1. An Experiment To Characterize Videos On The Web Soam Acharya Brian Smith Cornell University MMCN 1998

2. Overview Designed and implemented an experiment to search and analyze videos on the web 22500 HTML documents 57000 movies 100 Gbytes of data www

3. Why? Codec Designers Network Engineers Other Multimedia Researchers MM file systems Webmasters

4. How many movies are out there? What are their basic properties? What compression formats are popular? How well do the formats compare? Are standard modem rates enough? Questions We Asked Not all that many. We found 57,000. 90% last 45 seconds or less. 1.1 Mbytes is their median size QuickTime is about 53%, followed by MPEG (30%) and AVI MPEG compresses best. QuickTime and AVI are similar. 28.8 - 128 Kilobits/sec (Kbps) are useless for real-time download and display of movies.

5. Roadmap Data Collection Methodology Analysis Results Conclusion Future Work Open Questions

6. Data Collection Methodology Hunting Phase –get links to movies Gathering Phase –download movies and gather raw statistics Sifting Phase –eliminate outliers

7. Early April 1997 -Hunting Phase Milked AltaVista for documents dated –January 1995 - March 1997 looked for MPEG, QuickTime, AVI no streaming video format

8. Gathering Phase mid April 1997 - May 1997 LP1 1. http://www.eg.com/movie.html LDG: movie link distributor/gatherer LP: link processor www.eg.com 2. movie.html www.vid.com 3. my.mov 4. summary statistics LP0 LP2 LDG Http://www.eg.com/movie.html http://www.cnn.com/pepe.html …..

9. Sifting Phase Processed 100 Gbytes of data and 57,000 titles –used mpegstat and modified xanim 4 < frames/sec < 40{5000 titles} duration > 0.5 seconds{1000 titles} 0.6 < aspect ratio < 1.667{1000 titles} bitrate < 10 Mbps{1000 titles} –bitrate = (movie size)/(movie duration) duplicate URL detection{1500 titles}

10. Analysis 47500 titles remained –53% QuickTime, 30% MPEG, 17% AVI Can be divided into two categories –Distributions: by date fps size duration aspect ratio bitrate –Comparing movie formats against each other

11. Roadmap Data Collection Methodology Analysis Results Conclusion Future Work Open Questions

15. Movie Size (In bytes) 70% of movies are 2Mbytes or less Median movie size is about 1.1 MBytes

16. 90% of the movies are 45 sec or less, 50% < 15 sec

17. Aspect Ratio 74% of all files had an aspect ratio of 1.333 –320 x 240 –160 x 120 89% had aspect ratios of 1.2 - 1.5

18. Movie Bitrate = movie size / movie duration

19. So Far... Distributions: –by date –fps –size –duration –aspect ratio –bitrate Comparing movie formats

20. AVI/QuickTime Comparison Video CodecsAVIQuickTime Radius Cinepak43% 60% Intel Indeo R3.225% 2% Microsoft Video I26% 0% Apple Video-RPZA 0% 22% 25% of AVI, 33% of QuickTime: video only AVIQuickTime Audio CodecPCM PCM MS-ADPCM TWOS

21. How Compare Compression? Bits/pixel = (video size in bits)__ (width * height * # of frames) MeanMedian (bits/pixel) AVI 2.51 2.14 QT 2.16 1.82 MPEG 0.72 0.51

22. MPEG Bits/pixel Distribution Size of I:P:B frames ~ 1: 2 : 5 90% of MPEG files were video only Frame TypeMean bits/pixel Median bits/pixel I1.251.10 P0.760.54 B0.310.19

23. MPEG Frame Patterns Frame Pattern% DistributionMean bits/pixel I27.1 1.17 IBBPBB15.7 0.7 IBBPBBPBBPBBPBB10.4 0.31 IBBPBBPBBPBB 8.1 0.5 IBBBPBBBPBBB 4.4 0.66 IPBBIBB 4.2 0.39 IIP 3.5 0.7 80% of MPEG: some recurring pattern

24. Recap Number of movies coming online - exponential, then flat MPEG higher fps, QuickTime/AVI lower Median size of movies: 1.1 Mbytes 90% of movies last 45 seconds or less 1.333 is the most common aspect ratio 28.8 - 128 Kbps modem rates useless for real-time downloads Radius Cinepak is widely used by QuickTime and AVI MPEG compresses better than QuickTime and AVI 80% of MPEGs have some sort of recurring pattern

25. Conclusion Existing compression technologies not enough for transmission over standard modems –explains rise of streaming video technologies –users cope by making file sizes, duration smaller –but not by throttling the bitrate –perceptual threshold?

26. Future Work How do videos age? Another study to confirm findings –Brewster Kahle, –www.archive.org Develop tools to automate the process

27. Open Questions What are video access patterns on the Web? How to analyze streaming video files?