Presentation at EADIM 2011 conference, November 2011

1. Podcasting De Luxe
Lecture Recording
at the
Graz University of Technology

2. History and Development I
Past
•2006 – Start of Podcasting-Service
Simple screening and audio recording with Camtasia – 50% failed 
First efforts for automated postprocessing
•2007 – Lifetime Podcasting
1st Austrian Podcast Conference in cooperation with iUNIg
•2008 – Start with (live-)Streaming-Service
Live Screening, audio and video recording on ePresence Server
Check: http://curry.tugraz.at
•2009 – Start of iTunes U platform for TU Graz
Check: http://itunes.tugraz.at/series
•2010 – Start of Project: Automated Recording
•2011 – Searchable Recordings
Stationary workflow version

3. History and Development II
Ongoing Developments and Future
•Since 2010 – Project: Automated Lecture Recordings
Focus: Workflow and usability improvement for recordings
Fully automated recording and postprocessing of lectures
•Since 2011 – Searchable Recordings
Focus: Independent workflow version
Documentation
•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 lesson
Pre- or Postrecording at office
Tutorial and instructional sequences
Short clips for help-center
•Live Streaming (Screening / Audio / Video)
For Blended learning
Casting of special events
•iTunes U
„Selected“ media-files for Public Relations

7. Didactics and Workflow II
Workflow of General Recording
•Framework
Agreement with teacher, recording details
•Preprocess
Check of hardware, software, lecture room conditions
Wireless microphone, Tablet PC
Camtasia, iShow U
•Recording
Minimal or full assistance
•Postprocess
Audio Optimization
Text to Search processing
Production of end-formats (Flash with Search, MP4)
•Publishing
on TU Graz TeachCenter (LMS)

8. Indexing Video Podcasts
A 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 Problem
OCR 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 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

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

16. Contact
TU Graz – Dept. Social Learning:
Team Podcasting
Walther Nagler
Ypatios Grigoriadis
Christian Stickel
Wolfgang Hauer
walther.nagler@tugraz.at
ypatios@gmail.com
Social Learning (TU Graz)
sociallearning
http://elearning.tugraz.at