IEICE TRANSACTIONS on Information
Robust Moving Object Extraction and Tracking Method Based on Matching Position Constraints
Summary :
Object extraction and tracking in a video image is basic technology for many applications, such as video surveillance and robot vision. Many moving object extraction and tracking methods have been proposed. However, they fail when the scenes include illumination change or light reflection. For tracking the moving object robustly, we should consider not only the RGB values of input images but also the shape information of the objects. If the objects' shapes do not change suddenly, matching positions on the cost matrix of exclusive block matching are located nearly on a line. We propose a method for obtaining the correspondence of feature points by imposing a matching position constraint induced by the shape constancy. We demonstrate experimentally that the proposed method achieves robust tracking in various environments.
- Publication
- IEICE TRANSACTIONS on Information Vol.E98-D No.8 pp.1571-1579
- Publication Date
- 2015/08/01
- Publicized
- 2015/04/28
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.2014EDP7298
- Type of Manuscript
- PAPER
- Category
- Image Recognition, Computer Vision
Authors
Tetsuya OKUDA
Tokyo University of Agriculture and Technology
Yoichi TOMIOKA
Tokyo University of Agriculture and Technology
Hitoshi KITAZAWA
Keyword
Latest Issue
Copyrights notice of machine-translated contents
The copyright of the original papers published on this site belongs to IEICE. Unauthorized use of the original or translated papers is prohibited. See IEICE Provisions on Copyright for details.
Cite this
Copy
Tetsuya OKUDA, Yoichi TOMIOKA, Hitoshi KITAZAWA, "Robust Moving Object Extraction and Tracking Method Based on Matching Position Constraints" in IEICE TRANSACTIONS on Information,
vol. E98-D, no. 8, pp. 1571-1579, August 2015, doi: 10.1587/transinf.2014EDP7298.
Abstract: Object extraction and tracking in a video image is basic technology for many applications, such as video surveillance and robot vision. Many moving object extraction and tracking methods have been proposed. However, they fail when the scenes include illumination change or light reflection. For tracking the moving object robustly, we should consider not only the RGB values of input images but also the shape information of the objects. If the objects' shapes do not change suddenly, matching positions on the cost matrix of exclusive block matching are located nearly on a line. We propose a method for obtaining the correspondence of feature points by imposing a matching position constraint induced by the shape constancy. We demonstrate experimentally that the proposed method achieves robust tracking in various environments.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2014EDP7298/_p
Copy
@ARTICLE{e98-d_8_1571,
author={Tetsuya OKUDA, Yoichi TOMIOKA, Hitoshi KITAZAWA, },
journal={IEICE TRANSACTIONS on Information},
title={Robust Moving Object Extraction and Tracking Method Based on Matching Position Constraints},
year={2015},
volume={E98-D},
number={8},
pages={1571-1579},
abstract={Object extraction and tracking in a video image is basic technology for many applications, such as video surveillance and robot vision. Many moving object extraction and tracking methods have been proposed. However, they fail when the scenes include illumination change or light reflection. For tracking the moving object robustly, we should consider not only the RGB values of input images but also the shape information of the objects. If the objects' shapes do not change suddenly, matching positions on the cost matrix of exclusive block matching are located nearly on a line. We propose a method for obtaining the correspondence of feature points by imposing a matching position constraint induced by the shape constancy. We demonstrate experimentally that the proposed method achieves robust tracking in various environments.},
keywords={},
doi={10.1587/transinf.2014EDP7298},
ISSN={1745-1361},
month={August},}
Copy
TY - JOUR
TI - Robust Moving Object Extraction and Tracking Method Based on Matching Position Constraints
T2 - IEICE TRANSACTIONS on Information
SP - 1571
EP - 1579
AU - Tetsuya OKUDA
AU - Yoichi TOMIOKA
AU - Hitoshi KITAZAWA
PY - 2015
DO - 10.1587/transinf.2014EDP7298
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E98-D
IS - 8
JA - IEICE TRANSACTIONS on Information
Y1 - August 2015
AB - Object extraction and tracking in a video image is basic technology for many applications, such as video surveillance and robot vision. Many moving object extraction and tracking methods have been proposed. However, they fail when the scenes include illumination change or light reflection. For tracking the moving object robustly, we should consider not only the RGB values of input images but also the shape information of the objects. If the objects' shapes do not change suddenly, matching positions on the cost matrix of exclusive block matching are located nearly on a line. We propose a method for obtaining the correspondence of feature points by imposing a matching position constraint induced by the shape constancy. We demonstrate experimentally that the proposed method achieves robust tracking in various environments.
ER -
English
