Taming your media chaos
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  • 1. taming your media chaos
    iMinds13th Oct 2011
    KarelBraeckman
    VRT-medialab
  • 2. try finding the video about an earthquake
  • 3.
  • 4.
  • 5. A computer sees bits
    earthquake
    ?
    10011001010010110101010101010110101101010101010101111001
    10011001010010110101010101010110101101010101010101111001
    10011001010010110101010101010110101101010101010101111001
  • 6. Textual metadata is needed to help the system find the correct videos
    earthquake
    HAITI
    VICTIMS
    EARTHQUAKE
  • 7. how to obtain metadata?
  • 8. high quality
    but
    takes time
  • 9. 9
    CHAMP
    SCAIE
    MEDIAMAP
    PISA
    MEDIALOEP
  • 10. manual
    be smart
    crowd sourcing
    repurpose
    extraction tools
    linked data
  • 11. manual
    be smart
    crowd sourcing
    repurpose
    extraction tools
    linked data
  • 12. manual
    be smart
    crowd sourcing
    repurpose
    extraction tools
    linked data
  • 13. save & structure information
    while creating
    “cradle to the grave”
  • 14. @ Champ
  • 15. @ Champ
  • 16. @ MediaMap
  • 17. @ PISA “Scoop”
  • 18. http://www.youtube.com/watch?v=cc_xQN7iyZo
  • 19. = future
    but requires change of tools
    what about productions not made with those tools?
  • 20. manual
    be smart
    crowd sourcing
    repurpose
    extraction tools
    linked data
  • 21. repurpose information from existing systems for search & navigation
  • 22. @ PISA “Trouvaille”
  • 23. @ MediaLoep
    manual annotations
    subtitles
    playout schedulepress photosnews preparation
    news cmsnews agenciesscripts
  • 24. http://www.youtube.com/watch?v=CIaLnLKuXu8
  • 25.
  • 26. lots of metadata
    but
    not applicable to all material
  • 27. manual
    be smart
    crowd sourcing
    repurpose
    extraction tools
    linked data
  • 28. while interacting with your content
    people create metadata
  • 29. @ DeKoers
  • 30. @ DeKoers
    #gilbert
    #boonen
    #sprint
    #muur
  • 31. manual
    be smart
    crowd sourcing
    extraction tools
    repurpose
    linked data
  • 32. face = “GoedeleDevroy”
    “Live”,”Brussel”,“GoedeleDevroy”
    Speech Jingle
    “Iksta in Brusseltewachtenmaar…”
  • 33. @ PISA
    Detect shot / scene / audio changes
  • 34. @ PISA
    Detect and recognize faces
  • 35. @ PISA
    Detect reuse
  • 36.
  • 37. @ PISA
    promising
    low-level metadata
    academic
  • 38. @ EBU SCAIE
    list & evaluate
    feature extraction tools
    academic -> real-life
  • 39. manual
    be smart
    crowd sourcing
    extraction tools
    repurpose
    linked data
  • 40. manual
    be smart
    crowd sourcing
    repurpose
    extraction tools
    linked data
    Enhancing existing metadata
    using Linked Open Data
  • 41. Plotting a location on a map requires the latitude / longitude
    HAITI
  • 42. Showing a photograph or summarizing a set of search results
    BAN KI-MOON
  • 43. Open online knowledge basescontain an abundance of knowledge
    HAITI HAS COORDINATES 19°N 72°W
    THIS IS A PICTURERELATED TO EARTHQUAKE
    Geo-names
    FlickrWrappr
    DBpedia
    W3CWordNet
    HAITI IS A COUNTRY
    9 MILLION PEOPLE LIVE IN HAITI
    EARTHQAKE IS A GEOLOGICAL PHENOMENON
  • 44. Link to information from DBpedia & GeoNames
    KEYWORDS
    HAITI
    country
    HAITI
    HAITI
    type
    population
    8 924 000
    sameAs
    latitude, longitude
    19° N 72° W
    GeoNames
  • 45. @ MediaLoep
  • 46. VISIT OUR BOOTH
    FOR A DEMO!
  • 47. from PoC to product @
    VISIT OUR BOOTH
    FOR A DEMO!
    ALSO VISITTHIS BOOTH!
  • 48. manual
    be smart
    crowd sourcing
    repurpose
    extraction tools
    linked data
    Obtain & structure metadata: many methods, none is perfect
  • 49.
  • 50. thank you