Multiple ship targets association method of remote sensing images based on SIFT and bags of visual words model

Lichun Yang; Dan Yang; Jianghao Wu

doi:10.1145/3376067.3376080

Multiple ship targets association method of remote sensing images based on SIFT and bags of visual words model

Lichun Yang
, Dan Yang
, Jianghao Wu

School of Transportation Science and Engineering

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

1 Scopus citations

Abstract

Ships with unique moving and group activity characteristics can be considered as a type of very important military targets in marine situation awareness. We propose a novel method for multiple ship targets association with utilizing multi-temporal optical satellite images. First, a large number of local invariant features are extracted from the region of the optical satellite imagery containing the ship targets. Second, we present a weighted Bag of Visual Words model to perform transforming the 128-dim features to high-order semantic features. Finally, the optimization model based on the Associated Cost Matrix is constructed to solve the target optimal correlation matching. The experimental results clearly demonstrate that the proposed method is robust to multi-target association ambiguity and produces good matching accuracy with low computational effort.

Original language	English
Title of host publication	Proceedings of the 2019 3rd International Conference on Video and Image Processing, ICVIP 2019
Publisher	Association for Computing Machinery
Pages	137-142
Number of pages	6
ISBN (Electronic)	9781450376822
DOIs	https://doi.org/10.1145/3376067.3376080
State	Published - 20 Dec 2019
Event	3rd International Conference on Video and Image Processing, ICVIP 2019 - Shanghai, China Duration: 20 Dec 2019 → 23 Dec 2019

Publication series

Name	ACM International Conference Proceeding Series

Conference

Conference	3rd International Conference on Video and Image Processing, ICVIP 2019
Country/Territory	China
City	Shanghai
Period	20/12/19 → 23/12/19

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 14 Life Below Water

Keywords

Bag of Visual Words (BoVW)
Multi-target association
Multi-temporal remote sensing images
Scale Invariant Feature Transform (SIFT)
Ship targets

Access to Document

10.1145/3376067.3376080

Cite this

Yang, L., Yang, D., & Wu, J. (2019). Multiple ship targets association method of remote sensing images based on SIFT and bags of visual words model. In Proceedings of the 2019 3rd International Conference on Video and Image Processing, ICVIP 2019 (pp. 137-142). (ACM International Conference Proceeding Series). Association for Computing Machinery . https://doi.org/10.1145/3376067.3376080

@inproceedings{eb53b87e1c10448bb8ee659b7295e0be,

title = "Multiple ship targets association method of remote sensing images based on SIFT and bags of visual words model",

abstract = "Ships with unique moving and group activity characteristics can be considered as a type of very important military targets in marine situation awareness. We propose a novel method for multiple ship targets association with utilizing multi-temporal optical satellite images. First, a large number of local invariant features are extracted from the region of the optical satellite imagery containing the ship targets. Second, we present a weighted Bag of Visual Words model to perform transforming the 128-dim features to high-order semantic features. Finally, the optimization model based on the Associated Cost Matrix is constructed to solve the target optimal correlation matching. The experimental results clearly demonstrate that the proposed method is robust to multi-target association ambiguity and produces good matching accuracy with low computational effort.",

keywords = "Bag of Visual Words (BoVW), Multi-target association, Multi-temporal remote sensing images, Scale Invariant Feature Transform (SIFT), Ship targets",

author = "Lichun Yang and Dan Yang and Jianghao Wu",

note = "Publisher Copyright: {\textcopyright} 2019 Association for Computing Machinery.; 3rd International Conference on Video and Image Processing, ICVIP 2019 ; Conference date: 20-12-2019 Through 23-12-2019",

year = "2019",

month = dec,

day = "20",

doi = "10.1145/3376067.3376080",

language = "英语",

series = "ACM International Conference Proceeding Series",

publisher = "Association for Computing Machinery ",

pages = "137--142",

booktitle = "Proceedings of the 2019 3rd International Conference on Video and Image Processing, ICVIP 2019",

address = "美国",

}

Yang, L, Yang, D & Wu, J 2019, Multiple ship targets association method of remote sensing images based on SIFT and bags of visual words model. in Proceedings of the 2019 3rd International Conference on Video and Image Processing, ICVIP 2019. ACM International Conference Proceeding Series, Association for Computing Machinery , pp. 137-142, 3rd International Conference on Video and Image Processing, ICVIP 2019, Shanghai, China, 20/12/19. https://doi.org/10.1145/3376067.3376080

Multiple ship targets association method of remote sensing images based on SIFT and bags of visual words model. / Yang, Lichun; Yang, Dan; Wu, Jianghao.
Proceedings of the 2019 3rd International Conference on Video and Image Processing, ICVIP 2019. Association for Computing Machinery , 2019. p. 137-142 (ACM International Conference Proceeding Series).

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

TY - GEN

T1 - Multiple ship targets association method of remote sensing images based on SIFT and bags of visual words model

AU - Yang, Lichun

AU - Yang, Dan

AU - Wu, Jianghao

PY - 2019/12/20

Y1 - 2019/12/20

N2 - Ships with unique moving and group activity characteristics can be considered as a type of very important military targets in marine situation awareness. We propose a novel method for multiple ship targets association with utilizing multi-temporal optical satellite images. First, a large number of local invariant features are extracted from the region of the optical satellite imagery containing the ship targets. Second, we present a weighted Bag of Visual Words model to perform transforming the 128-dim features to high-order semantic features. Finally, the optimization model based on the Associated Cost Matrix is constructed to solve the target optimal correlation matching. The experimental results clearly demonstrate that the proposed method is robust to multi-target association ambiguity and produces good matching accuracy with low computational effort.

AB - Ships with unique moving and group activity characteristics can be considered as a type of very important military targets in marine situation awareness. We propose a novel method for multiple ship targets association with utilizing multi-temporal optical satellite images. First, a large number of local invariant features are extracted from the region of the optical satellite imagery containing the ship targets. Second, we present a weighted Bag of Visual Words model to perform transforming the 128-dim features to high-order semantic features. Finally, the optimization model based on the Associated Cost Matrix is constructed to solve the target optimal correlation matching. The experimental results clearly demonstrate that the proposed method is robust to multi-target association ambiguity and produces good matching accuracy with low computational effort.

KW - Bag of Visual Words (BoVW)

KW - Multi-target association

KW - Multi-temporal remote sensing images

KW - Scale Invariant Feature Transform (SIFT)

KW - Ship targets

UR - https://www.scopus.com/pages/publications/85081178631

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DO - 10.1145/3376067.3376080

M3 - 会议稿件

AN - SCOPUS:85081178631

T3 - ACM International Conference Proceeding Series

SP - 137

EP - 142

BT - Proceedings of the 2019 3rd International Conference on Video and Image Processing, ICVIP 2019

PB - Association for Computing Machinery

T2 - 3rd International Conference on Video and Image Processing, ICVIP 2019

Y2 - 20 December 2019 through 23 December 2019

ER -

Multiple ship targets association method of remote sensing images based on SIFT and bags of visual words model

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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