Podcasting De Luxe

Lecture Recordingat the

Graz 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 Podcasts

A 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 Problem

OCR 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 Extraction

Software: 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

Contact

TU Graz – Dept. Social Learning:Team PodcastingWalther NaglerYpatios Grigoriadis Christian StickelWolfgang Hauer

walther.nagler@tugraz.atypatios@gmail.com Social Learning (TU Graz) sociallearning

http://elearning.tugraz.at