrees, both in electrical engineering, from the University of Bologna, Bologna, Italy, in 2005 and 2009, respectively. In 2007, she was a Visiting Scholar at the University of California at San Diego (UCSD), San Diego, CA, USA, and since 2009, she has been a frequent visitor to the UCSD, working on media coding and streaming technologies. Between 2009 and 2011, she was with the Tele-Robotics and Application Department, Italian Institute of Technology, investigating wireless sensor networks for robotics applications. In 2012, she was a Postdoctoral Fellow at UCSD, and between 2013 and 2016, she was a Postdoctoral Fellow in the Signal Processing Laboratory (LTS4) at École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland. Since July 2016, she has been a Lecturer in the Electronic and Electrical Engineering Department, University College London (UCL), U.K. Her research mainly involves interactive multimedia systems, decision-making strategies under uncertainty, large-scale signal processing, and communications. She received the UCL Future Leadership Award in 2016, the ACM Best 10% Paper Award in 2013, and the IEEE/IFIP Best Paper Award in 2012.

Giovambattista Ianni | University of Calabria, Italy | Wednesday, February 19th, 2020 | 14:00 s.t. | room S.1.42

Abstract:
The availability of advanced features for controlling technical aspects of grounding engines and solver modules for the answer set semantics allows great flexibility and enables the possibility to scale in otherwise out of reach applications. Nonetheless, the presence of nonobvious heuristic tuning „knobs“ deepens and widens the gap between knowledge representation technologies and software developers. In this talk, we present our recent introduction of incremental grounding techniques for answer set solvers in the perspective of videogame development, a challenging applicative domain in which design-time fast prototyping and run-time speed are at the highest priority.

Same as in-stream reasoning, videogames require repeated and fast-paced executions of decision-making tasks. In this context, we illustrate an incremental grounding approach for the answer set semantics. We focus on the possibility of maintaining incrementally larger ground logic programs; so-called „overgrounded programs“ can be generated, updated and reused transparently to the user and in combination with deliberately many different sets of inputs. The update burden of overgrounded programs requires a small effort, thus making the instantiation of logic programs considerably faster when grounding is repeated on a series of inputs similar to each other.

CV: Giovambattista Ianni is a full professor of Computer Science in the Department of Mathematics and Computer Science at the University of Calabria, Italy. Prof. Ianni’s current research interests include knowledge representation, reasoning, and coupling of hybrid systems. He recently focused his research interests on Artificial Intelligence in videogames with particular attention to the issue of complex and time-consuming incremental reasoning in real-time contexts. He has contributed to the DLV system and the DLVHEX system, especially dealing with the issue of dealing with, often non-symbolic, external information to knowledge bases. He has been involved in several national and international research projects and has been acknowledged with research awards such as the ICLP Test-of-time award 2018 and the Artificial Intelligence Journal Prominent Paper Award 2013.

Björn Thór Jónsson, Associate Professor

IT University of Copenhagen, Denmark & Reykjavik University, Iceland

02.03.2020 | 10.00 | S.2.42

Abstract:

Scalable retrieval of high-dimensional feature vectors is an important component of many applications in multimedia and other fields, but also a very challenging problem. In this talk, we discuss the challenges of high-dimensional indexing at scale, and then present two approximate indexing methods designed for large-scale retrieval. We present results from experiments with the two largest feature collections reported in the literature, 28.5 billion SIFT features on a single server and 42.9 billion SIFT features in a distributed setting, and demonstrate an application with interactive retrieval over the 99.2 million images of the YFCC100M collection.

CV:

Björn Þór Jónsson is an Associate Professor at the IT University of Copenhagen, Denmark, and Reykjavík University, Iceland. Björn works in the broad field of Multimedia Analytics, applying multi-dimensional analysis concepts and techniques to large-scale multimedia collections.

Previously, Björn studied scalability of multimedia retrieval, where he was involved with the two largest feature vector collections reported in the literature. Björn has a special interest in promoting demonstrations, live events, and reproducibility, e.g. serving as Reproducibility Chair for ACM Multimedia 2019 and 2020. He served as general co-chair for MMM 2017 and CBMI 2019, and will co-organize ACM ICMR 2020 and SISAP 2020.

Prof. Daniele Fontanelli (Università degli Studi di Trento) 

24.01.2020 | 09.00 | B04a.1.06 (Lakeside Park)

Abstract:

Service robots are becoming more and more pervasive in modern societies. One of the ever increasing field of application are service robots able to help seniors in their daily duties. Indeed, ageing is generally associated with a decrease in mobility and social interaction: a growing body of research suggests that reduced levels of out-of-home mobility can have widespread, detrimental effects for older adults. With the median age in Europe projected to grow from 37.7 (2003) to 52.3 (2050), the population asking for mobility aids at an affordable price is becoming substantial.

In this talk, we briefly introduce our solution conceived for autonomous mobility: the FriWalk (i.e. Friendly Walker). Stemming from this example, we will present the fundamental problems for autonomous robots, i.e. localization, planning and control, with application-related scenarios. In particular, we will focus on three aspects of the technological solutions: the localisation problem using different low-cost sensing solutions, together with an optimal landmarks placement algorithm; the set of controlled guidance solutions implementing the authority sharing paradigm and modelled as hybrid systems; the activity and reactive planning approaches in actual application scenarios.

CV:

Daniele Fontanelli received the MSc degree in Information Engineering in 2001, and the Ph.D. degree in Automation, Robotics and Bioengineering in 2006, both from the University of Pisa, Italy.  He was a Visiting Scientist with the Vision Lab of the University of California at Los Angeles, US, and an Associate Researcher with the Interdepartmental Research Center „E. Piaggio“, University of Pisa.  From 2008 he joined the University of Trento, Italy, where he is now an Associate Professor at the Department of Industrial Engineering.   He is currently an Associate Editor for the IEEE Transactions on Instrumentation and Measurement and for the IET Science, Measurement & Technology Journal.His research interests include localisation algorithms, service robotics, motion planning, human motion modelling, real-time control and estimation, and resource aware control.

Assoc.-Prof. Rui Abreu (Universität Lissabon) | 19.12.2019 | 10:00 Uhr | S.1.37

Abstract:

In the past decade, research on test-suite-based automatic program repair has grown significantly. Each year, new approaches and implementations are featured in major software engineering venues. However, most of those approaches are evaluated on a single benchmark of bugs, which are also rarely reproduced by other researchers. In this paper, we present a large-scale experiment using 11 Java test-suite-based repair tools and 2,141 bugs from 5 benchmarks. Our goal is to have a better understanding of the current state of automatic program repair tools on a large diversity of benchmarks. Our investigation is guided by the hypothesis that the repairability of repair tools might not be generalized across different benchmarks. We found that the 11 tools 1) are able to generate patches for 21% of the bugs from the 5 benchmarks, and 2) have better performance on Defects4J compared to other benchmarks, by generating patches for 47% of the bugs from Defects4J compared to 10-30% of bugs from the other benchmarks. Our experiment comprises 23,551 repair attempts, which we used to find causes of non-patch generation. These causes are reported in this presentation, which can help repair tool designers to improve their approaches and tools. This work was presented at ESEC/FSE19 and was given an ACM SIGSOFT Distinguished Paper Award.

CV:

Rui Abreu holds a Ph.D. in Computer Science – Software Engineering from TU Delft, The Netherlands, and a M.Sc. in Computer and Systems Engineering from the U.Minho, Portugal. His research revolves around software quality, with emphasis on automating the testing and debugging phases of the software development life-cycle as well as self-adaptation. He is the recipient of 7 Best Paper Awards (including a 2019 FSE  Distinguished Paper Award). Before joining IST, U.Lisbon as an Associate Professor (with habilitation), he was a member of the Model-Based Reasoning group at PARC’s System and Sciences Laboratory. He has co-founded DashDash in January 2017, a platform to create web apps using only spreadsheet skills. Currently, he is enjoying a sabbatical leave as a Visiting Scientist at Google NY’s. He is also passionate about soccer and a FC Porto fan.

Prof. Dr. Alexander Salle (Institut für Mathematik, Universität Osnabrück) | 12.12.2019 | 17:15 Uhr | C.0.16 (Gebäude Sterneckstraße)

Kurzfassung/Abstrakt: »Zum Denken benötigt der Mensch lediglich sein Gehirn« – insbesondere im Hinblick auf das Lernen einer abstrakten Disziplin wie Mathematik ist diese Auffassung weit verbreitet. Viele Forschungsarbeiten der letzten Jahre verdeutlichen jedoch die zentrale Rolle des Körpers in mathematischen Lern- und Kommunikationsprozessen. Im Vortrag werden empirische Ergebnisse vorgestellt, anhand derer die Bedeutung von Gesten für die Analyse von Kommunikations- und Lernprozessen herausgearbeitet sowie Konsequenzen für die Erforschung und Gestaltung mathematischer Lehr-Lern-Arrangements diskutiert werden. Gerahmt werden die Ergebnisse durch theoretische Betrachtungen zu Gesten und Multimodalität.

Lebenslauf: Studium des Gymnasiallehramts (2008) und Diplommathematik (2009), Promotion zum Dr. phil (2014) an der Universität Bielefeld 2014, seit 2015 Juniorprofessur für Didaktik der Mathematik an der Universität Osnabrück, 2018 Habilitationsäquivalenz durch positive Evaluation, Arbeitsgebiete: Analyse mathematischer Lernprozesse aus multimodaler Perspektive; Bedeutung von Gesten, Notizen und Mitschriften für mathematikbezogene Lern- und Kommunikationsprozesse, Grundvorstellungen mathematischer Inhalte (insbes. im Bereich der Trigonometrie), Übergang Schule-Hochschule, Mathematik und digitale Medien.