International Journal of Computer Network and Information Security (IJCNIS)
IJCNIS Vol. 4, No. 7, 8 Jul. 2012
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Estimating the Video Registration Using Image Motions
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Author(s)
N.Kannaiya Raja
1,*
K.Arulanandam
1
R.Radha krishnan
1
M.Nataraj
1
Index Terms
Dynamic textures, video registration, nonrigid dynamical scenes
Abstract
In this research, we consider the problems of registering multiple video sequences dynamic scenes which are not limited non rigid objects such as fireworks, blasting, high speed car moving taken from different vantage points. In this paper we propose a simple algorithm we can create different frames on particular videos moving for matching such complex scenes. Our algorithm does not require the cameras to be synchronized, and is not based on frame-by-frame or volume-by-volume registration. Instead, we model each video as the output of a linear dynamical system and transform the task of registering the video sequences to that of registering the parameters of the corresponding dynamical models. In this paper we use of a joint frame together to form distinct frame concurrently. The joint identification and the Jordan canonical form are not only applicable to the case of registering video sequences, but also to the entire genre of algorithms based on the dynamic texture model. We have also shown that out of all the possible choices for the method of identification and canonical form, the JID using JCF performs the best.
Cite This Paper
N.Kannaiya Raja, K.Arulanandam, R.Radha krishnan, M.Nataraj, "Estimating the Video Registration Using Image Motions", International Journal of Computer Network and Information Security(IJCNIS), vol.4, no.7, pp.69-79, 2012. DOI:10.5815/ijcnis.2012.07.08
Reference
[1]M. Shah and R. Kumar (Eds). Video Registration. Kluwer, May 2003.
[2]B. Zitova and J. Flusser. Image registration methods: a survey. Image and Vision Computing, 21(11):977–1000, October 2003.
[3]Jose Miguel Buenaposada, Enrique Munoz, and Luis Baumela. Tracking a planar patch by additive image registration. 2003.
[4]P. Zhilkin and M. E. Alexander. A patch algorithm for fast registration of distortions. Vibrational Spectroscopy, 28(1):67 – 72, 2002.
[5]A. Krutz, M. Frater, M. Kunter, and T. Sikora. Windowed image registration for robust mosaicing of scenes with large background occlusions. In Image Processing, 2006 IEEE International Conference on, pages 353–356, Oct. 2006.
[6]A. Krutz, M. Frater, and T. Sikora. Window-based image registration using variable window sizes. In Image Processing, 2007. ICIP 2007.IEEE International Conference on, volume 5, pages V –369–V –372,16 2007-Oct. 19 2007.
[7]Bin Qi, M. Ghazal, and A. Amer. Robust global motion estimation oriented to video object segmentation. Image Processing, IEEE Transactions on, 17(6):958–967, June 2008.
[8]Marina Georgia Arvanitidou, Alexander Glantz, Andreas Krutz, Thomas Sikora, Marta Mrak, and Ahmet Kondoz. Global motion estimation using variable block sizes and its application to object segmentation. Image Analysis for Multimedia Interactive Services, International Workshop on, pages 173–176, 2009.
[9]Fang Zhu, Ping Xue, and Eeping Ong. Low-complexity global motion estimation based on content analysis. In Circuits and Systems, 2003.ISCAS '03. Proceedings of the 2003 International Symposium on, volume 2, pages II–624–II–627 vol.2, May 2003.
[10]John Y. A. Wang and Edward H. Adelson. Representing moving images with layers. IEEE Transactions on Image Processing, 3:625–638, 1994.
[11]A. Chan and N. Vasconcelos, "Probabilistic Kernels for the Classification of Auto-Regressive Visual Processes," Proc. IEEE Conf. Computer Vision and Pattern Recognition, vol. 1, pp. 846-851, 2005.
[12]G. Doretto, A. Chiuso, Y. Wu, and S. Soatto, "Dynamic Textures," Int'l J. Computer Vision, vol. 51, no. 2, pp. 91-109, 2003.
[13]R. Hartley and A. Zisserman, Multiple View Geometry in Computer Vision. Cambridge Univ. Press, 2000.
[14] P.V. Overschee and B.D. Moor, "Subspace Algorithms for the Stochastic Identification Problem," Automatica, vol. 29, no. 3, pp. 649-660, 1993.
[15]A. Ravichandran and R. Vidal, "Mosaicing Nonrigid Dynamical Scenes," Proc. Workshop Dynamic Vision, 2007.
[16]W.J. Rugh, Linear System Theory, second ed. Prentice Hall, 1996.
[17]R. Vidal and A. Ravichandran, "Optical Flow Estimation and Segmentation of Multiple Moving Dynamic Textures," Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 516-521, 2005.