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Reseach Article

Methodology of Multimedia and Visualization

by Balwinder Kaur, Sonia Sharma, Prince Verma
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 74 - Number 16
Year of Publication: 2013
Authors: Balwinder Kaur, Sonia Sharma, Prince Verma
10.5120/12972-0159

Balwinder Kaur, Sonia Sharma, Prince Verma . Methodology of Multimedia and Visualization. International Journal of Computer Applications. 74, 16 ( July 2013), 36-38. DOI=10.5120/12972-0159

@article{ 10.5120/12972-0159,
author = { Balwinder Kaur, Sonia Sharma, Prince Verma },
title = { Methodology of Multimedia and Visualization },
journal = { International Journal of Computer Applications },
issue_date = { July 2013 },
volume = { 74 },
number = { 16 },
month = { July },
year = { 2013 },
issn = { 0975-8887 },
pages = { 36-38 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume74/number16/12972-0159/ },
doi = { 10.5120/12972-0159 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:43:03.896219+05:30
%A Balwinder Kaur
%A Sonia Sharma
%A Prince Verma
%T Methodology of Multimedia and Visualization
%J International Journal of Computer Applications
%@ 0975-8887
%V 74
%N 16
%P 36-38
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

New visualization tools have been developed but geospatial data models and theories remain unchanged because they enable a user to determine a video's distinguishing content without investing long viewing times or requiring high network- transfer speeds. Recent developments in computer hardware and algorithm design have made possible content to integrate media indexing with computer visualization to achieve effective content-based access to video information. This paper starts addressing the theoretical aspect of a multimedia visualization and a consistent framework to express different types of data sources.

References
  1. Govedarvo, N, Niepage, S, and Burkhard, H. D. 2010. Semantic Content Models In ARA. In ISSN:1867-366X (Journal), Vol. 3, No. 1, 28 – 39.
  2. Ramírez, J. R. 2005. Advance in Multimedia Mapping. In Proceedings of the International Cartographic Conference, Coruña, Spain.
  3. Himmel, D, Greaves, M, Kao, A, and Poteet, S. 1998. Visualizations for Large Collection of Multimedia Information.
  4. Korakakis, G, Pavlatou, E. A, Palyvos J. A, Spyrellis, N. 2008. 3D visualization types in multimedia applications for science learning. A case study for 8th grade students in Greece, Computer & Education, 52(2), 390-401.
  5. Velez, M. , Silver, D. , and Tremaine, M. 2006. Understanding visualization through spatial ability differences. In Extended Proceedings of Visualization. Baltimore, MD.
  6. Sorden, S. 2005. A cognitive approach to instructional design for multimedia. In Learning Informing Science Journal, 8, 263–279.
  7. Samaras, H. , Giouvanakis, N. , Bousiou, D. , & Tarabanis, K. 2006. Towards a new generation of multimedia learning research. AACE Journal, 14(1), 3–30.
  8. Graham, J, Erol, B, Hull, J. J, and Lee, D. S. 2003. The Video Paper Multimedia Analysis System.
  9. Cawthon N. , Vande Moere A. 2007. The Effect of Aesthetic on the Usability of Data Visualization. IV, 637-648.
  10. Nagel, T, and Duval, E. 2012. Interactive Exploration of Geospatial Network Visualization. In Proceeding CHIEA'12 CHI'12 Extended Abstracts on Human Factors in Computing Systems, Pages 557-572, ACM Newyork, NYK, USA.
  11. Vedran Sabol, Wolfgang Kienreich, Michael Granitzer. 2008. Visualisation Techniques for Analysis and Exploration of Multimedia Data. Studies in Computational Intelligence Volume 101, pp 219-238
Index Terms

Computer Science
Information Sciences

Keywords

Multimedia linear content Semantic Content Modeling and Perceptual Content Modeling