Nighttime pedestrian detection using thermal imaging based on HOG feature

Shyang Lih Chang; Fu Tzu Yang; Wen Po Wu; Yu An Cho; Sei Wang Chen

doi:10.1109/ICSSE.2011.5961992

Nighttime pedestrian detection using thermal imaging based on HOG feature

Shyang Lih Chang^*, Fu Tzu Yang, Wen Po Wu, Yu An Cho, Sei Wang Chen

^*Corresponding author for this work

Department of Computer Science and Information Engineering

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

25 Citations (Scopus)

Abstract

This research focuses on pedestrian detection using infrared thermal imager. The purpose is to locate the pedestrians from studying thermal imagery. Based on HOG (Histograms of Oriented Gradients), Adaboost algorithm is used as a way to perform the detection. The system is divided into three sections, to extract the features of the pedestrians, to train the Adaboost classifier, and to detect the pedestrian. To get the features of the pedestrians, data is gathered from inserted images. The features allow the detection to work well. The feature extraction includes image segmentation, ROI selection, and feature extraction. We have successfully located the positions of the pedestrians with the methods mentioned above. This can be applied to the development of the intelligent driver assistance system, giving more road traffic situations to the drivers throughout the night.

Original language	English
Title of host publication	Proceedings 2011 International Conference on System Science and Engineering, ICSSE 2011
Pages	694-698
Number of pages	5
DOIs	https://doi.org/10.1109/ICSSE.2011.5961992
Publication status	Published - 2011
Event	2011 International Conference on System Science and Engineering, ICSSE 2011 - Macao, China Duration: 2011 Jun 8 → 2011 Jun 10

Publication series

Name	Proceedings 2011 International Conference on System Science and Engineering, ICSSE 2011

Other

Other	2011 International Conference on System Science and Engineering, ICSSE 2011
Country/Territory	China
City	Macao
Period	2011/06/08 → 2011/06/10

Keywords

Adaboost
HOG
ROI
pedestrian detection

ASJC Scopus subject areas

Control and Systems Engineering

Access to Document

10.1109/ICSSE.2011.5961992

Cite this

Chang, S. L., Yang, F. T., Wu, W. P., Cho, Y. A., & Chen, S. W. (2011). Nighttime pedestrian detection using thermal imaging based on HOG feature. In Proceedings 2011 International Conference on System Science and Engineering, ICSSE 2011 (pp. 694-698). Article 5961992 (Proceedings 2011 International Conference on System Science and Engineering, ICSSE 2011). https://doi.org/10.1109/ICSSE.2011.5961992

Nighttime pedestrian detection using thermal imaging based on HOG feature. / Chang, Shyang Lih; Yang, Fu Tzu; Wu, Wen Po et al.
Proceedings 2011 International Conference on System Science and Engineering, ICSSE 2011. 2011. p. 694-698 5961992 (Proceedings 2011 International Conference on System Science and Engineering, ICSSE 2011).

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

Chang, SL, Yang, FT, Wu, WP, Cho, YA & Chen, SW 2011, Nighttime pedestrian detection using thermal imaging based on HOG feature. in Proceedings 2011 International Conference on System Science and Engineering, ICSSE 2011., 5961992, Proceedings 2011 International Conference on System Science and Engineering, ICSSE 2011, pp. 694-698, 2011 International Conference on System Science and Engineering, ICSSE 2011, Macao, China, 2011/06/08. https://doi.org/10.1109/ICSSE.2011.5961992

@inproceedings{4399456bd4d24658a26f965ae33c172c,

title = "Nighttime pedestrian detection using thermal imaging based on HOG feature",

abstract = "This research focuses on pedestrian detection using infrared thermal imager. The purpose is to locate the pedestrians from studying thermal imagery. Based on HOG (Histograms of Oriented Gradients), Adaboost algorithm is used as a way to perform the detection. The system is divided into three sections, to extract the features of the pedestrians, to train the Adaboost classifier, and to detect the pedestrian. To get the features of the pedestrians, data is gathered from inserted images. The features allow the detection to work well. The feature extraction includes image segmentation, ROI selection, and feature extraction. We have successfully located the positions of the pedestrians with the methods mentioned above. This can be applied to the development of the intelligent driver assistance system, giving more road traffic situations to the drivers throughout the night.",

keywords = "Adaboost, HOG, ROI, pedestrian detection",

author = "Chang, {Shyang Lih} and Yang, {Fu Tzu} and Wu, {Wen Po} and Cho, {Yu An} and Chen, {Sei Wang}",

year = "2011",

doi = "10.1109/ICSSE.2011.5961992",

language = "English",

isbn = "9781612844718",

series = "Proceedings 2011 International Conference on System Science and Engineering, ICSSE 2011",

pages = "694--698",

booktitle = "Proceedings 2011 International Conference on System Science and Engineering, ICSSE 2011",

note = "2011 International Conference on System Science and Engineering, ICSSE 2011 ; Conference date: 08-06-2011 Through 10-06-2011",

}

TY - GEN

T1 - Nighttime pedestrian detection using thermal imaging based on HOG feature

AU - Chang, Shyang Lih

AU - Yang, Fu Tzu

AU - Wu, Wen Po

AU - Cho, Yu An

AU - Chen, Sei Wang

PY - 2011

Y1 - 2011

N2 - This research focuses on pedestrian detection using infrared thermal imager. The purpose is to locate the pedestrians from studying thermal imagery. Based on HOG (Histograms of Oriented Gradients), Adaboost algorithm is used as a way to perform the detection. The system is divided into three sections, to extract the features of the pedestrians, to train the Adaboost classifier, and to detect the pedestrian. To get the features of the pedestrians, data is gathered from inserted images. The features allow the detection to work well. The feature extraction includes image segmentation, ROI selection, and feature extraction. We have successfully located the positions of the pedestrians with the methods mentioned above. This can be applied to the development of the intelligent driver assistance system, giving more road traffic situations to the drivers throughout the night.

AB - This research focuses on pedestrian detection using infrared thermal imager. The purpose is to locate the pedestrians from studying thermal imagery. Based on HOG (Histograms of Oriented Gradients), Adaboost algorithm is used as a way to perform the detection. The system is divided into three sections, to extract the features of the pedestrians, to train the Adaboost classifier, and to detect the pedestrian. To get the features of the pedestrians, data is gathered from inserted images. The features allow the detection to work well. The feature extraction includes image segmentation, ROI selection, and feature extraction. We have successfully located the positions of the pedestrians with the methods mentioned above. This can be applied to the development of the intelligent driver assistance system, giving more road traffic situations to the drivers throughout the night.

KW - Adaboost

KW - HOG

KW - ROI

KW - pedestrian detection

UR - http://www.scopus.com/inward/record.url?scp=84860404889&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84860404889&partnerID=8YFLogxK

U2 - 10.1109/ICSSE.2011.5961992

DO - 10.1109/ICSSE.2011.5961992

M3 - Conference contribution

AN - SCOPUS:84860404889

SN - 9781612844718

T3 - Proceedings 2011 International Conference on System Science and Engineering, ICSSE 2011

SP - 694

EP - 698

BT - Proceedings 2011 International Conference on System Science and Engineering, ICSSE 2011

T2 - 2011 International Conference on System Science and Engineering, ICSSE 2011

Y2 - 8 June 2011 through 10 June 2011

ER -

Nighttime pedestrian detection using thermal imaging based on HOG feature

Abstract

Publication series

Other

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this