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Best ACM SIGMM 2023 PhD Thesis Award for Silvia Rossi

Publication date: 2023-11-21
Original article on CWI website [here and here]

During the ACM Multimedia Conference (ACM MM 2023), premier conference and a key world event to display scientific achievements and innovative industrial products in the multimedia field, Silvia Rossi, postdoctoral researcher in DIS group, won the 2023 SIGMM Award for Outstanding PhD Thesis in Multimedia Computing, Communications and Applications. This was announced by the organisation during the gala dinner on Wednesday, 1st November.

Silvia received the award thanks to the outstanding research conducted during her PhD which has been recognised with the potential of very high impact in multimedia computing, communication and applications. Her PhD thesis also received the 2022 Lombardi Prize  for the best UCL EEE doctoral thesis.

Silvia was the first PhD student of the Learning And Signal Processing (LASP) group led by Dr Laura Toni. In the last part of her PhD (from October 2020 to June 2021), she joined CWI as a visiting student of the DIS group under the supervision of Prof. Pablo Cesar. Her winning thesis advanced the multimedia state-of-the-art by understanding users’ behaviour in immersive environments and by combining such study with human-centric system optimization. 


Thesis Abstract

Recent technological advances have opened the gate to a novel way to communicate remotely still feeling connected. In these immersive communications, humans are at the centre of virtual or augmented reality with a full sense of immersion and the possibility to interact with the new environment as well as other humans virtually present. These next-generation communication systems hide a huge potential that can invest in major economic sectors. However, they also posed many new technical challenges, mainly due to the new role of the final user: from merely passive to fully active in requesting and interacting with the content. Thus, we need to go beyond the traditional quality of experience research and develop user-centric solutions, in which the whole multimedia experience is tailored to the final interactive user. With this goal in mind, a better understanding of how people interact with immersive content is needed and it is the focus of this thesis. In this thesis, we study the behaviour of interactive users in immersive experiences and its impact on the next-generation multimedia systems. The thesis covers a deep literature review on immersive services and user centric solutions, before develop- ing three main research strands. First, we implement novel tools for behavioural analysis of users navigating in a 3-DoF Virtual Reality (VR) system. In detail, we study behavioural similarities among users by proposing a novel clustering algorithm. We also introduce information-theoretic metrics for quantifying similarities for the same viewer across contents. As a second direction, we show the impact and advantages of taking into account user behaviour in immersive systems. Specifically, we formulate optimal user centric solutions i) from a server-side perspective and ii) a navigation aware adaptation logic for VR streaming platforms. We conclude by exploiting the aforementioned behavioural studies towards a more in- interactive immersive technology: a 6-DoF VR. Overall in this thesis, experimental results based on real navigation trajectories show key advantages of understanding any hidden patterns of user interactivity to be eventually exploited in engineering user centric solutions for immersive systems.


The ACM Special Interest Group on Multimedia (SIGMM) provides a forum for researchers, engineers, and practitioners in all aspects of multimedia computing, communication, storage, and applications. SIGMM sponsors the ACM Multimedia Conference series and ad hoc workshops on emerging areas of multimedia. In addition, SIGMM supports the upcoming "ACM Transactions on Multimedia, Applications, and Computing" (TOMCCAP, early 2005) and the SIGMM Website which contains forums and other relevant material. All SIGMM publications are available through the ACM Digital Library.

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