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Reseach Article

Generation of Video Panorama System

by Kawther Abbas Sallal, Abdul Monem Saleh Rahma
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 73 - Number 5
Year of Publication: 2013
Authors: Kawther Abbas Sallal, Abdul Monem Saleh Rahma
10.5120/12737-9614

Kawther Abbas Sallal, Abdul Monem Saleh Rahma . Generation of Video Panorama System. International Journal of Computer Applications. 73, 5 ( July 2013), 20-26. DOI=10.5120/12737-9614

@article{ 10.5120/12737-9614,
author = { Kawther Abbas Sallal, Abdul Monem Saleh Rahma },
title = { Generation of Video Panorama System },
journal = { International Journal of Computer Applications },
issue_date = { July 2013 },
volume = { 73 },
number = { 5 },
month = { July },
year = { 2013 },
issn = { 0975-8887 },
pages = { 20-26 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume73/number5/12737-9614/ },
doi = { 10.5120/12737-9614 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:39:16.675286+05:30
%A Kawther Abbas Sallal
%A Abdul Monem Saleh Rahma
%T Generation of Video Panorama System
%J International Journal of Computer Applications
%@ 0975-8887
%V 73
%N 5
%P 20-26
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The construction of large, high-resolution view is an active area of research in many fields like computer vision and computer graphics. A Panorama is the process of combining multiple images or videos with overlapping region to produce a panoramic view. it enables producing a complete view of an area that cannot fit in a single shot. This paper describes simple method for taking two or more videos and creating a panoramic video. Two steps of motion estimation is done. The first, estimates the motion between the frames of the two videos and the second estimates the motion to produce the final panoramic video. The process to generate a panoramic view can be divided into four main components: video acquisition, similar regions detection, motion estimation and merging. Geometric moment invariant produces a set of features that are invariant under shifting, scaling and rotation. it is widely used to extract the global features for pattern recognition due to its discrimination power and robustness. In this paper, moment invariant is used to determine the locations of merging. The experimental results are done on videos taken by two horizontally adjacent cameras. The results show that the proposed algorithm is fast and efficient.

References
  1. Hermans C. etl, "Augmented Panoramic Video" The Eurographics Association and Blackwell Publishing Ltd. Published by Blackwell Publishing ,2008.
  2. Zheng E. , Raguram R. , Fite-Georgel P. , "Efficient generation of multi-perspective panoramas", IEEE, International Conference on 3D Imaging, Modeling, Processing, Visualization and Transmission, 2011.
  3. Heymann S. , "representation coding and interactive rendering of high resolution panoramic images and video using MPEG-", Fraunhofer Institute for Telecommunications, Image Processing Department , Germany, 2005
  4. Adrien B. etl, "From Video Sequences to Motion Panoramas", Workshop on Motion and Video Computing , United States, 2002.
  5. Huang F. etl, "Animated Panorama from a Panning Video Sequence", IEEE, 2010.
  6. Imran A. and James C. , "A Panoramic Video System" Department of Computer Science University of the Western Cape, South Africa,2010.
  7. Lin L. and Nan G. , "Algorithm for Sequence Image Automatic Mosaic based on SIFT Feature", WASE International Conference on Information Engineering, 2010.
  8. Irani M. and Anandan P. , "Video indexing based on mosaic representations", in Proceedings of the IEEE, vol. 86, no. 5, pp. 905–921, May 1998.
  9. Shalini G. P. "Principles of Computer Graphics: Theory and Practice Using OpenGL and Maya", Springer, 2004.
  10. Hu M. K. , "Visual pattern recognition by moments Invariants", IRE Trans. Information Theory, 8: 179- 87,1962.
  11. Rizon M. and et al. , "Object Detection using Geometric Invariant Moment", American Journal of Applied Sciences , ISSN 1546-9239, 2006.
  12. Bei J. and Chen L. , "Map Matching Algorithms Based on Invariant Moments", Journal of Computational Information Systems, 2011.
  13. Adelson E. and et al. , "Pyramid methods in image processing," RCA Engineer, 29-6, 1984.
  14. Kavitha G. and Shanmugam J. , "Video Object Extraction Based on a Comparative Study of Efficient Edge Detection Techniques", The International Arab Journal of Information Technology, Vol. 6, No. 2, 2009.
  15. Aroh B. , "Block Matching Algorithms for Motion Estimation", IEEE, Final Project Paper, 2004.
Index Terms

Computer Science
Information Sciences

Keywords

geometric moments motion estimation registration panoramic video