Ship detection based on spatio-temporal features

Satoru Suzuki, Yasue Mitsukura, Tadasuke Furuya

研究成果: Conference contribution

1 引用 (Scopus)

抄録

The paper proposes the ship detection method based on Spatio-temporal Histograms of Oriented Gradients (STHOG) feature and Support Vector Machine (SVM). STHOG feature, which is the extension version of HOG feature, enables extract spatial and temporal features of an object. The ship detector based on HOG feature can wrongly detect the similar shape objects with ships. On the other hand, the ship detector based on STHOG feature can identify them successfully by utilizing temporal feature of an object. To extract temporal feature of an object, image registration is implemented and an image displacement by camera motion is corrected. Due to high dimensionality of STHOG feature, it requires high computational cost to scan entire image and find ship regions. Principal Component Analysis (PCA) is applied to STHOG feature to compress the dimension. In the computer simulations, the ship detection performance of the proposed method was evaluated. From the simulation results, our proposed method exhibited better results than ship detector based on PCA+HOG feature.

元の言語English
ホスト出版物のタイトル10th France-Japan Congress, 8th Europe-Asia Congress on Mecatronics, MECATRONICS 2014
出版者Institute of Electrical and Electronics Engineers Inc.
ページ93-98
ページ数6
ISBN(印刷物)9781479957170
DOI
出版物ステータスPublished - 2014 1 22
イベント10th France-Japan/8th Europe-Asia Congress on Mecatronics, MECATRONICS 2014 - Tokyo, Japan
継続期間: 2014 11 272014 11 29

Other

Other10th France-Japan/8th Europe-Asia Congress on Mecatronics, MECATRONICS 2014
Japan
Tokyo
期間14/11/2714/11/29

Fingerprint

Ships
Detectors
Principal component analysis
Image registration
Support vector machines
Cameras
Computer simulation
Costs

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Mechanical Engineering

これを引用

Suzuki, S., Mitsukura, Y., & Furuya, T. (2014). Ship detection based on spatio-temporal features. : 10th France-Japan Congress, 8th Europe-Asia Congress on Mecatronics, MECATRONICS 2014 (pp. 93-98). [7018610] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/MECATRONICS.2014.7018610

Ship detection based on spatio-temporal features. / Suzuki, Satoru; Mitsukura, Yasue; Furuya, Tadasuke.

10th France-Japan Congress, 8th Europe-Asia Congress on Mecatronics, MECATRONICS 2014. Institute of Electrical and Electronics Engineers Inc., 2014. p. 93-98 7018610.

研究成果: Conference contribution

Suzuki, S, Mitsukura, Y & Furuya, T 2014, Ship detection based on spatio-temporal features. : 10th France-Japan Congress, 8th Europe-Asia Congress on Mecatronics, MECATRONICS 2014., 7018610, Institute of Electrical and Electronics Engineers Inc., pp. 93-98, 10th France-Japan/8th Europe-Asia Congress on Mecatronics, MECATRONICS 2014, Tokyo, Japan, 14/11/27. https://doi.org/10.1109/MECATRONICS.2014.7018610
Suzuki S, Mitsukura Y, Furuya T. Ship detection based on spatio-temporal features. : 10th France-Japan Congress, 8th Europe-Asia Congress on Mecatronics, MECATRONICS 2014. Institute of Electrical and Electronics Engineers Inc. 2014. p. 93-98. 7018610 https://doi.org/10.1109/MECATRONICS.2014.7018610
Suzuki, Satoru ; Mitsukura, Yasue ; Furuya, Tadasuke. / Ship detection based on spatio-temporal features. 10th France-Japan Congress, 8th Europe-Asia Congress on Mecatronics, MECATRONICS 2014. Institute of Electrical and Electronics Engineers Inc., 2014. pp. 93-98
@inproceedings{5d3d647c96f646ce89a4bb1506ae5e57,
title = "Ship detection based on spatio-temporal features",
abstract = "The paper proposes the ship detection method based on Spatio-temporal Histograms of Oriented Gradients (STHOG) feature and Support Vector Machine (SVM). STHOG feature, which is the extension version of HOG feature, enables extract spatial and temporal features of an object. The ship detector based on HOG feature can wrongly detect the similar shape objects with ships. On the other hand, the ship detector based on STHOG feature can identify them successfully by utilizing temporal feature of an object. To extract temporal feature of an object, image registration is implemented and an image displacement by camera motion is corrected. Due to high dimensionality of STHOG feature, it requires high computational cost to scan entire image and find ship regions. Principal Component Analysis (PCA) is applied to STHOG feature to compress the dimension. In the computer simulations, the ship detection performance of the proposed method was evaluated. From the simulation results, our proposed method exhibited better results than ship detector based on PCA+HOG feature.",
author = "Satoru Suzuki and Yasue Mitsukura and Tadasuke Furuya",
year = "2014",
month = "1",
day = "22",
doi = "10.1109/MECATRONICS.2014.7018610",
language = "English",
isbn = "9781479957170",
pages = "93--98",
booktitle = "10th France-Japan Congress, 8th Europe-Asia Congress on Mecatronics, MECATRONICS 2014",
publisher = "Institute of Electrical and Electronics Engineers Inc.",

}

TY - GEN

T1 - Ship detection based on spatio-temporal features

AU - Suzuki, Satoru

AU - Mitsukura, Yasue

AU - Furuya, Tadasuke

PY - 2014/1/22

Y1 - 2014/1/22

N2 - The paper proposes the ship detection method based on Spatio-temporal Histograms of Oriented Gradients (STHOG) feature and Support Vector Machine (SVM). STHOG feature, which is the extension version of HOG feature, enables extract spatial and temporal features of an object. The ship detector based on HOG feature can wrongly detect the similar shape objects with ships. On the other hand, the ship detector based on STHOG feature can identify them successfully by utilizing temporal feature of an object. To extract temporal feature of an object, image registration is implemented and an image displacement by camera motion is corrected. Due to high dimensionality of STHOG feature, it requires high computational cost to scan entire image and find ship regions. Principal Component Analysis (PCA) is applied to STHOG feature to compress the dimension. In the computer simulations, the ship detection performance of the proposed method was evaluated. From the simulation results, our proposed method exhibited better results than ship detector based on PCA+HOG feature.

AB - The paper proposes the ship detection method based on Spatio-temporal Histograms of Oriented Gradients (STHOG) feature and Support Vector Machine (SVM). STHOG feature, which is the extension version of HOG feature, enables extract spatial and temporal features of an object. The ship detector based on HOG feature can wrongly detect the similar shape objects with ships. On the other hand, the ship detector based on STHOG feature can identify them successfully by utilizing temporal feature of an object. To extract temporal feature of an object, image registration is implemented and an image displacement by camera motion is corrected. Due to high dimensionality of STHOG feature, it requires high computational cost to scan entire image and find ship regions. Principal Component Analysis (PCA) is applied to STHOG feature to compress the dimension. In the computer simulations, the ship detection performance of the proposed method was evaluated. From the simulation results, our proposed method exhibited better results than ship detector based on PCA+HOG feature.

UR - http://www.scopus.com/inward/record.url?scp=84949922983&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84949922983&partnerID=8YFLogxK

U2 - 10.1109/MECATRONICS.2014.7018610

DO - 10.1109/MECATRONICS.2014.7018610

M3 - Conference contribution

AN - SCOPUS:84949922983

SN - 9781479957170

SP - 93

EP - 98

BT - 10th France-Japan Congress, 8th Europe-Asia Congress on Mecatronics, MECATRONICS 2014

PB - Institute of Electrical and Electronics Engineers Inc.

ER -