Template Matching Method Based on Visual Feature Constraint and Structure Constraint

Zhu LI; Kojiro TOMOTSUNE; Yoichi TOMIOKA; Hitoshi KITAZAWA

doi:10.1587/transinf.E95.D.2105

Template Matching Method Based on Visual Feature Constraint and Structure Constraint

Zhu LI, Kojiro TOMOTSUNE, Yoichi TOMIOKA, Hitoshi KITAZAWA

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Template matching for image sequences captured with a moving camera is very important for several applications such as Robot Vision, SLAM, ITS, and video surveillance systems. However, it is difficult to realize accurate template matching using only visual feature information such as HSV histograms, edge histograms, HOG histograms, and SIFT features, because it is affected by several phenomena such as illumination change, viewpoint change, size change, and noise. In order to realize robust tracking, structure information such as the relative position of each part of the object should be considered. In this paper, we propose a method that considers both visual feature information and structure information. Experiments show that the proposed method realizes robust tracking and determine the relationships between object parts in the scenes and those in the template.

Publication: IEICE TRANSACTIONS on Information Vol.E95-D No.8 pp.2105-2115

Publication Date: 2012/08/01

Publicized

Online ISSN: 1745-1361

DOI: 10.1587/transinf.E95.D.2105

Type of Manuscript: PAPER

Category: Image Recognition, Computer Vision

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Zhu LI, Kojiro TOMOTSUNE, Yoichi TOMIOKA, Hitoshi KITAZAWA, "Template Matching Method Based on Visual Feature Constraint and Structure Constraint" in IEICE TRANSACTIONS on Information, vol. E95-D, no. 8, pp. 2105-2115, August 2012, doi: 10.1587/transinf.E95.D.2105.
Abstract: Template matching for image sequences captured with a moving camera is very important for several applications such as Robot Vision, SLAM, ITS, and video surveillance systems. However, it is difficult to realize accurate template matching using only visual feature information such as HSV histograms, edge histograms, HOG histograms, and SIFT features, because it is affected by several phenomena such as illumination change, viewpoint change, size change, and noise. In order to realize robust tracking, structure information such as the relative position of each part of the object should be considered. In this paper, we propose a method that considers both visual feature information and structure information. Experiments show that the proposed method realizes robust tracking and determine the relationships between object parts in the scenes and those in the template.
URL: https://globals.ieice.org/en_transactions/information/10.1587/transinf.E95.D.2105/_p

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@ARTICLE{e95-d_8_2105,
author={Zhu LI, Kojiro TOMOTSUNE, Yoichi TOMIOKA, Hitoshi KITAZAWA, },
journal={IEICE TRANSACTIONS on Information},
title={Template Matching Method Based on Visual Feature Constraint and Structure Constraint},
year={2012},
volume={E95-D},
number={8},
pages={2105-2115},
abstract={Template matching for image sequences captured with a moving camera is very important for several applications such as Robot Vision, SLAM, ITS, and video surveillance systems. However, it is difficult to realize accurate template matching using only visual feature information such as HSV histograms, edge histograms, HOG histograms, and SIFT features, because it is affected by several phenomena such as illumination change, viewpoint change, size change, and noise. In order to realize robust tracking, structure information such as the relative position of each part of the object should be considered. In this paper, we propose a method that considers both visual feature information and structure information. Experiments show that the proposed method realizes robust tracking and determine the relationships between object parts in the scenes and those in the template.},
keywords={},
doi={10.1587/transinf.E95.D.2105},
ISSN={1745-1361},
month={August},}

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TY - JOUR
TI - Template Matching Method Based on Visual Feature Constraint and Structure Constraint
T2 - IEICE TRANSACTIONS on Information
SP - 2105
EP - 2115
AU - Zhu LI
AU - Kojiro TOMOTSUNE
AU - Yoichi TOMIOKA
AU - Hitoshi KITAZAWA
PY - 2012
DO - 10.1587/transinf.E95.D.2105
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E95-D
IS - 8
JA - IEICE TRANSACTIONS on Information
Y1 - August 2012
AB - Template matching for image sequences captured with a moving camera is very important for several applications such as Robot Vision, SLAM, ITS, and video surveillance systems. However, it is difficult to realize accurate template matching using only visual feature information such as HSV histograms, edge histograms, HOG histograms, and SIFT features, because it is affected by several phenomena such as illumination change, viewpoint change, size change, and noise. In order to realize robust tracking, structure information such as the relative position of each part of the object should be considered. In this paper, we propose a method that considers both visual feature information and structure information. Experiments show that the proposed method realizes robust tracking and determine the relationships between object parts in the scenes and those in the template.
ER -