User-centered EEG-based multimedia quality assessment

Multimedia users are becoming increasingly quality-aware as the technological advances make ubiquitous the creation and delivery of high-definition multimedia content. While much research work has been conducted on multimedia quality assessment, most of the existing solutions come with their own limitations, with particular solutions being more suitable to assess particular aspects related to user's Quality of Experience (QoE). In this context, there is an increasing need for innovative solutions to assess user's QoE with multimedia services. This paper proposes the QoE-EEG-Analyser that provides a solution to automatically assess and quantify the impact of various factors contributing to user's QoE with multimedia services. The proposed approach makes use of participant's frustration level measured with a consumer-grade EEG system, the Emotiv EPOC. The main advantage of QoE-EEG-Analyser is that it enables continuous assessment of various QoE factors over the entire testing duration, in a non-invasive way, without requiring the user to provide input about his perceived visual quality. Preliminary subjective results have shown that frustration can indicate user's perceived QoE

Avaliação da qualidade de experiência de vídeo em várias tecnologias

Mestrado em Engenharia Eletrónica e TelecomunicaçõesNowadays the internet is associated with many services. Combined with this fact, there is a marked increase of the users joining this service. In this perspective, it is required that the service providers guarantee a minimum quality to the network services. The Quality of Experience of services is quite crucial in the development of services in networks. Also noteworthy, the tra c increase in multimedia services, including video streaming, increases the probability of congesting the networks. In the perspective of the service provider, the monitoring is a solution to avoid saturation in network. This way, this dissertation proposes to develop a platform that allows a multimedia tra c monitoring in the Meo Go service provided by the operator Portugal Telecom Communications. The architecture of the adaptive streaming over HTTP has been studied and tested to obtain the quality of experience metrics. This adaptive streaming technique presents the smooth streaming, an architecture made by Microsoft company, and it is used in the Meo Go service. Then, it is monitored the metrics obtained with the video player. This analysis is done objectively and subjectively. In this phase, the objective implementation of the method allows to obtain the prediction value of the Quality of Experience by consumers. The selected metrics were derived from the state / performance of network and terminal device. The obtained metrics aim to simulate human action in video score quality. Otherwise, subjectively, it is conducted a survey based in a questionnaire to compare methods. In this phase it was created an on-line platform to allow the obtain a greater number of rankings and data processing. In the obtained results, rstly in the smooth streaming player, it is shown the adaptive streaming implementation technique. On the next phase, test scenarios were created to demonstrate the functioning of the method in many cases, with greater relevance for those ones with higher dynamic complexity. From the perspective of subjective and objective methods, these have values that con rm the architecture of the implemented module. Over time, the performance of the scoring the quality of video streaming services approaches the one in a human mental action.Nos dias de hoje a Internet é um dos meios com mais serviços associados. Conjugado a este facto, existe um acentuado aumento de utilizadores a aderir a este serviço. Nesta perspectiva existe a necessidade de garantir uma qualidade mínima por parte dos prestadores de serviços. A Qualidade de Experiência que os consumidores têm dos serviços é bastante crucial no desenvolvimento e optimização dos serviços nas redes. É ainda de salientar que o aumento do tráfego multimédia, nomeadamente os streamings de vídeo, apresenta incrementos na probabilidade de as redes se congestionarem. Na perspectiva do prestador de serviços a monitorização é a solução para evitar a saturação total. Neste sentido, esta dissertação pretende desenvolver uma plataforma que permite a monitorização do tráfego de multimédia do serviço do Meo Go, fornecido pela operadora Portugal Telecom Comunicações. Neste trabalho foi necessário investigar e testar a arquitectura do streaming adaptativo sobre HTTP para ser possível obter métricas de qualidade de experiência. Este streaming adaptativo apresenta a técnica de smooth streaming, sendo esta arquitectura projectada pela empresa Microsoft e utilizada no serviço Meo Go. Posteriormente foram monitorizadas as métricas que se obtiveram no player de vídeo. Esta análise foi realizada de forma objectiva e subjectiva. Nesta fase da implementação objectiva do método em que se pretende obter uma predição do valor de Qualidade de Experiência por parte do consumidor, foram seleccionadas as métricas oriundas do estado/desempenho da rede e do dispositivo terminal. As métricas obtidas entram num processo de tratamento que pretende simular a ação humana nas classificações da qualidade dos vídeos. De outra forma, subjectivamente, foi realizada uma pesquisa, com base num questionário, de modo a comparar os métodos. Nesta etapa foi gerada uma plataforma online que possibilitou obter um maior número de classificações dos vídeos para posteriormente se proceder ao tratamento de dados. Nos resultados obtidos, primeiramente ao nível do player de smooth streaming, estes permitem analisar a técnica de implementação de streaming adaptativo. Numa fase seguinte foram criados cenários de teste para comprovar o funcionamento do método em diversas situações, tendo com maior relevância aqueles que contêm dinâmicas mais complexas. Na perspectiva dos métodos subjectivo e objectivo, estes apresentam valores que confirmam a arquitectura do módulo implementado. Adicionalmente, o desempenho do método em classificar a qualidade de serviço de vídeo streaming, ao longo do tempo, apresentou valores que se aproximam da dinâmica esperada numa ação mental humana

The quality of experience of next generation audio :exploring system, context and human influence factors

PhD ThesisThe next generation of audio reproduction technology has the potential to deliver immersive and personalised experiences to the user; multichannel with-height loudspeaker arrays and binaural techniques offer 3D audio experiences, whereas objectbased techniques offer possibilities of adapting content to suit the system, context and user. A fundamental process in the advancement of such technology is perceptual evaluation. It is crucial to understand how listeners perceive new technology in order to drive future developments. This thesis explores the experience provided by next generation audio technology by taking a quality of experience (QoE) approach to evaluation. System, context and human factors all influence QoE and in this thesis three case studies are presented to explore the role of these categories of influence factors (IFs) in the context of next generation audio evaluation. Furthermore, these case studies explore suitable methods and approaches for the evaluation of the QoE of next generation audio with respect to its various IFs. Specific contributions delivered from these individual studies include a subjective comparison between soundbar and discrete surround sound technology, the application of the Open Profiling of Quality method to the field of audio evaluation, an understanding of both how and why environmental noise influences preferred audio object balance, an understanding of how the influence of technical audio quality on overall listening experience is related to a range of psychographic variables and an assessment of the impact of binaural processing on overall listening experience. When considering these studies as a whole, the research presented here contributes the thesis that to effectively evaluate the perceived quality of next generation audio, a QoE mindset should be taken that considers system, context and human IFs.Engineering and Physical Sciences Research Council (EPSRC) and the British Broadcasting Corporation Research & Development department (BBC R&D