Emotional Aspects and Quality of Experience for Multifactor Evaluation of Audiovisual Content

Author(s):  
George Kalliris ◽  
Maria Matsiola ◽  
Charalampos Dimoulas ◽  
Andreas Veglis

The present paper investigates multifactor audiovisual-content quality evaluation strategies, in mediated communication. The primary aims of the work are to identify, describe and model the mechanisms that the attributes of source content and its encoding properties influence the communication process and the involved emotional aspects in terms of Quality of Experience (QoE), information perception and understanding. Mediated learning constitutes a demanding thus suitable investigation case-study, where communication efficiency can be monitored with the use of applicable Quality of Learning (QoL) parameters, such as the learning outcome and its relation to the prior knowledge status. Real-world e-learning scenarios are utilized for sentiment analysis tests combined with QoE/QoL evaluation, using both subjective scores and perceptually-adapted metrics. This experimental research attempts to monitor communication efficiency and its relation to the quality and emotional impact of the mediated content, offering new insights in mediated learning and broader audiovisual communication services.

Author(s):  
Maria Luiza Carlos Riato ◽  
Maria Isabel Ramos do Amaral ◽  
Vanessa B. Campoy Rocha ◽  
Raquel Mezzalira ◽  
Guita Stoler

Exploring emotional aspects commonly associated with the symptom of dizziness is essential for a better understanding and prognosis of vestibular disorder, once it is known that dizziness can be associate as a cause or consequence from psychological disorders. The aim of this study was to analyse the emotional impact caused by dizziness/vertigo symptom in vestibulopathic patients comparing two protocols: Dizziness Handicap Inventory (DHI) and Questionário de Impacto Emocional da Vertigem (CIEV). We concluded that both questionnaires can be used to evalute the impact of dizziness in patients' quality of life, but they explore different aspects being considered complementary during the diagnosis and for a better prognosis.


2017 ◽  
Vol 9 (3) ◽  
pp. 340-344
Author(s):  
Vytautas Abromavičius

Development of new multimedia technologies allows us to receive better quality of audio and video content. Quality of Experience (QoE) evaluates given content from the consumer’s perspective. This measurement allows to evaluate not only visual and audible quality, but also general acceptability of provided service. QoE evaluation is getting popular between engineers, designers, retailers who wants to provide high quality content for consumers. QoE is generally evaluated subjectively by surveys. It is possible to find relationship between physiological signals measured while user is consuming audiovisual content and make the subjective evaluation of this experience. This paper investigates relationship between heart rate and QoE while user is watching 1 min duration video recordings on three different devices. Heart rate was calculated as mean RR interval for each recording. Mean RR intervals of 0.848 s, 0.869 s and 0.884 s were calculated for low, medium and high QoE device configurations, respectively. ANOVA analysis results indicates a relation between heart rate and QoE level. The results can help to develop further the investigations of QoE level and heart rate relationship for various subjective assessment, device configurations and content provided.


Author(s):  
Rigas Kotsakis ◽  
Charalampos Dimoulas ◽  
George Kalliris ◽  
Andreas Veglis

The present paper focuses on the extraction and evaluation of salient audiovisual features for the prediction of the encoding requirements in audiovisual content. Recent research showed that encoding decisions can be really crucial during audiovisual mediated communication, where poor encoding may lead to unaccepted Quality of Experience (QoE) or even to the creation of negative emotional response. In contrast, exaggerated high quality encoding may create increased bandwidth demands that are associated with annoying delays and irregular playback flow, resulting again in QoE degradation with similar emotional repulsion. Thus, there has to be a careful treatment with proper encoding balance during the production and deployment of mediated communication audiovisual resources. Such machine-assisted creativity is investigated in the current work, with the utilization of applicable audiovisual features, QoE metrics and emotional measures, aiming at implementing intelligent models for optimal audiovisual production and encoding configuration in demanding mediated communication applications and services.


Author(s):  
Thomas He ◽  
Chelsea DeGuzman ◽  
Leon Zucherman ◽  
Tiffany Tong ◽  
Mark Chignell

In this paper we explore how memories of experience with streaming video affect Quality of Experience (QoE) indicators that are of interest to service providers and marketers. Since observations of experience are time consuming, and the effects of technical quality (TQ) are difficult to entangle from content quality (CQ), we examined the impact of a visualization methodology for assessing experiences. A study was carried out to examine how well overall technical quality (TQ) judgments for a sequence of visualized video experience (a picture of a red video playbar with yellow portions indicating disrupted video in place of actually viewed video) would correspond to overall TQ judgments made after watching a sequence of actual videos. Sequencing effects found in overall TQ ratings, made after viewing visualizations (with their overlaid disruptions) were similar to sequencing effects found after viewing actual videos. However, the sequencing effects after viewing the visualizations were less pronounced than the corresponding sequencing effects that were found after viewing actual videos. Sequences of both visualized and actually viewed videos showed significant negative end effect and trend effects (both positive and negative). There was also evidence that sequencing effects respond to relative change in TQ rather than absolute TQ.


2021 ◽  
Vol 20 (3) ◽  
pp. 1-25
Author(s):  
Elham Shamsa ◽  
Alma Pröbstl ◽  
Nima TaheriNejad ◽  
Anil Kanduri ◽  
Samarjit Chakraborty ◽  
...  

Smartphone users require high Battery Cycle Life (BCL) and high Quality of Experience (QoE) during their usage. These two objectives can be conflicting based on the user preference at run-time. Finding the best trade-off between QoE and BCL requires an intelligent resource management approach that considers and learns user preference at run-time. Current approaches focus on one of these two objectives and neglect the other, limiting their efficiency in meeting users’ needs. In this article, we present UBAR, User- and Battery-aware Resource management, which considers dynamic workload, user preference, and user plug-in/out pattern at run-time to provide a suitable trade-off between BCL and QoE. UBAR personalizes this trade-off by learning the user’s habits and using that to satisfy QoE, while considering battery temperature and State of Charge (SOC) pattern to maximize BCL. The evaluation results show that UBAR achieves 10% to 40% improvement compared to the existing state-of-the-art approaches.


2021 ◽  
Vol 25 (2) ◽  
pp. 133-155
Author(s):  
Sarvesh Sawant ◽  
Aswathi Nair ◽  
Shaik Aisha Sultana ◽  
Arjun Rajendran ◽  
Kapil Chalil Madathil

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