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How Passive Image Viewers Became Active Multimedia Users

New Trends and Recent Advances in Subjective Assessment of Quality of Experience

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Visual Signal Quality Assessment

Abstract

Subjective assessment of quality of experience (QoE) is key to understanding user preferences with respect to multimedia fruition. As such, it is a necessary step to multimedia delivery optimization, since QoE needs to take into account technology limitations as well as user satisfaction. The study of QoE appreciation dates back to the twentieth century, when it exploded with the advent of CRT first and LCD displays later. For a long time, this branch of research was targeted at determining user sensitivity to impairments induced in the media by suboptimal delivery. The media recipient was considered a passive observer, whose appreciation of the video material was determined primarily by the degree of annoyance due to the impairments affecting it. With the advent of mobile technology and Internet-based media delivery, this impairment-centric concept of QoE has shown to be incomplete. The media recipient became an active user who creates content, interacts with the system, and selects the media he/she wants to have delivered. As a result, elements such as visual semantics, user personality, preferences and intent, social and environmental context of media fruition also concur to the final experience assessment. The role played by these elements in QoE and the cognitive/affective processes that underlie them are still to be understood, although several models of QoE appreciation have already been proposed. In this paper, we review the evolution of subjective QoE assessment and models from the impairment-centric approach to a more user-centric approach. We analyze relevant features and factors influencing QoE, and point out future directions for subjective QoE assessment research.

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Redi, J.A., Zhu, Y., de Ridder, H., Heynderickx, I. (2015). How Passive Image Viewers Became Active Multimedia Users. In: Deng, C., Ma, L., Lin, W., Ngan, K. (eds) Visual Signal Quality Assessment. Springer, Cham. https://doi.org/10.1007/978-3-319-10368-6_2

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