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Mpeg 7 video signature tools for content recognition
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Mpeg 7 video signature tools for content recognition

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Transcript

  • 1. The MPEG-7 Video Signature Tools for Content Recognition
  • 2. Introduction What is MPEG-7? • "Multimedia Content Description Interface“ • ISO/IEC standard by MPEG (Moving Picture Experts Group) • Providing meta-data for multimedia • MPEG-1, -2, -4: make content available; MPEG-7: makes content accessible, retrievable, filterable, manageable (via device / computer). • Multi-degrees of interpretation of information’s meaning • Support as broad a range of applications as possible. • A compatible (with existing tech) and extensible standard.
  • 3. Why The MPEG-7 Video Signature Tools ? • Handling billions of videos. • Efficiently search for a copy of a specific piece of video content. • Duplicate video clip detection in large databases. • Finding out edited or modified version and embedded in a longer piece of video content.
  • 4. Application’s domains (incomplete) • Broadcast media selection (e.g., radio channel, TV channel). • Digital libraries (e.g., film, video, audio and radio archives). • E-Commerce (e.g., personalized advertising). • Education (e.g., repositories of multimedia courses, multimedia search for support material). • Home Entertainment (e.g., management of personal multimedia collections, including manipulation of content, e.g. karaoke). • Journalism (e.g. searching speeches of a certain politician using his name, his voice or his face). • Multimedia directory services (e.g. yellow pages, G.I.S). • Surveillance and remote sensing. • Database management and deduplication
  • 5. Requirements of the proposed technology 1) Uniqueness 2) Robustness to editing operations 3) Independence 4) Fast matching 5) Fast extraction 6) Compactness 7) Non alteration of the content 8) Self-containment of the signatures 9) Coding independence 10)Partial matching 11)Accurate temporal localization of duplicated and 12)embedded content
  • 6. Scope There are four parts to the standard in video signature: 1) The descriptor extraction and decoding, along with its descriptor definition language 2) A reference software implementation and source code for the video signature tools 3) The conditions and dataset for ensuring conformance to the standard 4) An exemplary pair wise matching and localization scheme, as used during the MPEG-7 evaluation process
  • 7. Main benefits to the different systems 1) Follows a systematic peer-reviewed evaluation process, leading to the adoption of the best technologies from various proposals 2) the video signature tools enable interoperability, i.e., they allow different users and systems to talk to each other in terms of descriptors.
  • 8. Video Signature Extraction and Compression The video signature comprises two parts: 1) Fine signatures 2) Coarse signatures 3) Video Signature Organization
  • 9. Video Signature Matching and Localization • The matching between two video signatures v1 and v2 is carried out in three stages . 1) Coarse Signature Matching 2) Temporal Parameter Estimation 3) Localization and Verification
  • 10. Hardware Specification Minimum Required Configuration: • Intel Pentium or equivalent processor • 128 MB RAM • TEN GB HDD • Keyboard (104 keys/…), Mouse(2/3 buttons) • Svga color/black & white
  • 11. Conclusion • Achieves high levels of robustness to common video editing operations • Accurately detect and localize a piece of video content embedded in a longer piece of unrelated video content
  • 12. Bibliography 1) Stavros Paschalakis, Kota Iwamoto, Paul Brasnett, Nikola Sprljan, Ryoma Oami, Toshiyuki Nomura, Akio Yamada, Miroslaw Bober, “The MPEG-7 Video Signature Tools for Content Identification”, IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, VOL. 22, NO. 7, JULY 2012. 2) A. Hampapur, K. Hyun, and R. Bolle, “Comparison of sequence matching techniques for video copy detection,” in Proc. Conf. Storage Retrieval Media Databases, 2002, pp. 194–201. 3) J. Law-To, L. Chen, A. Joly, I. Laptev, O. Buisson, V. Gouet-Brunet, N. Boujemaa, and F. Stentiford, “Video copy detection: A comparative study,” in Proc. 6th ACM Int. Conf. Image Video Retrieval, Jul. 2007, pp. 371–378. 4) H. T. Shen, X. Zhou, Z. Huang, J. Shao, and X. Zhou, “UQLIPS: A real-time near- duplicate video clip detection system,” in Proc. 33rd Int. Conf. Very Large Data Bases, Sep. 2007, pp. 1374–1377. 5) S. Paisitktiangkrai, T. Mei, J. Zhang, and X.-S. Hua, “Scalable clip-based near- duplicate video detection with ordinal measure,” in Proc. ACM Int. Conf. Image Video Retrieval, Jul. 2010, pp. 121–128. …
  • 13. THANK YOU