Jeong, Dongseok. There are two techniques used for Video Fingerprinting : CPF(Color Patches Features) and Gradient Histograms. What is the main idea of.

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Presentation transcript:

Jeong, Dongseok

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?

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?

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

CPF example

Gradient Histograms Edge-based features

Gradient Histograms cont.

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

Clip Length : choose 25 frames

Minimum Fraction of Matched Frames  choose 20%

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

Minimum Length of Duplicates  Choose 100 frames

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

Apply the system to a variety of broadcast stations

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?

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?

Any Question?