Saliency based SIFT keypoints filtration

Xin He; Huiyun Jing; Xuefeng Bai; Li Li; Qi Han; Xiamu Niu

doi:10.1117/12.946105

Saliency based SIFT keypoints filtration

Xin He^*
, Huiyun Jing
, Xuefeng Bai
, Li Li
, Qi Han
, Xiamu Niu

^*Corresponding author for this work

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

Abstract

In this paper, we propose a novel method to filter the keypoints and reduce redundant keypoints. SIFT (Scale Invariant Feature Transform) is one of the most robust and widely used methods for image matching and object recognition, which is robust to illumination changes, image scaling and rotation. However SIFT generates a large number of redundant keypoints in the background of the scene. Based on saliency detection and salient region selection, the keypoints out of the selected salient region are pruned in our method. The experimental results show that though the repeatability in our method is a little lower than original SIFT (less than 6%), the number of keypoints in our method is significantly reduced (more than 33%).

Original language	English
Title of host publication	Fourth International Conference on Digital Image Processing, ICDIP 2012
DOIs	https://doi.org/10.1117/12.946105
State	Published - 2012
Externally published	Yes
Event	4th International Conference on Digital Image Processing, ICDIP 2012 - Kuala Lumpur, Malaysia Duration: 7 Apr 2012 → 8 Apr 2012

Publication series

Name	Proceedings of SPIE - The International Society for Optical Engineering
Volume	8334
ISSN (Print)	0277-786X

Conference

Conference	4th International Conference on Digital Image Processing, ICDIP 2012
Country/Territory	Malaysia
City	Kuala Lumpur
Period	7/04/12 → 8/04/12

Keywords

Keypoints filtration
SIFT
Saliency map

Access to Document

10.1117/12.946105

Cite this

@inproceedings{b60cc9069e704aa1bb409bca91dbda4b,

title = "Saliency based SIFT keypoints filtration",

abstract = "In this paper, we propose a novel method to filter the keypoints and reduce redundant keypoints. SIFT (Scale Invariant Feature Transform) is one of the most robust and widely used methods for image matching and object recognition, which is robust to illumination changes, image scaling and rotation. However SIFT generates a large number of redundant keypoints in the background of the scene. Based on saliency detection and salient region selection, the keypoints out of the selected salient region are pruned in our method. The experimental results show that though the repeatability in our method is a little lower than original SIFT (less than 6\%), the number of keypoints in our method is significantly reduced (more than 33\%).",

keywords = "Keypoints filtration, SIFT, Saliency map",

author = "Xin He and Huiyun Jing and Xuefeng Bai and Li Li and Qi Han and Xiamu Niu",

year = "2012",

doi = "10.1117/12.946105",

language = "英语",

isbn = "9780819489913",

series = "Proceedings of SPIE - The International Society for Optical Engineering",

booktitle = "Fourth International Conference on Digital Image Processing, ICDIP 2012",

note = "4th International Conference on Digital Image Processing, ICDIP 2012 ; Conference date: 07-04-2012 Through 08-04-2012",

}

He, X, Jing, H, Bai, X, Li, L, Han, Q & Niu, X 2012, Saliency based SIFT keypoints filtration. in Fourth International Conference on Digital Image Processing, ICDIP 2012., 833415, Proceedings of SPIE - The International Society for Optical Engineering, vol. 8334, 4th International Conference on Digital Image Processing, ICDIP 2012, Kuala Lumpur, Malaysia, 7/04/12. https://doi.org/10.1117/12.946105

TY - GEN

T1 - Saliency based SIFT keypoints filtration

AU - He, Xin

AU - Jing, Huiyun

AU - Bai, Xuefeng

AU - Li, Li

AU - Han, Qi

AU - Niu, Xiamu

PY - 2012

Y1 - 2012

N2 - In this paper, we propose a novel method to filter the keypoints and reduce redundant keypoints. SIFT (Scale Invariant Feature Transform) is one of the most robust and widely used methods for image matching and object recognition, which is robust to illumination changes, image scaling and rotation. However SIFT generates a large number of redundant keypoints in the background of the scene. Based on saliency detection and salient region selection, the keypoints out of the selected salient region are pruned in our method. The experimental results show that though the repeatability in our method is a little lower than original SIFT (less than 6%), the number of keypoints in our method is significantly reduced (more than 33%).

AB - In this paper, we propose a novel method to filter the keypoints and reduce redundant keypoints. SIFT (Scale Invariant Feature Transform) is one of the most robust and widely used methods for image matching and object recognition, which is robust to illumination changes, image scaling and rotation. However SIFT generates a large number of redundant keypoints in the background of the scene. Based on saliency detection and salient region selection, the keypoints out of the selected salient region are pruned in our method. The experimental results show that though the repeatability in our method is a little lower than original SIFT (less than 6%), the number of keypoints in our method is significantly reduced (more than 33%).

KW - Keypoints filtration

KW - SIFT

KW - Saliency map

UR - https://www.scopus.com/pages/publications/84874705458

U2 - 10.1117/12.946105

DO - 10.1117/12.946105

M3 - 会议稿件

AN - SCOPUS:84874705458

SN - 9780819489913

T3 - Proceedings of SPIE - The International Society for Optical Engineering

BT - Fourth International Conference on Digital Image Processing, ICDIP 2012

T2 - 4th International Conference on Digital Image Processing, ICDIP 2012

Y2 - 7 April 2012 through 8 April 2012

ER -

Saliency based SIFT keypoints filtration

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Keywords

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