Your SlideShare is downloading. ×
0
Podcasting De Luxe
Podcasting De Luxe
Podcasting De Luxe
Podcasting De Luxe
Podcasting De Luxe
Podcasting De Luxe
Podcasting De Luxe
Podcasting De Luxe
Podcasting De Luxe
Podcasting De Luxe
Podcasting De Luxe
Podcasting De Luxe
Podcasting De Luxe
Podcasting De Luxe
Podcasting De Luxe
Podcasting De Luxe
Upcoming SlideShare
Loading in...5
×

Thanks for flagging this SlideShare!

Oops! An error has occurred.

×
Saving this for later? Get the SlideShare app to save on your phone or tablet. Read anywhere, anytime – even offline.
Text the download link to your phone
Standard text messaging rates apply

Podcasting De Luxe

907

Published on

Presentation at EADIM 2011 conference, November 2011

Presentation at EADIM 2011 conference, November 2011

0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total Views
907
On Slideshare
0
From Embeds
0
Number of Embeds
2
Actions
Shares
0
Downloads
2
Comments
0
Likes
0
Embeds 0
No embeds

Report content
Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
No notes for slide

Transcript

  • 1. Podcasting De Luxe Lecture Recording at theGraz University of Technology
  • 2. History and Development I Past•2006 – Start of Podcasting-ServiceSimple screening and audio recording with Camtasia – 50% failed First efforts for automated postprocessing•2007 – Lifetime Podcasting1st Austrian Podcast Conference in cooperation with iUNIg•2008 – Start with (live-)Streaming-ServiceLive Screening, audio and video recording on ePresence ServerCheck: http://curry.tugraz.at•2009 – Start of iTunes U platform for TU GrazCheck: http://itunes.tugraz.at/series•2010 – Start of Project: Automated Recording•2011 – Searchable RecordingsStationary workflow version
  • 3. History and Development II Ongoing Developments and Future•Since 2010 – Project: Automated Lecture RecordingsFocus: Workflow and usability improvement for recordingsFully automated recording and postprocessing of lectures•Since 2011 – Searchable RecordingsFocus: Independent workflow versionDocumentation•Since 2011 – Project: Automated Audio-Postprocessing:Cooperation with team from auphonic(http://auphonic.com/)
  • 4. Facts of Podcasting Service I
  • 5. Facts of Podcasting Service II
  • 6. Didactics and Workflow I Didactics and Purposes•General Recordings (Screening / Audio / Video)Full Recording of lessonPre- or Postrecording at officeTutorial and instructional sequencesShort clips for help-center•Live Streaming (Screening / Audio / Video)For Blended learningCasting of special events•iTunes U„Selected“ media-files for Public Relations
  • 7. Didactics and Workflow II Workflow of General Recording•FrameworkAgreement with teacher, recording details•PreprocessCheck of hardware, software, lecture room conditionsWireless microphone, Tablet PCCamtasia, iShow U•RecordingMinimal or full assistance•PostprocessAudio OptimizationText to Search processingProduction of end-formats (Flash with Search, MP4)•Publishingon TU Graz TeachCenter (LMS)
  • 8. Indexing Video PodcastsA method for making long presentation videos searchable
  • 9. Overview● Target: make long video presentation searchable● Idea: generate index from extracted text● Key Technology: OCR (Optical Character Recognition)● Input: screen-capture video of presentation● Output: encoded video embedded in a flash player with a ToC (Table of Contents) and a word search field [example]
  • 10. Main ProblemOCR software is not compatible with video files Solution: frame extraction
  • 11. Frame Extraction● What software to use?● Which frames to extract?● Are all extracted frames useful?
  • 12. Frame ExtractionSoftware: FFmpeg http://ffmpeg.org/● Frame selection: FFmpeg (-vstats option) ● Locate “I” frames ● Extract timestamp● Further frame sorting: Perl http://www.perl.org/ ● Size ● Position
  • 13. AVC (Advanced Video Codec) GOP (Group Of Pictures)
  • 14. OCR procedure● Extracted frames are sent to OCR software for analysis● OCR software returns one text file for each frame ● Name of text file contains timing info● Information from the test files is collected and used for ToC generation
  • 15. ContactTU Graz – Dept. Social Learning:Team PodcastingWalther NaglerYpatios GrigoriadisChristian StickelWolfgang Hauerwalther.nagler@tugraz.atypatios@gmail.com Social Learning (TU Graz) sociallearninghttp://elearning.tugraz.at

×