Podcasting De Luxe

Podcasting De Luxe Lecture Recording at theGraz University of Technology

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

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/)

Facts of Podcasting Service I

Facts of Podcasting Service II

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

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)

Indexing Video PodcastsA method for making long presentation videos searchable

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]

Main ProblemOCR software is not compatible with video files Solution: frame extraction

Frame Extraction● What software to use?● Which frames to extract?● Are all extracted frames useful?

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

AVC (Advanced Video Codec) GOP (Group Of Pictures)

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

ContactTU Graz – Dept. Social Learning:Team PodcastingWalther NaglerYpatios GrigoriadisChristian StickelWolfgang Hauerwalther.nagler@tugraz.atypatios@gmail.com Social Learning (TU Graz) sociallearninghttp://elearning.tugraz.at

Podcasting De Luxe

by Martin Ebner on Nov 11, 2011

Accessibility

Categories

Tags

Upload Details

Usage Rights

2 Embeds 123

Statistics

Podcasting De Luxe — Presentation Transcript

http://elearningblog.tugraz.at	119
http://wbt24.de	4