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Multimedia (VR/AR) Analytics with 5G
Edge Nodes
Bhojan Anand, National University of Singapore
Agenda
• VR/AR Consumer Adoption
• Role of Edge Nodes and 5G
• Key Challenges – Streaming,
Tracking, Analytics
Consumer Adoption-
Lack of quality contents
Any Killer-App for MASS
adoption?
Source: eMarketer.com
Lack of quality contents ranks high in a
recent survey on
“Primary Obstacle to Mass Adoption of
AR/VR Technology”
Consumer Adoption – Not compact enough
• Does not look and feel like everyday glasses to use for most of the
context sensitive applications.
best AR glass on the market
Consumer Adoption – other issues
• VR Hardware Limitations
• Motion Sickness with
controller based navigation,
FoV (110 vs required 190),
Resolution
• AR
• Lack of a geospatial social
“AR Cloud” that would
make the glasses
contextually aware
Field of View (FoV)
Eye 350 + Head 600 = 950. Both sides : 95 x 2 = 1900
Technology is still not perfect for consumer/entertainment market
Consumer Adoption – Focus shifts towards
Commercial/Industrial market
Technology is still not perfect for consumer/entertainment market
image courtesy: Qualcomm Technologies
A glimpse of future
light-weight AR/VR glasses
Technologies to enable MASS adoption
(Making the standalone devices powerful with the
edge nodes)
1. VR Cloud/edge Streaming
2. Edge nodes & analytics
•Object Recognition
•Realtime 3D Mesh Reconstruction and Crowdsourcing
to Build the world (AR Cloud)
Tethered VR
Wireless VR – 60 Ghz
VR Standalone
Needs the cloud support for highly immersive contents
Streaming Requirements for Immersion
• Low latency
• 15 ms for VR. [some studies state 20ms]
•1/90s frame time [~ 11 ms]
•Bandwidth
•Current: 4K Video
•Future: 8K Video and 6 DoF
Interaction Delay
5G killer Apps: AR and VR
eg. Gamelets
5G latency 10X lower than 4G
Client Bandwidth
5G killer Apps: AR and VR
5G theoritical BW 10 gigabits per second (Gbps). 100X of 4G
VR Streaming
Started as Game streaming service.
Now, VR streaming is feasible
Using the Edge
GameContentServer
Cloudlet
(UE4)
Textures
VideoStream
SSCloudyGame
PlayerInput
ThinClients
Cloudlet
(UE4)
Cloudlet
(UE4)
MinimalContentSet
4
Textures
Gamelet Gamelet Gamelet
-- Latency
Network
-- Scalability
Server bandwidth
Processing
Cloudy
game and
Super-
streamer
over 5G
edge nodes
(Gamelet)
Source: B. Anand and A. J. Hao Edwin, "Gamelets —
Multiplayer mobile games with distributed micro-clouds,”
IEEE-ICMU 2014
Optimising Gamelet for VR
Conventional VR Rendering Pipeline
@ VR Headset (Standalone VR)
Optimising Gamelet for VR
EncodingDecoding
@ Edge Nodes
@ VR Headset
VR Rendering Pipeline with Streaming
e to e latency < 20ms
Independent Hardware for
Rendering and Encoding
Source: Luyang Liu, MobiCom
Optimising Gamelet
for VR
Parallelizing
Rendering and
Streaming
Source: Luyang Liu, MobiCom
Optimising Gamelet for VR Parallelizing Rendering and
Streaming
Source: Luyang Liu, MobiCom
Optimising Gamelet for VR Parallelizing Rendering and
Streaming
Cloud AR (Global AR tags)
Using the Edge
Realtime 3D Mesh
Reconstruction and
Crowdsourcing to Build the
world mesh with AR data
(“Cloud AR”)
• A challenging process with resource limited
glasses/phones
Realtime 3D Mesh Reconstruction and
Crowdsourcing to Build the world mesh (Cloud AR)
AR – Object
Recognition/Analytics and
Tracking
Using the Edge
AR- Object
recognition
/analytics
and
tracking
Source: Luyang Liu, MobiCom
RoI Encoding, Adaptive
Offloading and Motion
vector based Tracking to
achieve <20ms
RoI based local tracking
Previously Detected
Motion Vectors
Tracking
Parallel streaming
Source: Luyang Liu, MobiCom
Cloud vs 5G-Edge: Analytics [Real-time]
Real-time Analytics can be cone in Cloud, 5G-Edge, or Client.
Realtime Video Analytics at the Edge
(Streaming & Analytics)
Options & Trade-offs:
• Cloud Only
• 5G-Edge Only
• Client Node Only
• Cloud and 5G-Edge
• 5G-Edge and Client
• Cloud, 5G-Edge and Client
THANK YOU!
Bhojan Anand
email:
Domain: comp.nus.edu.sg
Username: banand

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Multimedia Analytics with 5G Edge Nodes