360° Video Streaming

With the help of live analysis of users' head movements by sensors and historical knowledge about user behaviour, for example which areas of 360° videos were viewed most frequently, it is possible to predict which area of the video the user will view next.

This prediction can be used to load the expected viewed areas in high quality, and the areas outside this viewing area in low resolution, which can save bandwidth. A transition of these two prediction mechanisms can increase the perceived quality of the user.

Participating subprojects and awards

  • 2 participating subprojects (C3, B4)
  • International cooperation with Mercator Fellow (Michael Zink, UMASS AMHERST)
  • 2 Software projects