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Optical Engineering

Scale-invariant object tracking method using strong corners in the scale domain
Author(s): Hyungtae Lee; Pyeong Gang Heo; Jung-Yeop Suk; Bo-Yeoun Yeou; HyunWook Park
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Paper Abstract

The object tracking method using the scale-invariant feature transform (SIFT) is applicable to rotated or scaled targets, and also maintains good performance in occluded or intensity-changed images. However, the SIFT algorithm has high computational complexity. In addition, the template size has to be sufficiently large to extract enough features to match. This paper proposes a scale-invariant object tracking method using strong corner points in the scale domain. The proposed method makes it possible to track a smaller object than the SIFT tracker by extracting relatively more features from a target image. In the proposed method, strong features of the template image, which correspond to strong corner points in the scale domain, are selected. The strong features of the template image are then matched with all features of the target image. The matched features are used to find relations between the template and target images. In experimental results, the proposed method shows better performance than the existing SIFT tracker.

Paper Details

Date Published: 1 January 2009
PDF: 9 pages
Opt. Eng. 48(1) 017204 doi: 10.1117/1.3070665
Published in: Optical Engineering Volume 48, Issue 1
Show Author Affiliations
Hyungtae Lee, Korea Advanced Institute of Science and Technology (Korea, Republic of)
Pyeong Gang Heo, Korea Advanced Institute of Science and Technology (Korea, Republic of)
Jung-Yeop Suk, LIG Nex1 Co., Ltd. (Korea, Republic of)
Bo-Yeoun Yeou, LIG Nex1 Co., Ltd. (Korea, Republic of)
HyunWook Park, Korea Advanced Institute of Science and Technology (Korea, Republic of)


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