In viewport-adaptive streaming of omnidirectional video, only the field of view is streamed in high quality. While this has significant benefits over streaming the entire 360 sphere, no standard test method for perceived quality and simulator sickness is available to evaluate the quality of experience (QoE) of such streaming approaches. QoE testing is important as tile-based viewport-adaptive streaming technologies are replacing classical approaches because of significant bandwidth savings and increase in viewing quality. In this work, we propose a testbed, a test method, as well as test metrics for QoE tests of viewport-adaptive streaming approaches. The proposed method is validated in two different test setups, using a specific tile-based streaming technology available in the market. The chosen input variables (videos sequences, resolution, bandwidth, and network round-trip delay) are tested for their statistical significance. We found that our test method is suitable for QoE testing of viewport-adaptive streaming technologies. We also found that simulator sickness scores increase with test duration, but that breaks between tests reduce this effect. With our systematic test approach, it is possible to compare metrics among different test setups. On the tested technology, we found that a typical network delay (47 ms) only has a minimal effect on the quality ratings. Furthermore, the magnitude of the network delay does not influence simulator sickness for the system we have tested.

Mobile networks, especially LTE networks, are used more and more for high-bandwidth services like multimedia or video streams. The quality of the data connection plays a major role in the perceived quality of a service. Videos may be presented in a low quality or experience a lot of stalling events, when the connection is too slow to buffer the next frames for playback. So far, no publicly available data set exists that has a larger number of LTE network traces and can be used for deeper analysis. In this data set, we provide 546 traces of 5 minutes each with a sample rate of 100 ms. Thereof 377 traces are pure LTE data. We furthermore provide an Android app to gather further traces as well as R scripts to clean, sort, and analyze the data.

Dynamic Adaptive Streaming over HTTP (DASH) is a technology for delivering video content over the Internet. It provides an effective mechanism, which has been adopted by major content providers. Nevertheless, available DASH player implementations have a number of drawbacks such as performance problems on shared network connections, which lead to video freezes and frequent video quality changes. In this paper, we propose a method to reduce the performance problems that exist in networks with a large number of DASH players. These networks can be found in hotels, apartment complexes, and airports. In experiments with up to 600 simultaneously active players, we are able to reduce the number of DASH players with freezes by 95% (from 345 to 15) compared to throughput-based adaptation and by 75% (from 62 to 15) compared to BOLA using our DASH Assisting Network Element (DANE). In addition, we reduced the number of quality switches by 94% compared to throughput-based adaptation, and by 85% compared to BOLA.

Hypervideos, consisting of media enriched and linked video scenes, have proven useful in many scenarios. Software solutions exist that help authors make hypervideos from media files. However, recording and editing video scenes for hypervideos is a tedious and time consuming job. Huge video databases like YouTube exist that can provide rich sources of video material. Yet it is often illegal to download and re-purpose videos from these sites, requiring a solution that links whole videos or parts of videos and plays them in an embedded player. This work presents the SIVA Web Producer, a Chrome extension for the creation of hypervideos consisting of scenes from YouTube videos. After creating a project, the SIVA Web Producer embeds YouTube videos or parts thereof as video clips. These can then be linked in a scene graph and extended with annotations. The plug-in provides a preview space for testing the hypervideo. Finalized videos can be published on the SIVA Web Portal or embedded in a Web page.

Due to their structure, hypervideos are well suited for different scenarios. Compared to traditional linear videos, they have advantages especially in e-learning and training, where the study matter can be fitted to the needs of the viewer. In this paper we present the SIVA Suite, an open source framework for the creation, playback, and administration of hypervideos. The SIVA Suite consists of an authoring tool, an HTML5 hypervideo player, and a Web server for user and video management. This framework has been successfully used for the creation of hypervideos in different use cases, e.g. a medical hypervideo training. It was evaluated in several usability tests and improved step-by-step since 2008.

With HTML5 becoming more and more standardized, it is possible to implement platform independent applications running on smartphones, tablets, laptops, and desktop PCs with different operating systems and screen resolutions. A combination of HTML5 with CSS and JavaScript allows the implementation of appealing user interfaces with advanced functionality. In this paper we present an HTML5 player for interactive non-linear videos using these technologies. In addition to standard player functions, our player provides extended navigation (button panels, table of contents, keyword search) in the video, areas for additional information, opportunities for collaboration, and a logging function. The latter allows analyses of the user behavior for further research questions. We also address first user studies.

A literature review on the term "interactive video" and "interactive non-linear video" revealed different levels of interaction in varying definitions. We give a formal definition of the term "interactive non-linear video" to clarify the elements and possible relations between elements contained in such videos. Furthermore, we introduce a new event-based XML format consisting of four required and two optional elements to describe this form of video. A scene graph consisting of scenes with triggers for annotations builds the core of the format. Formal definition and XML format are both illustrated by a real world example.

With rapid improvements in available bandwidth and processing power of smart phones, the presentation of interactive non-linear video became possible. Web players for these form of video already exist, they usually have a video area and one or more annotation areas. Most of them can not be used for mobile phones because of their space consuming representation. This work presents a player to display interactive nonlinear videos on Android smart phones. The small display size and the possibility to switch between portrait and landscape mode have been taken into account. The player also provides functions to manage a library of downloaded interactive videos for off line use as well as bookmarks.

In this paper, an intuitive authoring system and player for interactive non-linear video called SIVA Suite is presented for demonstration. Such videos are enriched by additional content. Possible forms of additional content are plaintext, richtext, images and videos. Interactivity is implemented based upon selection buttons which allow the user to follow different plotlines. Additional forms of interactivity are realized as clickable objects in the video and a table of contents for the video. The software provides a tool for manually cutting videos and an automated shot detection. The non-linear flow of the video can be designed using a scene graph with fork nodes. Editors for text and images support the user in adding information to the video. A finished video project is exported to an XML file with a specific schema and Flash video (flv) files. The player processes the XML file, plays the interactive video and shows additional contents. It can be customized to the requirements of the presentation of the video and the corporate design of the homepage the video is embedded in.