Proposing a fast circular HOG descriptor for detecting rotated objects

Junhyuk Hyun, Jeonghyun Baek, Jisu Kim, Peyman Hosseinzajeh Kassani, Euntai Kim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Object detection is one of the most interesting branches in computer vision. Accurate detection systems can be utilized to various areas. There are two steps in detection, feature extraction and classification. In this paper, new feature extraction method is proposed. Histogram Oriented Gradient (HOG) is famous, fast and accurate feature, but it is not rotation invariant. This paper proposes a new shape of HOG for fast detection of rotated objects. The proposed method is faster than conventional method in rotational object detection.

Original languageEnglish
Title of host publication2015 International Joint Conference on Neural Networks, IJCNN 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Volume2015-September
ISBN (Electronic)9781479919604, 9781479919604, 9781479919604, 9781479919604
DOIs
Publication statusPublished - 2015 Sep 28
EventInternational Joint Conference on Neural Networks, IJCNN 2015 - Killarney, Ireland
Duration: 2015 Jul 122015 Jul 17

Other

OtherInternational Joint Conference on Neural Networks, IJCNN 2015
CountryIreland
CityKillarney
Period15/7/1215/7/17

Fingerprint

Feature extraction
Computer vision
Object detection

All Science Journal Classification (ASJC) codes

  • Software
  • Artificial Intelligence

Cite this

Hyun, J., Baek, J., Kim, J., Kassani, P. H., & Kim, E. (2015). Proposing a fast circular HOG descriptor for detecting rotated objects. In 2015 International Joint Conference on Neural Networks, IJCNN 2015 (Vol. 2015-September). [7280501] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IJCNN.2015.7280501
Hyun, Junhyuk ; Baek, Jeonghyun ; Kim, Jisu ; Kassani, Peyman Hosseinzajeh ; Kim, Euntai. / Proposing a fast circular HOG descriptor for detecting rotated objects. 2015 International Joint Conference on Neural Networks, IJCNN 2015. Vol. 2015-September Institute of Electrical and Electronics Engineers Inc., 2015.
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abstract = "Object detection is one of the most interesting branches in computer vision. Accurate detection systems can be utilized to various areas. There are two steps in detection, feature extraction and classification. In this paper, new feature extraction method is proposed. Histogram Oriented Gradient (HOG) is famous, fast and accurate feature, but it is not rotation invariant. This paper proposes a new shape of HOG for fast detection of rotated objects. The proposed method is faster than conventional method in rotational object detection.",
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Hyun, J, Baek, J, Kim, J, Kassani, PH & Kim, E 2015, Proposing a fast circular HOG descriptor for detecting rotated objects. in 2015 International Joint Conference on Neural Networks, IJCNN 2015. vol. 2015-September, 7280501, Institute of Electrical and Electronics Engineers Inc., International Joint Conference on Neural Networks, IJCNN 2015, Killarney, Ireland, 15/7/12. https://doi.org/10.1109/IJCNN.2015.7280501

Proposing a fast circular HOG descriptor for detecting rotated objects. / Hyun, Junhyuk; Baek, Jeonghyun; Kim, Jisu; Kassani, Peyman Hosseinzajeh; Kim, Euntai.

2015 International Joint Conference on Neural Networks, IJCNN 2015. Vol. 2015-September Institute of Electrical and Electronics Engineers Inc., 2015. 7280501.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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AU - Kassani, Peyman Hosseinzajeh

AU - Kim, Euntai

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N2 - Object detection is one of the most interesting branches in computer vision. Accurate detection systems can be utilized to various areas. There are two steps in detection, feature extraction and classification. In this paper, new feature extraction method is proposed. Histogram Oriented Gradient (HOG) is famous, fast and accurate feature, but it is not rotation invariant. This paper proposes a new shape of HOG for fast detection of rotated objects. The proposed method is faster than conventional method in rotational object detection.

AB - Object detection is one of the most interesting branches in computer vision. Accurate detection systems can be utilized to various areas. There are two steps in detection, feature extraction and classification. In this paper, new feature extraction method is proposed. Histogram Oriented Gradient (HOG) is famous, fast and accurate feature, but it is not rotation invariant. This paper proposes a new shape of HOG for fast detection of rotated objects. The proposed method is faster than conventional method in rotational object detection.

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Hyun J, Baek J, Kim J, Kassani PH, Kim E. Proposing a fast circular HOG descriptor for detecting rotated objects. In 2015 International Joint Conference on Neural Networks, IJCNN 2015. Vol. 2015-September. Institute of Electrical and Electronics Engineers Inc. 2015. 7280501 https://doi.org/10.1109/IJCNN.2015.7280501