1. Jeong, Dongseok

2. There are two techniques used for Video Fingerprinting : CPF(Color Patches Features) and Gradient Histograms. What is the main idea of these techniques? What methods are used for similar image searching?

3. Detecting recurring video clips in a TV broadcast stream In this case, to detect recurring commercials in a TV broadcast stream How can we overcome the storage and computing issue of video data?

4. Introduction Fingerprinting Video Streams ☜  CPF, Gradient Histograms Explain own search algorithm ☜ Experimental results Related Work Conclusion

6. CPF example

7. Gradient Histograms Edge-based features

8. Gradient Histograms cont.

10. Finding similar images to the source video  Use inverted index and Locality Sensitive Hashing Compare short clips from each source Finding the start-point and end-point of repeated sequences Classifying the repeated video

11. Clip Length : choose 25 frames

12. Minimum Fraction of Matched Frames  choose 20%

13. Maximum Number of Entries in Hash Table  choose 100 entries per hash value

14. Minimum Length of Duplicates  Choose 100 frames

15. Searching for flips with GHs is up to 30% faster than using CPFs But CPFs are faster to evaluate and need a smaller amount of storage (a) : Chart TV (b) : Sky Sports News

16. Apply the system to a variety of broadcast stations

17. The remaining false detections are mainly caused by repeated news stories(in ARD : the German public broadcaster) Gemini is an Indian TV channel – for non- natives what are commercials and what not?

18. There are two techniques used for Video Fingerprinting : CPF(Color Patches Features) and Gradient Histograms. What is the main idea of these techniques? What methods are used for similar image searching?

19. Any Question?