Study-Element Based Adaptation of Lecture Videos to Mobile Devices Ganesh Narayana Murthy (M.Tech IIT Bombay) Sridhar Iyer (Associate Professor, IIT Bombay)

Study-Element Based Adaptation of Lecture Videos to Mobile Devices

Ganesh Narayana Murthy (M.Tech IIT Bombay)Sridhar Iyer (Associate Professor, IIT Bombay)

Ganesh Narayana Murthy NCC 2010, Chennai, 30/01/2010 1

Problem Definition

• Adapt CDEEP videos to be viewable on mobile devices:– Viewable at low network bandwidths (like GPRS)– Viewable at low cost

• Video bit-rate – Size of video stream over time– Total size = bit-rate * total time– CDEEP video bit-rate: 1150kbps– GPRS bit-rate: 40kbps

• The problem:– Video playing incurs delays if available network bandwidth is less than

video-bit rate


Video Transcoding

• Converting from one video format to another– Changing video bit rate– Changing other parameters like frame rate, screen

resolution


Format Name Typical Bit Rate Application

MPEG-1 1.5Mbps or less CD-ROM

MPEG-2 5-8Mbps DVD, HDTV

H.263 Typically low bit rates Low bit-rate video conferencing

MPEG-4 / H.264 40Kbps to 10Mbps and above

Internet Streaming, Video Telephony

Flash Video (FLV) Typically low bit rates Embedded video in websites

Video Quality at low-bit rates


(a) MPEG-1 (b) MPEG-2

Images from transcoded videos (Target bit rate : 40kbps, No audio)

Video Quality at low bit-rates (contd.)


(c) H.264 (mp4) (d) H.263 (3gpp)



(e) Flash Video (flv)


Comparison of Video CodecsFormat Name

Original VideoSize

Converted VideoSize

Video Quality at low-bit rates

Remarks

MPEG-1 432MB 26MB Poor Cannot be used at low bit-rates

MPEG-2 432MB 29.12MB Poor Cannot be used at low bit rates

H.263 432MB 38.3MB Poor Cannot be used at low bit rates

H.264 432MB 16.9MB Good Processing power / Decoding complexity is high.[1]

Flash 432MB 20.5MB Good Can be used, but cost is still high.


(Note: Video bit rate = 1150kbps, No audio, Target bit rate = 40kbps, No audio)

Video Sizes are still high forviewing over GPRS

Study-Element Based Adaptation


Motivation

• CDEEP video usually consists of– Presentation slides– Instructor explaining on white paper– Video of instructor talking

• Presentation slide is usually not changing– Video of slide is not required. One image is sufficient

• Idea– Extract one image every ‘n’ seconds and send to client.– This would reduce amount of data sent for showing one

slide.


Method-1

• Send one image every ‘n’ seconds– Server sends one image every ‘n’ seconds to client– Audio is simultaneously streamed

• Network bandwidth and Size – Network Overhead (NO) = Image Size / n– Size Overhead (SO) = Total size of images

• What is the user experience?


User Experience Basis

• Presentation Study Element– Portion of video showing one slide

• White Paper Study Element– Portion of video showing instructor writing on

white paper

• Instructor Study Element– Portion of video showing instructor talking


…………..

0 5 10 15

Presentation Slide

Delay in start of slide

3

………..

25 30 35

White Paper

Video Time(secs)

User Experience• Presentation Element

– Delay Experienced (D2) = • Delay in start of slide as compared to audio

• White Paper Element– Delay Experienced (D1) =

• Delay between any two consecutive images = Sending Rate

• Instructor Element– Only audio important. No image need be sent.

• User Experience is assumed to be one

• User Experience (Ui) = 1 sec / Di


Method-2• Trade-off for user experience

• Cost incurred in terms of number of images sent

• Same sending interval for all elements, cannot balance user experience and cost.

• Choose different sending interval for each study element

• Probably:– Higher user experience for white paper

element– Lower user experience for presentation

element


User Experience

Cost

Sending Interval

Trade-Off Relation

System Overview


Building the index

• Corpus of 10 videos– Representative of various departments

• Consider different sending intervals ‘r’– For each ‘r’ find NO,SO and U for every study element in a

video. – Repeat for all videos and take average.

• This relation can be used backwards:– For calculating sending interval, given network bandwidth

and user experience.


Graphs of User Experience


Graphs of overheads


Results

Original Video Size(MB)

Images Size (MB)

Reduction (%)

U1 U2 SupportedNetwork Bandwidth

432 2.85 97% 0.2 0.38 20kbps and above


Achieved Size Reduction

Fig: Video stream size reduction (note: Original video bit-rate = 1150kbps, No audio)

Results (contd.)

Sending Interval U1 U2 NO1(kbps)

S01(MB)

NO2(kbps)

SO2(MB)

Total Size (SO)

White Paper Element

Presentation Element

5 5 0.2 0.337 15.12 1.25 23.43 1.6 5.46

5 15 0.2 0.115 15.12 1.25 7.81 0.53 1.78

15 15 0.067 0.115 5.254 0.781 7.63 1.03 1.81


Balance User Experience and Cost

Required Network Bandwidth =max(NO1,NO2) is reduced

Reduction in size user experience for white paper element remaining same

Conclusion

• Large size reduction can be achieved by using the concept of slideshows

• Identifiying study-elements within the video helps define user-experience of the slideshow.

• CDEEP Lecture videos can be adapted to low network bandwidths and in a cost-controlled manner.


Future Work

Automated tagging– Identifying study element boundaries – Shot detection techniques

User Experience Correlation– Identifying relation between obtained user

experience and actual user values


References1. H.264 white paper.

http://ati.amd.com/products/pdf/h264_whitepaper.pdf.2. Real-time Content-Based Adaptive Streaming of Sports Videos.

Shih-Fu Chang, Di Zhong, and Raj Kumar. In CBAIVL '01: Proceedings of the IEEE Workshop on Content-based Access of Image and Video Libraries (CBAIVL'01), page 139, Washington, DC, USA, 2001. IEEE Computer Society.

3. Content-aware video adaptation under low-bitrate constraint. Ming-Ho Hsiao, Yi-Wen Chen, Hua-Tsung Chen, Kuan-Hung Chou, and Suh-Yin Lee. EURASIP J. Adv. Signal Process,2007(2):27-27, 2007.

4. A Characteristics-Based Bandwidth Reduction Technique for Pre-recorded Videos. Wallapak Tavanapong and Srikanth Krishnamohan. In IEEE International Conference on Multimedia and Expo (III), pages 1751-1754, 2000.


Questions?


Content-Aware Adaptation


Method Name Adaption Mechanism Video Quality Remarks

Hsiao et.al.[2] Identify visual attention regions in a frame. Encode them at high quality.

Poor Quality of important objects still depends on network bandwidth

Chang.et.al [3] Identify events in sports videos at high quality. Other regions as slideshows.

Good Slideshow of images reduces network bandwidth and size

Tavanapong. et. Al. [4]

Identify non-changing portions of lecture video and extract one image from them

Good Exploits redundancy in lecture videos

Study-Element Based Adaptation of Lecture Videos to Mobile Devices Ganesh Narayana Murthy (M.Tech IIT Bombay) Sridhar Iyer (Associate Professor, IIT Bombay)

Documents

rate video conferencingmpeg

video format

ratesembedded video

anotherchanging video

motivationcdeep video

video transcodingconverting

rate size of video stream

ratesganesh narayana