More Pixels and Samples: High Resolution Media Streaming

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Transcript More Pixels and Samples: High Resolution Media Streaming

More Pixels and Samples:
High Resolution Media Streaming
Roger Zimmermann
Data Management Research Laboratory
University of Southern California
Los Angeles, CA 90089
http://dmrl.usc.edu
Outline
• Motivation
• Background
– Remote Media Immersion
– Distributed Immersive Performance
• High-performance Data Recording
Architecture
• Demonstration
• Conclusions
APAN, January 2004
Integrated Media Systems Center, USC
Motivation
• The charter of the Integrated Media
Systems Center (IMSC) is
“Immersipresence”
– Immerse real (e.g. people) and virtual
elements into a common space
• Becomes much more interesting in a
distributed environment
– Many sub-problems: tracking, gesture
recognition, data management, …
– Video and audio are an important
component
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What is the problem?
• Live streaming is either
– Low to medium quality, or
– Very expensive, i.e., there are only a few
people to call …
• Other obstacles
– Complicated (not like the telephone)
– Often requires room engineering
– Network bandwidth is not available
• Some of the technical constraints can
and will be solved
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Ex.: Network Infrastructure
• UTOPIA (Utah Telecommunications Open
Infrastructure Agency): public works
project to provide fiber to the home
(FTTH).
• SuperNet, Alberta, Canada. Public
project to provide a high speed Internet
infrastructure.
• NSF sponsored workshop, Oct. 23-24,
2003, Chicago, Illinois. The importance of
“broaderband” networks is recognized.
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Research Timeline
2002
Jun 2-3
Unveiling of RMI Demonstration
Oct 29
Internet2 Meeting: RMI Demonstration
Dec 28
DIP Experiment 1: Distributed Duet
2003
Jan 18
Recording from Stream
Jan 19
DIP Experiment 2: Remote Master Class
Jun 2-3
DIP Experiment 3: Duet with Audience
2004
Jan 29
APAN Meeting: HYDRA Experiment
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Integrated Media Systems Center, USC
What is the RMI?
“The goal of the Remote Media Immersion
system is to build a testbed for the creation of
immersive applications.”
Immersive application aspects:
1. Multi-model environment (aural, visual, haptic, …)
2. Shared space with virtual and real elements
3. High fidelity
4. Geographically distributed
5. Interactive
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Integrated Media Systems Center, USC
RMI Challenges

Immersive, high-quality video
acquisition and rendering
 High Definition video 1080i and
720p (40 Mb/s)

Immersive, high-quality audio
acquisition and rendering
 10.2 channels of uncompressed
audio (12 Mb/s)

Storage and transmission of media
streams across networks

Synchronization between streams
(A/V, A/A, V/V)!
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RMI Architecture
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RMI Experimental Setup
• Synchronized immersive audio and HDTV streamed playback
from Yima server over Internet2
– 16 channels of immersive audio, uncompressed at 16 Mb/s
– 1920x1080i HDTV content, MPEG-2 compressed at 40 Mb/s
• Control of end-to-end process: capturing, network interface,
transmission, rendering
ISI East
IMSC
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Internet2 Fall ‘02
Member Meeting
Video: HDTV 1280x720p
Audio: 10.2 channel,
immersive sound
system
New World Symphony, Miami, FL
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Integrated Media Systems Center, USC
Distributed Immersive Performance
• Outgrowth of Remote Media Immersion (RMI)
– Create seamless immersive environment for
distributed musicians, conductor (active) and
audience (passive)
– Compelling relevance for any human interaction
scenario: education, journalism, communications
• Scenario:
– Orchestra not available in town
– Famous soloist cannot fit travel into schedule
– Multiple soloists in different places
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60 ms
20 ms
30 ms
40 ms
10 ms
30 ms
Challenge: network latency
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• Key observations:
– Network latency maps to audio delay on stage
– Video delay is zero
• Challenge:
– Synchronization
– Transmitting low latency video of conductor to players
and audience
– Maintaining constant delay between players
Player 1
15m: 45ms
15m: 45ms
Conductor
Player 2
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10m: 30ms
Integrated Media Systems Center, USC
Barriers and Requirements
1. Real-time continuous media (CM) stream
transmission (network protocol) with low latency
2. Precise timing: GPS clock, synchronization
3. Data loss management: error concealment, FEC,
retransmission, multi-path streaming
4. Many-to-many transmission capability
5. Low latency, high-quality real-time video and
audio acquisition and rendering
6. Real-time CM stream recording
7. User experiments, requirements, specifications,
performance evaluation
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Distributed Immersive Performance
v.1.0-The Duet
• Experiments and Objectives
– Experimental testbed and demonstration system
– Demonstrate and document a distributed musical performance
with two musicians (a duet)
– Two-way interactive video and 10.2 channel immersive audio
capability
– Explore other applications involving passive and active participants,
such as two-site interactive meetings
– Evaluate technical barriers and psychophysical effects of latency
and fidelity on music and other forms of human interaction
between two interconnected sites
• Dennis Thurmond - USC Thornton School of Music
• Elaine Chew - USC Industrial and Systems Engineering
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Distributed Immersive Performance
v.1.0-The Duet
Linux PC
Linux PC
DV FireWire
Camera
DV FireWire
Camera
100BaseT
campus net
100BaseT
IMSC net
350 meters
Ramo Hall of Music (RHM 106)
Powell Hall (PHE 106)
• Video: NTSC resolution, 31 Mb/s DV, software decode, one-way
latency: 110 ms due to DV camera compression + < 5 ms network
• Audio: uncompressed, 16 or more channels at 1 Mb/s each, one-way
latency: < 10 ms due to audio processing + < 5 ms network
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Distributed Immersive
Performance v.1.0-The Duet
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HYDRA Streaming Architecture
• Most previous work in streaming media has focused on the
retrieval and playback functionality.
• More and more devices directly output digital media
streams:
– E.g., camcorders (FireWire, USB, SDI),
microphones (Bluetooth), mobile handsets (3G)
• Need for a backend data stream recording /
playback system (“Super TiVo”)
 HYDRA (High-performance Data Recording Architecture)
[ICEIS 2003]
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Challenges
• Variable bit rate media streams
• Multi-zoned disks
• Different read and write
transfer rates
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Live Streaming
• Latency is a crucial limiting factor:
– Only ~ 20-40 ms is unnoticeable (for
universal interactive applications)
• Tradeoff: Latency versus bandwidth
– Compression reduces bandwidth
– But: high compression increases latency
(e.g., interframe MPEG compression)
• Approach:
– Perform experiments within this design space
e.g. DV: NTSC resolution, 31Mb/s, SW/HW codecs
e.g. uncompressed audio and video
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Architecture
HYDRA HD Live Streaming
JVC HD10U
FireWire
MPEG TS
Extractor
HD-SDI
RTP/
UDP/IP
VGA Display
MPEG-2
Decoder
• Acquisition and rendering PC are both Linux
based (RH 9 includes kernel support for FireWire).
• MPEG transport stream extraction.
• Data transport via UDP packets with single
retransmissions
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Rendering
• Solution 1: Software based rendering
• Use X11 hw acceleration: XvMC (libmpeg2)
– Motion compensation and iDCT with GPU
• Our hw: NVIDIA FX 5200 ($100)
• Performance: ~ 90 fps @ 1280x720 with 3 GHz P4
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Rendering
• Issues with software rendering
– Precise timing: 29.97 fps
– Decoding time for I, P, and B frames varies
– Buffering of decoded frames necessary to
achieve precise timing
– Transport stream splitter and audio decoding
– Video card refresh rate (timing) is
independent of MPEG timing, but
• Non-standard display modes are possible:
720p on Linux (16x9)
– Decoding latency
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Rendering
• Solution 2: Hardware based rendering
• E.g.: CineCast HD board from Vela Research
– Digital HD-SDI and analog RGB/YPrPb outputs
• Great and stable picture (but $$$)
• Genlock input for synchronization
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Rendering
• Issues with hardware rendering
– Linux drivers hard to come by
– CineCast HD board uses SCSI interface
• Wrote our own SCSI extensions to the Linux
SCSI Generic driver (/dev/sg0)
– Decoding latency: requires 8 x 64 kB to start
decoding
– Consumer HD card:
Telemann HiPix ($400)
But: No Linux drivers
(no Windows filters?)
– New Vela card:
CineCast HD LE
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Live HD Video Streaming
(1280x720p)
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Distributed Immersive Performance
v.2.0-Extended Architecture
• Conflicting requirements: Low latency and low
bandwidth (i.e., use of compression)
• Solution - two-tier architecture:
• Between performers
– Low latency stereo audio streaming
– Low latency video streaming
• Between performers and audience
– High definition video streaming
– Multichannel audio streaming (10.2 channel)
• Recording of all streams sychronously for archival
purposes and later playback.
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Multichannel audio
Stereo audio
Low latency, low resolution video
High latency, high resolution video
Performer 1
Performer 2
Playback and
Recording
Audience
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Integrated Media Systems Center, USC
Thank You! Questions?
• More info at:
– Data Management Research Lab
• http://dmrl.usc.edu
– Integrated Media Systems Center
• http://imsc.usc.edu
• Acknowledgments:
– Kun Fu, Beomjoo Seo, Shihua Liu, Dwipal A.
Desai, Didi Shu-Yuen Yao, Mehrdad Jahangiri,
Farnoush Banaei-Kashani, Rishi Sinha, Hong
Zhu, Nitin Nahata, Sahitya Gupta, Vasan N.
Sundar,
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