Christian Keimel

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Quality of Experience (QoE) in multimedia applications is closely linked to the end users’ perception and therefore its assessment requires subjective user studies in order to evaluate the degree of delight or annoyance as experienced by the users. QoE crowdtesting refers to QoE assessment using crowdsourcing, where anonymous test subjects conduct(More)
Video quality assessment with subjective testing is both time consuming and expensive. An interesting new approach to traditional testing is the so-called crowdsourcing, moving the testing effort into the internet. We therefore propose in this contribution the QualityCrowd framework to effortlessly perform subjective quality assessment with crowdsourcing.(More)
Research on Quality of Experience (QoE) heavily relies on subjective evaluations of media. An important aspect of QoE concerns modeling and quantifying the subjective notions of 'beauty' (aesthetic appeal) and 'something well-known' (content recognizability), which are both subject to cultural and social effects. Crowdsourcing, which allows employing people(More)
A no-reference video quality metric for High-Definition video is introduced. This metric evaluates a set of simple features such as blocking or blurring, and combines those features into one parameter representing visual quality. While only comparably few base feature measurements are used, additional parameters are gained by evaluating changes for these(More)
Video quality evaluation with subjective testing is both time consuming and expensive. A promising new approach to traditional testing is the so-called crowdsourcing, moving the testing effort into the Internet. The advantages of this approach are not only the access to a larger and more diverse pool of test subjects, but also the significant reduction of(More)
High definition video over IP based networks (IPTV) has become a mainstay in today's consumer environment. In most applications, encoders conforming to the H.264/AVC standard are used. But even within one standard, often a wide range of coding tools are available that can deliver a vastly different visual quality. Therefore we evaluate in this contribution(More)
To improve the prediction accuracy of visual quality metrics for video we propose two simple steps: temporal pooling in order to gain a set of parameters from one measured feature and a correction step using videos of known visual quality. We demonstrate this approach on the well known PSNR. Firstly, we achieve a more accurate quality prediction by(More)
The term “Crowdtesting” refers to subjective user studies which are conducted via crowdsourcing. The anonymous test subjects are remotly conducting the tests in their preferred environment. The advantages of crowdtesting are reduced time and costs for tests, large and diverse panel of international users, and realistic user settings. However, conceptual and(More)
This contribution presents a no-reference video quality metric, which is based on a set of simple rules that assigns a given video to one of four different content classes. The four content classes distinguish between video sequences which are coded with a very low data rate, which are sensitive to blocking effects, which are sensitive to blurring, and a(More)