Email this article Multi-Cloud System For Multimedia Content Protection
Abstract
Complete multi-cloud framework for interactive media content assurance. The framework bolsters different types of interactive media content and can successfully use changing figuring assets. • Novel technique for making signatures for 3-D videos. This strategy makes marks that catch the profundity in stereo substance without computing the depth signal itself, which is a computationally costly process. • New plan for an appropriated coordinating motor for high-dimensional multimedia items. This outline gives the primitive capacity of discovering - closest neighbors for vast scale datasets. The outline likewise offers an assistant capacity for further preparing of the neighbors. This two-level outline empowers the proposed framework to effectively bolster distinctive sorts of interactive multimedia content.
References
A. Abdelsadek, “Distributed index for matching multimedia objects,”M.S. thesis, School of Comput. Sci., Simon Fraser Univ., Burnaby, BC,Canada, 2014.
A. Abdelsadek and M. Hefeeda, “Dimo: Distributed index for matchingmultimedia objects using MapReduce,” in Proc. ACMMultimedia Syst.Conf. (MMSys’14), Singapore, Mar. 2014, pp. 115–125.
M. Aly, M. Munich, and P. Perona, “Distributed Kd-Trees for retrievalfrom very large image collections,” in Proc. Brit. Mach. Vis. Conf.(BMVC), Dundee, U.K., Aug. 2011.
J. Bentley, “Multidimensional binary search trees used for associativesearching,” in Commun. ACM, Sep. 1975, vol. 18, no. 9, pp. 509–517.[5] P. Cano, E. Batle, T. Kalker, and J. Haitsma, “A review of algorithmsfor audio fingerprinting,” in Proc. IEEE Workshop Multimedia SignalProcess., Dec. 2002, pp. 169–173.
J. Dean and S. Ghemawat, “MapReduce: Simplified data processingon large clusters,” in Proc. Symp. Oper. Syst. Design Implementation(OSDI’04), San Francisco, CA, USA, Dec. 2004, pp. 137–150.
J. Deng, W. Dong, R. Socher, L. Li, K. Li, and L. Fei-Fei, “Imagenet:A large-scale hierarchical image database,” in Proc. IEEE Conf.Comput. Vis. Pattern Recog. (CVPR’09), Miami, FL, USA, Jun. 2009,pp. 248–255.
A. Hampapur, K. Hyun, and R. Bolle, “Comparison of sequencematching techniques for video copy detection,” in Proc. SPIE Conf.Storage Retrieval Media Databases (SPIE’02), San Jose, CA, USA,Jan. 2002, pp. 194–201.
S. Ioffe, “Full-length video fingerprinting. Google Inc.,” U.S. Patent8229219, Jul. 24, 2012.
A. Kahng, J. Lach, W. Mangione-Smith, S. Mantik, I. Markov, M.Potkonjak, P. Tucker, H. Wang, and G. Wolfe, “Watermarking techniquesfor intellectual property protection,” in Proc. 35th Annu. Design
Autom. Conf. (DAC’98), San Francisco, CA, USA, Jun. 1998, pp.776–781.
N. Khodabakhshi and M. Hefeeda, “Spider: A system for finding 3Dvideo copies,” in ACM Trans. Multimedia Comput., Commun., Appl.(TOMM), Feb. 2013, vol. 9, no. 1, pp. 7:1–7:20.
S. Lee and C. Yoo, “Robust video fingerprinting for content-basedvideo identification,” IEEE Trans. Circuits Syst. Video Technol., vol.18, no. 7, pp. 983–988, Jul. 2008.
H. Liao, J. Han, and J. Fang, “Multi-dimensional index on hadoopdistributed file system,” in Proc. IEEE Conf. Netw., Archit. Storage(NAS’10), Macau, China, Jul. 2010, pp. 240–249.
Z. Liu, T. Liu, D. Gibbon, and B. Shahraray, “Effective, and scalablevideo copy detection,” in Proc. ACM Conf. Multimedia Inf. Retrieval(MIR’10), Philadelphia, PA, USA, Mar. 2010, pp. 119–128.
J. Lu, “Video fingerprinting for copy identification: From researchto industry applications,” in Proc. SPIE, 2009, vol. 7254, pp.725402:1–725402:15.
Refbacks
- There are currently no refbacks.
Copyright © 2013, All rights reserved.| ijseat.com
International Journal of Science Engineering and Advance Technology is licensed under a Creative Commons Attribution 3.0 Unported License.Based on a work at IJSEat , Permissions beyond the scope of this license may be available at http://creativecommons.org/licenses/by/3.0/deed.en_GB.