VideoHypE: An Editor Tool for Supervised Automatic Video Hyperlinking
1. Television Linked To The Web
VideoHypE: An Editor Tool for Supervised
Automatic Video Hyperlinking
Lotte Belice Baltussen, Roeland Ordelman, Jaap Blom
Netherlands Institute for Sound and Vision
EuroITV | Como, Italy – 24 June 2013
www.linkedtv.eu
2. The LinkedTV vision
www.linkedtv.eu
LinkedTV: interweaving Web and TV into a
single experience
Mixing lean back and lean forward
2
Want to maintain immersion while removing fourth
wall illusion
Works only for certain genres and audiences
Does second screen help or hinder?
linkedtv.eu
3. Scenarios and content
www.linkedtv.eu
Enriched News
Antiques Interactive
Professional news content
produced by RBB for general
audience
local news show rbb Aktuell
People, locations and events
can be linked to previous
events.
Program watched
predominantly by 50+ers
AVRO:
3
linkedtv.eu
Tussen Kunst en Kitsch (TKK)
Objects, locations and
experts provide anchors to
related materials (targets).
5. Workflow
www.linkedtv.eu
Hypervideo
analysis
Paintings by Jan Sluijters
Generation of
media fragments
Named Entity
Recognition
Enriching NEs with
web content
“...painting of Jan Sluijters....”
dbpedia.org/resource/Jan_Sluyters
5
linkedtv.eu
Presentation
engine
6. Workflow
www.linkedtv.eu
Hypervideo
analysis
Paintings by Jan Sluijters
Generation of
media fragments
Named Entity
Recognition
Enriching NEs with
web content
VideoHypE
“...painting of Jan Sluijters....”
dbpedia.org/resource/Jan_Sluyters
6
linkedtv.eu
Presentation
engine
7. Why do we need VideoHypE?
www.linkedtv.eu
Broadcasters want to have some control.
Editors have the expertise to determine relevance +
The user interface can only show a limited amount of links, and there are many
Research: sample 805 videos, average 55 NEs per video. 55 NEs = many, many
possible links depending on the size of the white list [Li et al., 2013]
ist 1
hite l
w
Link
NE - person: Jan Sluijters
, Roeland Ordelman1
NE – art syle: Fauvism
NE - person: Emiel Aardewerk
Link white
list 2
Link white lis
Link white list 4
Link white list 5
hite l
in k w
L
ist 6
list 7
Link white
Link white lis
7
t3
t etc etc
8. VideoHypE requirements
www.linkedtv.eu
Requirements session with 5 AVRO editorial members +
digital staff of TKK. Main outcomes:
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2.
3.
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8.
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Separate user environment for each end user partner
Selecting from list of available episodes
Create and edit chapters
Timeline with chapters
See annotations per chapters, distinction between entity types
Select annotations + related hyperlinks
, Roeland Ordelman1
Add selected, approved hyperlinks
Remove hyperlinks and/or entities (per media fragment or episode)
Timeline with enities and hyperlinks
Add new hyperlinks to media fragments (e.g. shots/chapters/spatial)
Adding to white list
Sorting on entity types => not yet
Collaborative space => not yet
Delete annotations forever => not yet
Level of completion per chapter / episode => not yet
Variable # suggested links depending on time pressure
MAX 20-30 minutes per episode!!!
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9. Demo overview – choose your video
www.linkedtv.eu
, Roeland Ordelman1
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16. VideoHypE – discussion & future work
www.linkedtv.eu
1.
2.
Implementing remaining requirements.
How to make the editor tool scalable?
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Different programmes, different requirements
How to deal with live content?
There is not just one front-end => one-screen solutions, 2nd screens, multiple
screens, etc.
Personalisation: what ‘bandwith’ is left personalisation?
Relevance is a crucial issue – how can the system ‘learn’?
User testing with real editors
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17. Thanks!
www.linkedtv.eu
Find me here:
@lottebelice | lbbaltussen@beeldengeluid.nl
Credits:
Again: other authors are Roeland Ordelman and Jaap Blom
Slides partly by: Lynda Hardman (CWI)
Heaps of thanks to AVRO for so generously letting LinkedTV use their content.
, Roeland Ordelman1
Links:
www.linkedtv.eu
twitter.com/BenGlabs
www.avro.nl
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Editor's Notes
(1) Big Q: Do you ever have a question about what you are watching?
Would you like related information about something you have seen?
Something someone mentioned?
One option is to pause the TV, go find your smart phone or pad and start some google search.
When you carry out the search, your device doesn't know what you were watching, nor what the specific scene was about.
Wouldn't it be nice to have a system that knows what you are watching, knows what you like and that presents links to extra pieces of information to you?
Technology only likely to be useful when audience, content and program genre match.
(2) slide
(1) Currently developing tools using 2 program genres
(1) What do we think it will look like? Not like this!
Select video. Link to video!
http://www.linkedtv.eu/scenarios/hyperlinked-documentary-scenario/
Developing individual technologies, using content from 2 program genres, with the aim of creating an end2end prototype.
1. Given a video:
segment it to shots
detect visual concepts
detect faces
perform audio analysis (ASR)
perform keyword extraction
2. Media fragments => time-related!
3. ANCHORS Named Entities => e.g. Jan Sluyters, disambiguated wtih DBpedia link
4. TARGETS web content from WHITE LIST connected to the ANCHORS