Information fusion based on optical flow field and feature extraction for solving registration problems

Ze Xu Zhang; Ping Yuan Cui

doi:10.1109/ICMLC.2006.258799

Information fusion based on optical flow field and feature extraction for solving registration problems

Ze Xu Zhang^*, Ping Yuan Cui

^*Corresponding author for this work

Harbin Institute of Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

A novel information fusion method for solving the automated registration problems was proposed. The main information sources include the global optical flow field and feature extracted from images. Our primary contribution is an improved estimation algorithm for computing the optical flow field using anisotropic diffusion. Moreover, we show that the registration process can be consolidated through the background registration and moving target registration that estimates global deformation while ensuring robustness to systematic errors such as those caused by moving foreground objects or occlusion. The validity and accuracy of the algorithm of optical flow on synthetic and real data are demonstrated. The simulation experiments for infrared images show that the fusion method is ideally suited for the application of automated image registration.

Original language	English
Title of host publication	Proceedings of the 2006 International Conference on Machine Learning and Cybernetics
Pages	4002-4007
Number of pages	6
DOIs	https://doi.org/10.1109/ICMLC.2006.258799
Publication status	Published - 2006
Externally published	Yes
Event	2006 International Conference on Machine Learning and Cybernetics - Dalian, China Duration: 13 Aug 2006 → 16 Aug 2006

Publication series

Name	Proceedings of the 2006 International Conference on Machine Learning and Cybernetics
Volume	2006

Conference

Conference	2006 International Conference on Machine Learning and Cybernetics
Country/Territory	China
City	Dalian
Period	13/08/06 → 16/08/06

Keywords

Automated registration
Feature extraction
Information fusion
Optical flow field

Access to Document

10.1109/ICMLC.2006.258799

Cite this

Zhang, Z. X., & Cui, P. Y. (2006). Information fusion based on optical flow field and feature extraction for solving registration problems. In Proceedings of the 2006 International Conference on Machine Learning and Cybernetics (pp. 4002-4007). Article 4028772 (Proceedings of the 2006 International Conference on Machine Learning and Cybernetics; Vol. 2006). https://doi.org/10.1109/ICMLC.2006.258799

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title = "Information fusion based on optical flow field and feature extraction for solving registration problems",

abstract = "A novel information fusion method for solving the automated registration problems was proposed. The main information sources include the global optical flow field and feature extracted from images. Our primary contribution is an improved estimation algorithm for computing the optical flow field using anisotropic diffusion. Moreover, we show that the registration process can be consolidated through the background registration and moving target registration that estimates global deformation while ensuring robustness to systematic errors such as those caused by moving foreground objects or occlusion. The validity and accuracy of the algorithm of optical flow on synthetic and real data are demonstrated. The simulation experiments for infrared images show that the fusion method is ideally suited for the application of automated image registration.",

keywords = "Automated registration, Feature extraction, Information fusion, Optical flow field",

author = "Zhang, {Ze Xu} and Cui, {Ping Yuan}",

year = "2006",

doi = "10.1109/ICMLC.2006.258799",

language = "English",

isbn = "1424400619",

series = "Proceedings of the 2006 International Conference on Machine Learning and Cybernetics",

pages = "4002--4007",

booktitle = "Proceedings of the 2006 International Conference on Machine Learning and Cybernetics",

note = "2006 International Conference on Machine Learning and Cybernetics ; Conference date: 13-08-2006 Through 16-08-2006",

}

Zhang, ZX & Cui, PY 2006, Information fusion based on optical flow field and feature extraction for solving registration problems. in Proceedings of the 2006 International Conference on Machine Learning and Cybernetics., 4028772, Proceedings of the 2006 International Conference on Machine Learning and Cybernetics, vol. 2006, pp. 4002-4007, 2006 International Conference on Machine Learning and Cybernetics, Dalian, China, 13/08/06. https://doi.org/10.1109/ICMLC.2006.258799

Information fusion based on optical flow field and feature extraction for solving registration problems. / Zhang, Ze Xu; Cui, Ping Yuan.
Proceedings of the 2006 International Conference on Machine Learning and Cybernetics. 2006. p. 4002-4007 4028772 (Proceedings of the 2006 International Conference on Machine Learning and Cybernetics; Vol. 2006).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Information fusion based on optical flow field and feature extraction for solving registration problems

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AU - Cui, Ping Yuan

PY - 2006

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N2 - A novel information fusion method for solving the automated registration problems was proposed. The main information sources include the global optical flow field and feature extracted from images. Our primary contribution is an improved estimation algorithm for computing the optical flow field using anisotropic diffusion. Moreover, we show that the registration process can be consolidated through the background registration and moving target registration that estimates global deformation while ensuring robustness to systematic errors such as those caused by moving foreground objects or occlusion. The validity and accuracy of the algorithm of optical flow on synthetic and real data are demonstrated. The simulation experiments for infrared images show that the fusion method is ideally suited for the application of automated image registration.

AB - A novel information fusion method for solving the automated registration problems was proposed. The main information sources include the global optical flow field and feature extracted from images. Our primary contribution is an improved estimation algorithm for computing the optical flow field using anisotropic diffusion. Moreover, we show that the registration process can be consolidated through the background registration and moving target registration that estimates global deformation while ensuring robustness to systematic errors such as those caused by moving foreground objects or occlusion. The validity and accuracy of the algorithm of optical flow on synthetic and real data are demonstrated. The simulation experiments for infrared images show that the fusion method is ideally suited for the application of automated image registration.

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KW - Feature extraction

KW - Information fusion

KW - Optical flow field

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DO - 10.1109/ICMLC.2006.258799

M3 - Conference contribution

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SN - 1424400619

SN - 9781424400614

T3 - Proceedings of the 2006 International Conference on Machine Learning and Cybernetics

SP - 4002

EP - 4007

BT - Proceedings of the 2006 International Conference on Machine Learning and Cybernetics

T2 - 2006 International Conference on Machine Learning and Cybernetics

Y2 - 13 August 2006 through 16 August 2006

ER -

Information fusion based on optical flow field and feature extraction for solving registration problems

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Keywords

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