Why Quality of Experience (QoE) of Multimedia Services is important?
Day by day we are facing an enormous growth of multimedia applications market as a wide spectrum of end-user devices combines with different efficient core and access network technologies. Some of these applications will mature and survive while others will disappear after their initial flash out. The crucial factor for a market success of an emerging application is its holistic design process including content issues, service management, service context, user profiles, and last but not least impact of an underlying network technology (expressed by Quality of Service parameters).
All these facets contribute to the Quality of the user Experience (QoE) being a measure of how users evaluate the obtained service. The accurate prediction of QoE measures in terms of different application facets is a powerful tool when aiming at deployment of successful services.
Reliable QoE measuring is difficult since volatile user opinions have to be taken into account. Surveying users is tricky since even small difference in the way the question was prepared can change results. Moreover, knowing the target question, which could be: “what is probability that a user would inform the company call center about a distortion?” does not show how to ask a user. The Quality of Experience of Multimedia Services team is working both on subjective experiment specifications and objective QoE metrics relating QoE with service conditions. To achieve this goal we deploy specific statistical survey analysis tools enabling better understanding how a user scores.
The research on QoE is not limited to 2D entertainment services. As for example, it is being investigated how to assess immersive media subjective video quality. The first step is to perform subjective experiments that examine crosstalk. These subjective experiments provide valuable feedback on both acceptable levels of crosstalk and how to perform a reliable and repeatable immersive media subjective test.
Furthermore, as for another example, users of video to perform tasks (CCTV public safety, telemedicine services, and firefighters) require sufficient video quality to recognize the information needed for their application. Therefore, the fundamental measure of video quality in these applications is the success rate of these recognition tasks, which is referred to as visual intelligibility or acuity. One of the major causes of reduction of visual intelligibility is loss of data, through various forms of compression. Additionally, the characteristics of the scene being captured have a direct effect on visual intelligibility and on the performance of a compression operation-specifically, the size of the target of interest, the lighting conditions, and the temporal complexity of the scene. Series of application specific tests are being performed in order to study the effects and interactions of compression and scene characteristics. An additional goal is to test existing or develop new objective measurements that will predict the results of the subjective tests of visual intelligibility.
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