The week's pick
Random Articles
Reseach Article
Content Identification using Video Fingerprint based on Video Classification
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 109 - Number 1 |
| Year of Publication: 2015 |
| Authors: Kulbhushan Abasaheb Choure, Anilkumar N. Holambe |
10.5120/19156-0598
|
Kulbhushan Abasaheb Choure, Anilkumar N. Holambe . Content Identification using Video Fingerprint based on Video Classification. International Journal of Computer Applications. 109, 1 ( January 2015), 45-50. DOI=10.5120/19156-0598
Abstract
Internet usage has drastically increased in recent years. Based on the topic a tool for video content identification and video classification is presented. Tool uses MPEG-7 standard. Thus video streams are easily available in various forms. One must appreciate text-based search engines for immediate access to such a vast multimedia data on web. But currently, only text-based search engines are obtainable. So a tool that will search for a unique content in the video not in the name of the video is proposed. Tool will make use of video fingerprint. Video Fingerprint is a unique identity of a video most commonly called as video signature. The video signature has numerous applications like distribution management, corporate or personal database management, rights management and monetization, metadata association, and usage monitoring. We will be making use of this Video content identification tool for implementation of Topic linking concept, a method of organizing contents based on topics, presentation videos and provides such efficient way of browsing, such as news programs. This in turn helps to categorize the video according to its possessed content and store and manage the multimedia data in an easy way.
References
- L. Shang, L. Yang, F. Wang, K. -P. Chan, and X. -S. Hua, " Real-time largescale near-duplicate web video retrieval," in Proc. ACM Int. Conf. Multimedia, Oct. 2010, pp. 531–540.
- Content Based Video Copy Detection: Issues and Practices. Sanjoy KumarSaha ,CSE Department, Jadavpur University, Kolkata, India.
- Hampapur, K. Hyun, and R. Bolle, "Comparison of sequence matchingtechniques for video copy detection," inProc. Conf. Storage RetrievalMedia Databases, 2002, pp. 194–201.
- J. Law-To, L. Chen, A. Joly, I. Laptev, O. Buisson, V. Gouet-Brunet, N. Boujemaa, and F. Stentiford, "Video copy detection: A comparativestudy," in Proc. 6th ACM Int. Conf. Image Video Retrieval, Jul. 2007,
- H. T. Shen, X. Zhou, Z. Huang, J. Shao, and X. Zhou, "UQLIPS: AReal-time near-duplicate video clip detection system," inProc. 33rd Int. Conf. Very Large Data Bases, Sep. 2007, pp. 1374–1377.
- Y. Li, J. S. Jin, and X. Zhou. Video matching using binary signature. InProc. Intl. Symp. on Intelligent Signal Processing and Comm. Systems,pages 317 – 320, 2005.
- R. Radhakrishnan and C. Bauer. Robust video fingerprints based on subspace embed-ding. In Proc. ICASSP, pages 2245–2248, 2008.
- S. Lee and C. D. Yoo. Video fingerprinting based on centroids of gradientorientations. In Proc. ICASSP, pages 401 – 404, 2006.
- S-C. S. Cheung and A. Zakhor. Efficient video similarity measurementwith video signature. IEEE Trans. CSVT, 13 No. 1:59–74, 2003
- M. Ferman, A. M. Tekalp, and R. Mehrotra. Robust color histogramdescriptors for video segment retrieval and identification. IEEE Trans. on IP, 11(5):497 – 508, 2002.
- L. Chen and T. S. Chua. A match and tiling approach to content-basedvideo retrieval. In Proc. Intl. Conf. on Multimedia and Expo, 2001.
- International Organization for Standardization Organization InternationaleDe Normalisation Iso/Iec Jtc1/Sc29/Wg11 Coding Of Moving PicturesAnd Audio.
- S. Paschalakis, K. Iwamoto, P. Brasnett, N. Sprljan, R. Oami, T. Nomura,A. Yamada, and M. Bober, "The MPEG-7 Video Signature Tools forContent Identification".
Index Terms
Keywords