Cross Reference Strategies for Cooperative Modalities
||International Journal of Computer Trends and Technology (IJCTT)||
|© - Issue 2012 by IJCTT Journal|
|Year of Publication : 2012|
|Authors :D.Srikar, Ch.S.V.V.S.N.Murthy.|
D.Srikar, Ch.S.V.V.S.N.Murthy."Cross Reference Strategies for Cooperative Modalities "International Journal of Computer Trends and Technology (IJCTT),V3(3):1039-1043 Issue 2012 .ISSN 2231-2803.www.ijcttjournal.org. Published by Seventh Sense Research Group.
Abstract: -In this paper, we propose a Generic video visual approach for find the best cluster video shots. It is one kind of categorization technique for classifying clusters. New Clusters Sequences generation or creation using local videos of sequence and global temporal videos sequences. Previously we discuss about relevance feedback, pseudo relevance feedback, Meta search strategy, Content based video retrieval are not provides better ranking features. Some kind’s videos are gets the wrong ranking features and wrong clusters also. These clusters are works as missing features clusters. Now we introduce perfect clusters creation with genetic algorithm. We take major input as a different or multiple numbers of modalities. Each and every model of genomes we recognize same like collects the different video of different genomes. It is good classification and categorization process. Classification works matrix based features selection from multiple modalities. It is the regroup and new video creation. New video contains good density and content features. This is optimal cluster creation.
 Alessandri. A, Gaggero. M and Tonelli. F “Relevance feedback and query expansion” DRAFT! © April 1, 2009 Cambridge University Press. Feedback welcome.
 P Geeta, Vasumathi Narayanan. “A Survey of Content- Based Video Retrieval” Journal of Computer Science 4 (6): 474-486, 2008 ISSN 1549-3636 © 2008 Science Publications
 Emilie Dumont and Georges Quenot. “Automatic Story Segmentation for TV News Video using Multiple Modalities” Transactions on Automation Science and Engineering: 96 – 110 (2010).
 P. Salembie, N. O’Connor2, F. Pereira “HIERARCHICAL VISUAL DESCRIPTION SCHEMES FOR STILL IMAGES AND VIDEO SEQUENCES” Transactions on Intelligent Transport Systems, IET: 307 – 317 (2010).
 M. Sainz, N.Bagherzadeh, A. Susin J.A “MTMesh: Image Based Mesh Reconstruction and Rendering” Transactions on Systems, Man and Cybernetics, Part A: Systems and Humans: 767 – 778(2010).
 Zhengdong Lu , Miguel A´ . Carreira-Perpin˜a´n “Constrained Spectral Clustering through Affinity Propagation” Transactions on Services Computing:104- 115(2010).
 Alejandro Jaimes and Shih-Fu Chang ”A Conceptual Framework for Indexing Visual Information at Multiple Levels” IS&T/SPIE Internet Imaging, Vol. 3964, San Jose, CA, Jan. 2000
 Johann M Kraus, Hans A Kestler “A highly efficient multi-core algorithm for clustering extremely large datasets” Kraus and Kestler BMC Bioinformatics 2010, 11:169 http://www.biomedcentral.com/1471-2105/11/16
Keywords:AGenetic algorithm, multiple modalities, segmentation, indexing features, classification, categorization.