Extending a 360° Video Cloud Playout  

Student Project (1-3 participants), Bachelor Thesis

The Fraunhofer FOKUS 360° Video Cloud Streaming system (read more here) enables high quality 360° video experience on low capability devices, such as Hybrid TVs (HBBTV), or in cases of constrained network connectivity e.g. on mobile devices. VR-Glasses are a hot topic right now and we believe bringing this immersive experience to Smart-TVs allows to address a much wider audience, since TVs are much more widespread. 

This solution allows content providers and broadcasters to provide an innovative video experience to traditional TV screens. Viewers can experience video content with freely selectable views on their primary video viewing device – the large TV screen. Enriching this technology with a wide range of features addressing viewers as well as broadcasters helps acceptance and spreading of this technology. 

Your tasks:

  • Native 360° Video Player 

Standard Video Player implementations use their own buffering strategies to ensure smooth video playback. In our 360° video streaming case this behavior is not wanted because it adds up the delay between user input and reaction in the video. Hence a player with low delay and therefore full buffer control is necessary. This is possible either native on a Smart TV or web based with MSE support (and using an open source video player).

  • Record user path

Record and playback the viewing path a user has chosen during his session. 

  • Pausing a 360° Video

Currently it is not possible to pause a 360° Video due to limitations with the buffering strategies and general streaming challenges. Your task is to allow the user to pause the video and restart playback without major latencies. As an extension to this function, a user can even change the (paused) perspective.

  • Cube maps instead equirectangular video

As source videos we use equirectangular videos. These are mapped on to a sphere and being rendered in openGL. The calculations for a sphere are much more complex than for a cube. Therefore we want to experiment with cubemaps to make the rendering process more efficient.

Required skills:

  • Web Technologies: JavaScript, Node.js, PHP, HTML, CSS
  • Programming Languages: C/C++

Related Technologies:


Related FAME Projects:


Contact:

Sascha Braun 

Adaptive Streaming of 360° and panoramic videos

Student project (2 participants), Bachelor- and Master Thesis

MPEG-DASH enables multiple representations with varying bitrate and resolution for media streams. One part of the DASH specification deals with the support for 360 degree and panoramic videos. The goal for that specific type of videos is to selectively deliver certain parts and regions which are of interest for the viewer. A typical use case for panoramic and 360° videos is the live streaming of a sport event where the viewer can dynamically switch between different available areas in the stadium.

Open source players like dash.js and Shaka enable streaming of DASH content in the browser without the need for external plugins. However, they still lack in support and interfaces for the streaming of 360° and panoramic videos.


Your Tasks:

  • Understand the technology behind 360° and panoramic videos in MPEG-DASH
  • Research and develop use cases
  • Extend open source players 
Required skills:

  • Web Technologies: JavaScript, HTML, CSS
  • Basic Knowledge in media streaming


Related technologies:


Related FAME projects:


Contact: 

Stefan Pham

Daniel Silhavy

Virtual Reality and 360° Video Analytics: User Tracking and View-Field Prediction for Future Video Presentations

Student Project (1-3 participants), Master Thesis

The Fraunhofer FOKUS 360° Video Cloud Streaming solution enables high quality 360° video experience on low capability devices, such as Hybrid TVs (HBBTV), or in cases of constrained network connectivity e.g. on mobile devices. In 360° video the full spherical image of any direction of view is available in every moment while the spectator can freely change her individual perspective of view. Thus for a high quality partial view on the scene the necessary source video material becomes quite large.

This solution allows content providers and broadcasters to provide an innovative video experience to traditional TV screens. Viewers can experience video content with freely selectable views on their primary video viewing device – the large TV screen. The capability of view analytics allows content producers and advertisers to get specific information what viewers are interested in and what part of the scene they are watching, allowing detailed feedback about home user interests that wasn't previously available outside of limited lab trials.

You shall realize the following tasks:

  • View behavior analysis per user (persist the viewed camera angle in a 360° video etc.)
  • Reporting of clustered viewing behaviors on a video player with the help of heat map overlays
  • Integration into the existing FAME infrastructure
  • Live- and on-Demand-Reporting for 360° Live-Streams 
  • Creation of Cam-Tracks: e.g. average viewing hot spots or tracking shots
  • Filtering User-Groups: e.g. by IP (region), User-Agent (device) etc.
  • Prediction and recommendation of current and future camera tracks in real time

Required skills:

  • Good programming/ prototyping skills in HTML/ JS as well as in server technologies of your choice
  • Optional: High-Level Understanding of Data Mining/ User Profiling
  • Creative ideas, analytical skills and autonomous acting

Related technologies:

  • Video Delivery Technologies
  • Predictive Data Mining

Related FAME Projects:


Contact:

Christopher Krauß