16K Cinematic VR Streaming

  • Aerts M.
  • Lievens S.
  • Macq J.
  • Rondao Alface P.
  • Stevens C.
  • Tytgat D.
  • Verzijp N.

We present an end-to-end system for streaming Cinematic Virtual Reality (VR) content (also called 360 or omnidirectional content) that is captured at a resolution of 16K at 50Hz, towards mobile untethered VR devices. Besides the usual navigation interactions such as panning and tilting offered by common VR systems, we also provide a zooming interactivity. This allows the VR client to fetch high quality pixels captured at a spatial resolution of 16K that greatly increase perceived quality compared to a 4K VR streaming solution. Since current client devices are not capable of receiving and decoding a 16K video, several optimizations are provided to only stream the required pixels for the current viewport of the user, while meeting strict latency and bandwidth requirements for a qualitative VR immersive experience.

Recent Publications

August 09, 2017

A Cloud Native Approach to 5G Network Slicing

  • Francini A.
  • Miller R.
  • Sharma S.

5G networks will have to support a set of very diverse and often extreme requirements. Network slicing offers an effective way to unlock the full potential of 5G networks and meet those requirements on a shared network infrastructure. This paper presents a cloud native approach to network slicing. The cloud ...

August 01, 2017

Modeling and simulation of RSOA with a dual-electrode configuration

  • De Valicourt G.
  • Liu Z.
  • Violas M.
  • Wang H.
  • Wu Q.

Based on the physical model of a bulk reflective semiconductor optical amplifier (RSOA) used as a modulator in radio over fiber (RoF) links, the distributions of carrier density, signal photon density, and amplified spontaneous emission photon density are demonstrated. One of limits in the use of RSOA is the lower ...

July 12, 2017

PrivApprox: Privacy-Preserving Stream Analytics

  • Chen R.
  • Christof Fetzer
  • Le D.
  • Martin Beck
  • Pramod Bhatotia
  • Thorsten Strufe

How to preserve users' privacy while supporting high-utility analytics for low-latency stream processing? To answer this question: we describe the design, implementation and evaluation of PRIVAPPROX, a data analytics system for privacy-preserving stream processing. PRIVAPPROX provides three properties: (i) Privacy: zero-knowledge privacy (ezk) guarantees for users, a privacy bound tighter ...