On the impact of video stalling and video quality in the case of camera switching during adaptive streaming of sports content

The widespread usage of second screens, in combination with mobile video streaming technologies like HTTP Adaptive Streaming (HAS), enable new means for taking end-users' Quality of Experience (QoE) to the next level. For sports events, these technological evolutions can, for example, enhance the overall engagement of remote fans or give them more control over the content. In this paper, we consider the case of adaptively streaming multi-camera sports content to tablet devices, enabling the end-user to dynamically switch cameras. Our goal is to subjectively evaluate the trade-off between video stalling duration (as a result of requesting another camera feed) and initial video quality of the new feed. Our results show that short video stallings do not significantly influence overall quality ratings, that quality perception is highly influenced by the video quality at the moment of camera switching and that large quality fluctuations should be avoided

ATM network impairment to video quality

Includes bibliographical reference

Computer animation via optical video disc

Thesis (M.S.V.S.)--Massachusetts Institute of Technology, Dept. of Architecture, 1980.MICROFICHE COPY AVAILABLE IN ARCHIVES AND ROTCH. VIDEOCASSETTE IN ROTCH VISUAL COLLECTIONS.Bibliography: leaves 43-45.This paper explores the notion of marrying two technologies: raster-scan computer animation and optical video discs. Animated sequences, generated at non real-time rates, then transfered to video disc, can be recalled under user control at real-time rates. Highly detailed animation may be combined with other media in interactive systems. Such systems inherently offer a greater degree of flexibility to the animator. The implementation of one such system is discussed in detail.by Walter Bender.M.S.V.S

Hybrid video quality prediction: reviewing video quality measurement for widening application scope

A tremendous number of objective video quality measurement algorithms have been developed during the last two decades. Most of them either measure a very limited aspect of the perceived video quality or they measure broad ranges of quality with limited prediction accuracy. This paper lists several perceptual artifacts that may be computationally measured in an isolated algorithm and some of the modeling approaches that have been proposed to predict the resulting quality from those algorithms. These algorithms usually have a very limited application scope but have been verified carefully. The paper continues with a review of some standardized and well-known video quality measurement algorithms that are meant for a wide range of applications, thus have a larger scope. Their individual artifacts prediction accuracy is usually lower but some of them were validated to perform sufficiently well for standardization. Several difficulties and shortcomings in developing a general purpose model with high prediction performance are identified such as a common objective quality scale or the behavior of individual indicators when confronted with stimuli that are out of their prediction scope. The paper concludes with a systematic framework approach to tackle the development of a hybrid video quality measurement in a joint research collaboration.Polish National Centre for Research and Development (NCRD) SP/I/1/77065/10, Swedish Governmental Agency for Innovation Systems (Vinnova

Quality of experience and HTTP adaptive streaming: a review of subjective studies

HTTP adaptive streaming technology has become widely spread in multimedia services because of its ability to provide adaptation to characteristics of various viewing devices and dynamic network conditions. There are various studies targeting the optimization of adaptation strategy. However, in order to provide an optimal viewing experience to the end-user, it is crucial to get knowledge about the Quality of Experience (QoE) of different adaptation schemes. This paper overviews the state of the art concerning subjective evaluation of adaptive streaming QoE and highlights the challenges and open research questions related to QoE assessment