English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

Virtual reality has been gaining popularity in recent years caused by theproliferation of affordable consumer-grade devices such as Oculus Rift, HTCVive, and Samsung VR. Amongst the various VR applications, 360{\deg} videostreaming is currently one of the most popular ones. It allows user to changetheir field-of-view (FoV) based on head movement, which enables them to freelyselect an area anywhere from the sphere the video is (virtually) projected to.While 360{\deg} video streaming offers new exciting ways of consuming contentfor viewers, it poses a series of challenges to the systems that areresponsible for the distribution of such content from the origin to the viewer.One challenge is the significantly increased bandwidth requirement forstreaming such content in real time. Recent research has shown that onlystreaming the content that is in the user's FoV in high quality can lead tostrong bandwidth savings. This can be achieved by analyzing the viewers headorientation and movement based on sensor information. Alternatively, historicinformation from users that watched the content in the past can be taken intoaccount to prefetch 360{\deg} video data in high quality assuming the viewerwill direct the FoV to these areas. In this paper, we present a 360{\deg} videostreaming system that transitions between sensor- and content-based predictivemechanisms. We evaluate the effects of this transition-based approach on theQuality of Experience (QoE) of such a VR streaming system and show that theperceived quality can be increased between 50\% and 80\% compared to systemsthat only apply either one of the two approaches.

Increasing the Quality of 360{\deg} Video Streaming by Transitioning between Viewport Quality Adaptation Mechanisms