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Structure and Motion Estimation with Expectation Maximization and Extended Kalman Smoother for Continuous Image Sequences
Kauai, Hawaii December 08-December 14
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CVPR.2001.9906602001 IEEE Computer Society Conference ...
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Yongduek Seo, Ki-Sang Hong, "Structure and Motion Estimation with Expectation Maximization and Extended Kalman Smoother for Continuous Image Sequences," Computer Vision and Pattern Recognition, IEEE Computer Society Conference on, vol. 1, pp. 1148, 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'01) - Volume 1, 2001.
 
 
BibTex
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@article{ 10.1109/CVPR.2001.990660,
author = {Yongduek Seo and Ki-Sang Hong},
title = {Structure and Motion Estimation with Expectation Maximization and Extended Kalman Smoother for Continuous Image Sequences},
journal ={Computer Vision and Pattern Recognition, IEEE Computer Society Conference on},
volume = {1},
year = {2001},
issn = {1063-6919},
pages = {1148},
doi = {http://doi.ieeecomputersociety.org/10.1109/CVPR.2001.990660},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - Computer Vision and Pattern Recognition, IEEE Computer Society Conference on
TI - Structure and Motion Estimation with Expectation Maximization and Extended Kalman Smoother for Continuous Image Sequences
SN - 1063-6919
SP
EP
A1 - Yongduek Seo,
A1 - Ki-Sang Hong,
PY - 2001
KW - null
VL - 1
JA - Computer Vision and Pattern Recognition, IEEE Computer Society Conference on
ER -
 
Yongduek Seo, Pohang University of Science and Technology
Ki-Sang Hong, Pohang University of Science and Technology
This paper deals with the problem of estimating structure and motion from long continuous image sequences, applying the Expectation Maximization algorithm based on extended Kalman smoother to impose the time-continuity of the motion parameters. By repeatedly estimating the state transition matrix of the dynamic equation and the param-eters of noise processes in the dynamic and measurement equations, this optimization gives the maximum likelihood estimates of the motion and structure parameters. Practically, this research is essential for dealing with a long video-rate image sequence with partially unknown system equation and noise. The algorithm is implemented and tested for a real image sequence.
Citation:
Yongduek Seo, Ki-Sang Hong, "Structure and Motion Estimation with Expectation Maximization and Extended Kalman Smoother for Continuous Image Sequences," cvpr, vol. 1, pp.1148, 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'01) - Volume 1, 2001
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