Embed Size (px)
Citation preview
RAI - Centro Ricerche, Innovazione Tecnologica e Sperimentazione 1
Innovation at RAI CRITSAdvanced Content Management & Coding Technologies
Alberto Messina, Roberto Iacoviello
RAI - Centro Ricerche, Innovazione Tecnologica e Sperimentazione 2
Manual Annotation System
Automated Speech Recognition for News
Automated Segmentation of news
Semantic enrichment through NLPAutomated
news aggregation
Visual Analysis & Search
Cognitive Services
Programme genre detection
1996
2001
2005
2007 2012
2014
2017
2009
2018
AI-Assisted Production
AI-based video
coding
RAI - Centro Ricerche, Innovazione Tecnologica e Sperimentazione 3
How to achieve quicker and cheaper metadata?
* at reasonable costs …
RAI - Centro Ricerche, Innovazione Tecnologica e Sperimentazione 4
RAI - Centro Ricerche, Innovazione Tecnologica e Sperimentazione 5
people
locations
organisations
RAI - Centro Ricerche, Innovazione Tecnologica e Sperimentazione 6
Microsoft
CS
Amazon
CS
CSIBM CS
Applications
REST Interface
Application Logic
Middleware
GUI Interface
Users
Annotations
RAI Media Cognitive Service Framework
Other CS
RAI - Centro Ricerche, Innovazione Tecnologica e Sperimentazione 7
RAI - Centro Ricerche, Innovazione Tecnologica e Sperimentazione 8
Audio Content Recognition
RAI - Centro Ricerche, Innovazione Tecnologica e Sperimentazione 9
Model
checker e.g.,
ML model
AI applications in media - Dataset lifecycle
DatasetGeneration
OperationVerification
Cognitive Template
+ Dictionaries ML model ,
Interactive process
RAI - Centro Ricerche, Innovazione Tecnologica e Sperimentazione 10
MULTIple DRONE platform for media
production
RAI - Centro Ricerche, Innovazione Tecnologica e Sperimentazione 11
11
• Efficient real-time target tracking
AI-assisted production
RAI - Centro Ricerche, Innovazione Tecnologica e Sperimentazione 12
Software Architecture
On Board On Ground
AI-intensive software modules
RAI - Centro Ricerche, Innovazione Tecnologica e Sperimentazione 13
Two approaches:
Neural Network Video approach
Conservative Disruptive
One to One End to End
Replace one MPEG block with one
Deep Learning block
Replace the entire chain MPEG
RAI - Centro Ricerche, Innovazione Tecnologica e Sperimentazione 14
Neural Network Video approach: Disruptive
Videos are temporally highly redundant
No deep image compression can compete with state-of-the-art video compression, which exploits this redundancy
Optical Flow
RAI - Centro Ricerche, Innovazione Tecnologica e Sperimentazione 15
Optical Flow
In the computer vision tasks, optical flow is widely used to exploit temporal relationship
Learning based optical flow methods can provide accurate motion information at pixel-level
Artificial data set
RAI - Centro Ricerche, Innovazione Tecnologica e Sperimentazione 16
DVC: An End-to-end Deep Video Compression Framework
MPEG NN
RAI - Centro Ricerche, Innovazione Tecnologica e Sperimentazione 17
End to end chain
Issues: Optical flow compression
Next: Motion compensation network?
What are we doing?
RAI - Centro Ricerche, Innovazione Tecnologica e Sperimentazione 18
RAI - Centro Ricerche, Innovazione Tecnologica e Sperimentazione 19
Dr. Alberto Messina
RAI – Radiotelevisione Italiana
Centre for Research and Technological Innovation – Turin
[email protected] vast majority of pictures included in this presentation are freely available from www.pixabay.cpm and www.pexels.com .
A remaining few have been found on the Internet and their inclusion here should be considered fair use .
RAI copyrighted material cannot be used elsewhere without explicit permission.
