Region-Based Segmentation of Generic Video Scenes Indexing
In this work we develop an object extraction method
and propose efficient algorithms for object motion characterization.
The set of proposed tools serves as a basis for development of objectbased
functionalities for manipulation of video content. The
estimators by different algorithms are compared in terms of quality
and performance and tested on real video sequences. The proposed
method will be useful for the latest standards of encoding and
description of multimedia content – MPEG4 and MPEG7.
[1] A. M. Aree, motion estimation by differential methods for
MPEG2 video coding, Journal of Dohuk University,2005, Vol.8,
No.2.
[2] S. Jehan-Besson, M. Barlaud, G. Aubert, Video object
segmentation using Eulerian region-based active contour, IEEE
International Conference on ICCV, 2001, Vol. 1, pp. 353-360.
[3] W. Wei and N. King, Automatic Video Object Segmentation for
MPEG-4. School of Computer Engineering, 2003, Nanyang
Technological University, Singapore.
[4] S. Jehan, M. Barlaud, and G. Aubert, Detection and tracking of
moving objects using a new level set based method, 2000,
ICPR.
[5] M. Changick and H. Jenq-Neng, Video Object Extraction for
Object-Oriented Applications. Journal on VLSI, 2001, 29(1),
pp. 7-21.
[6] B. G. Shunck and B. P. Horn, Determining optical flow.
Artificial Intelligence, 1981, Vol(17) :185-203.
[7] D. R. Walker and K. R. RAO, Improved pel-recursive motion
compensation. Artificial Intelligence, 1981,Vol (32): 1128-
1134.
[8] F. Cafforio, The differential method for image motion
estimation". Image sequence processing , 1983, 104-124
[9] J. R. Shewchuk, An introduction to the conjugate gradient
method. School of Computer Science, 1994.
[1] A. M. Aree, motion estimation by differential methods for
MPEG2 video coding, Journal of Dohuk University,2005, Vol.8,
No.2.
[2] S. Jehan-Besson, M. Barlaud, G. Aubert, Video object
segmentation using Eulerian region-based active contour, IEEE
International Conference on ICCV, 2001, Vol. 1, pp. 353-360.
[3] W. Wei and N. King, Automatic Video Object Segmentation for
MPEG-4. School of Computer Engineering, 2003, Nanyang
Technological University, Singapore.
[4] S. Jehan, M. Barlaud, and G. Aubert, Detection and tracking of
moving objects using a new level set based method, 2000,
ICPR.
[5] M. Changick and H. Jenq-Neng, Video Object Extraction for
Object-Oriented Applications. Journal on VLSI, 2001, 29(1),
pp. 7-21.
[6] B. G. Shunck and B. P. Horn, Determining optical flow.
Artificial Intelligence, 1981, Vol(17) :185-203.
[7] D. R. Walker and K. R. RAO, Improved pel-recursive motion
compensation. Artificial Intelligence, 1981,Vol (32): 1128-
1134.
[8] F. Cafforio, The differential method for image motion
estimation". Image sequence processing , 1983, 104-124
[9] J. R. Shewchuk, An introduction to the conjugate gradient
method. School of Computer Science, 1994.
@article{"International Journal of Information, Control and Computer Sciences:54181", author = "Aree A. Mohammed", title = "Region-Based Segmentation of Generic Video Scenes Indexing", abstract = "In this work we develop an object extraction method
and propose efficient algorithms for object motion characterization.
The set of proposed tools serves as a basis for development of objectbased
functionalities for manipulation of video content. The
estimators by different algorithms are compared in terms of quality
and performance and tested on real video sequences. The proposed
method will be useful for the latest standards of encoding and
description of multimedia content – MPEG4 and MPEG7.", keywords = "Object extraction, Video indexing, Segmentation,Optical flow, Motion estimators.", volume = "2", number = "6", pages = "1933-7", }