scispace - formally typeset
S

Sebastian Möller

Researcher at Technical University of Berlin

Publications -  531
Citations -  7103

Sebastian Möller is an academic researcher from Technical University of Berlin. The author has contributed to research in topics: Quality (business) & Quality of experience. The author has an hindex of 34, co-authored 491 publications receiving 5830 citations. Previous affiliations of Sebastian Möller include German Research Centre for Artificial Intelligence & University of Oslo.

Papers
More filters
Proceedings ArticleDOI

Google now is for the extraverted, cortana for the introverted: investigating the influence of personality on IPA preference

Patrick Ehrenbrink, +2 more
TL;DR: The personality profile of users and their preference for either Apple's Siri, Google's Now or Microsoft's Cortana, based on attractiveness and psychological state reactance is assessed, revealing how the preference for an IPA depends on a person's character traits.
Proceedings ArticleDOI

A Technique for Seamless VoIP-Codec Switching in Next Generation Networks

Marcel Wältermann, +3 more
TL;DR: This contribution introduces an ergonomic technique that aims at seamlessly switching the speech codec in Voice-over-IP calls during vertical handovers, based on SIP/SDP session renegotiation, the establishment of a parallel media stream and RTP packet filtering.
Book ChapterDOI

Crowdsourcing Quality of Experience Experiments

Sebastian Egger-Lampl, +7 more
TL;DR: In this paper, the differences between laboratory-based and crowd-based QoE evaluation are discussed in order to utilise these advantages, and the difference between laboratory and crowd based evaluation is discussed in this chapter.
Posted Content

Influence of Hand Tracking as a way of Interaction in Virtual Reality on User Experience

Jan-Niklas Voigt-Antons, +3 more
- 27 Apr 2020 - 
TL;DR: Results show that different interaction types statistically significantly influence reported emotions with Self-Assessment Manikin, where for hand tracking participants were feeling higher valence, but lower arousal and dominance, and task type of grabbing was reported to be more realistic, and participants experienced a higher presence.
Proceedings ArticleDOI

DEMI: Deep Video Quality Estimation Model using Perceptual Video Quality Dimensions

Saman Zadtootaghaj, +6 more
TL;DR: In this paper, a deep learning based quality estimation model considering both gaming and non-gaming videos was developed in three phases: a convolutional neural network (CNN) is trained based on an objective metric which allows the CNN to learn video artifacts such as blurriness and blockiness.