Dr.-Ing. Mathias Wien, RWTH Aachen University | May 14, 2018 | 16:00 | E.2.42

Abstract: In October 2017, ISO/IEC JCT1 SC29/WG11 MPEG and ITU-T SG16/Q6 VCEG have jointly published a Call for Proposals on Video Compression with Capability beyond HEVC and its current extensions. It is targeting at a new generation of video compression technology that has substantially higher compression capability than the existing HEVC standard. The responses to the call are evaluated in April 2018, forming the kick-off for a new standardization activity in the Joint Video Experts Team (JVET) of VCEG and MPEG, with a target of finalization by the end of the year 2020. Three categories of video are addressed: Standard dynamic range video (SDR), high dynamic range video (HDR), and 360° video. While SDR and HDR cover variants of conventional video to be displayed e.g. on a suitable TV screen at very high resolution (UHD), the 360° category targets at videos capturing a full-degree surround view of the scene. This enables an immersive video experience with the possibility to look around in the rendered scene, e.g. when viewed using a head-mounted display. This application triggers various technical challenges which need to be addressed in terms of compression, encoding, transport, and rendering. The talk summarizes the current state of the complete standardization project. Focussing on the SDR and 360° video categories, it highlights the development of selected coding tools compared to the state of the art. Representative examples of the new technological challenges as well as corresponding proposed solutions are presented.

Bio: Mathias Wien received the Diploma and Dr.-Ing. degrees from RWTH Aachen University, Germany, in 1997 and 2004, respectively. He currently works as a senior research scientist, head of administration, and lecturer, at the Institute of Communication Engineering of RWTH Aachen University, Germany. His research interests include image and video processing, immersive, space-frequency adaptive and scalable video compression, and robust video transmission. With respect to standardization, Mathias has contributed to ITU-T VCEG, ISO/IEC MPEG, as well as their collaborative teams, the Joint Video Experts Team, the Joint Collaborative Team on Video Coding (JCT-VC), and the Joint Video Team (JVT), in the standardization work towards the successor of HEVC, HEVC, and AVC, respectively. In standardization, he has co-chaired and coordinated several AdHoc groups as well as tool- and core experiments. He has authored and co-authored more than 60 conference and journal papers in the area of video coding,  as well as 18 granted patents. He has published the Springer textbook “High Efficiency Video Coding: Coding Tools and Specification”, which fully covers Version 1 of HEVC. Mathias is a member of the IEEE Signal Processing Society and the IEEE Circuits and Systems Society.

Links:

• Web site
• Google Scholar

Massimiliano Di Penta | April 4, 2018 | 13:30 | E 2.42

Abstract: The availability of a wide variety of software repositories, ranging from Questions and Answer forums to mailing lists, forges and issue trackers opens the road for building recommender systems aimed at supporting developers in their activities. Upon evaluating such recommenders, in most cases researchers focus on the underlying approach capability of providing accurate and complete results.
In this seminar I will report our experience in evaluating recommenders, showing that an offline evaluation of the approach precision and recall is only a very preliminary starting point. Importantly, different kinds of evaluations having different size and level of control, and above all involving humans, are required to achieve results able to convince practitioners of the actual usefulness and applicability of a tool. Moreover, I will discuss how context plays a paramount role in the empirical evaluation of recommender systems.

Bio: Massimiliano Di Penta is associate professor at the University of Sannio, Italy. His research interests include software maintenance and evolution, mining software repositories, empirical software engineering, search-based software engineering, and testing. He is author of over 250 papers appeared in international journals, conferences and workshops, and received various awards for his research and reviewing activity, including two most influential paper awards (SANER 2017 and GECCO 2015) and three ACM SIGSOFT Distinguished Paper Awards (ICSE, FSE and ASE). He serves and has served in the organizing and program committees of over 100 conferences such as ICSE, FSE, ASE, ICSME, ICST, MSR, SANER, ICPC, GECCO, WCRE, and others. He is currently member of the steering committee of ICSME, MSR, and PROMISE. Previously, he has been steering committee member of other conferences, including ICPC, SSBSE, CSMR, SCAM, and WCRE. He is in the editorial board of ACM Transactions on Software Engineering and Methodology, the Empirical Software Engineering Journal edited by Springer, and of the Journal of Software: Evolution and Processes edited by Wiley. He has served the editorial board of IEEE Transactions on Software Engineering.

Links:

• Web site
• Google Scholar

The review of the TEWI colloquia of Csaba Szabó from February 7, 2018 comprises the slides.

Slides:

The review of the TEWI colloquia ofDr. Marko Tkalčič from December 21, 2017 comprises the slides.

Slides:

Abstract

The talk will cover the research carried out by the author in the domain of psychologically-driven personalized systems. In order to be truly personalized a system needs to understand the user. Current systems employ data-driven models, such as recommendations based on past ratings, clicks or purchases. However, psychologically-grounded models appear to have potential for better personalized systems. The author will cover models of emotions and personality, the unobtrusive acquisition thereof through social media crawling, video processing and machine learning and their use in personalization algorithms.

Bio

Marko Tkalčič is Assistant Professor at the Faculty of Computer Science at the Free University in Bolzano, Italy. He received his PhD from the Faculty of Electrical Engineering at the University of Ljubljana in 2011. After a postdoc at the University of Ljubljana, he worked as a postdoc at the Johannes Kepler University in Linz, Austria from 2013 to 2015. From 2016 he is with the Free University of Bolzano. His research explores ways in which psychologically-motivated user characteristics, such as emotions and personality, can be used to improve personalized systems. It employs methods such as user studies and machine learning.

Dr. Tkalčič has published in prestigious journals, such as Elsevier Information Sciences and Springer UMUAI. He has presented at venues, such as RecSys and UMAP. Recently he edited the book Emotions and Personality in Personalized Systems with Springer. He is active in organizing conferences (RecSys 2017, UMAP 2017) and workshops (EMPIRE, SOAP, HUMANIZE), editing special issues, and reviewing for prestigious journals, conferences and grant bodies. He is a member of the editorial board of the UMUAI journal.