Classification and tracking of large vehicles for night driving

Jiann Der Lee; Yong Sheng Chen; Jong Chih Chien

doi:10.1109/GCCE.2016.7800320

Classification and tracking of large vehicles for night driving

Jiann Der Lee, Yong Sheng Chen, Jong Chih Chien

Department of Electrical Engineering

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

1 Scopus citations

Abstract

Night driving is dangerous already, but when driving near a large vehicle, the danger multiplies. Because the attention of the driver at night could be distracted thus fail to pay attention to dangerously large vehicles, we propose a component for ADAS systems that will help alert the drivers to the presence of large vehicles. This component utilizes a combination of rear lights detector, LBP-based Adaboost classifier and a BOF classifier that uses patent-free feature extractors/descriptors to extract and verify the existence of large vehicles. The preliminary experimental results show that this combination of setup is feasible in achieving desired results.

Original language	English
Title of host publication	2016 IEEE 5th Global Conference on Consumer Electronics, GCCE 2016
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781509023332
DOIs	https://doi.org/10.1109/GCCE.2016.7800320
State	Published - 27 12 2016
Event	5th IEEE Global Conference on Consumer Electronics, GCCE 2016 - Kyoto, Japan Duration: 11 10 2016 → 14 10 2016

Publication series

Name	2016 IEEE 5th Global Conference on Consumer Electronics, GCCE 2016

Conference

Conference	5th IEEE Global Conference on Consumer Electronics, GCCE 2016
Country/Territory	Japan
City	Kyoto
Period	11/10/16 → 14/10/16

Bibliographical note

Publisher Copyright:
© 2016 IEEE.

Keywords

BOF
KAZE
ORB
night driving

Access to Document

10.1109/GCCE.2016.7800320

Cite this

@inproceedings{a98c4ad24a01484a90f035d3cb63a492,

title = "Classification and tracking of large vehicles for night driving",

abstract = "Night driving is dangerous already, but when driving near a large vehicle, the danger multiplies. Because the attention of the driver at night could be distracted thus fail to pay attention to dangerously large vehicles, we propose a component for ADAS systems that will help alert the drivers to the presence of large vehicles. This component utilizes a combination of rear lights detector, LBP-based Adaboost classifier and a BOF classifier that uses patent-free feature extractors/descriptors to extract and verify the existence of large vehicles. The preliminary experimental results show that this combination of setup is feasible in achieving desired results.",

keywords = "BOF, KAZE, ORB, night driving",

author = "Lee, {Jiann Der} and Chen, {Yong Sheng} and Chien, {Jong Chih}",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 5th IEEE Global Conference on Consumer Electronics, GCCE 2016 ; Conference date: 11-10-2016 Through 14-10-2016",

year = "2016",

month = dec,

day = "27",

doi = "10.1109/GCCE.2016.7800320",

language = "英语",

series = "2016 IEEE 5th Global Conference on Consumer Electronics, GCCE 2016",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "2016 IEEE 5th Global Conference on Consumer Electronics, GCCE 2016",

address = "美国",

}

Lee, JD, Chen, YS & Chien, JC 2016, Classification and tracking of large vehicles for night driving. in 2016 IEEE 5th Global Conference on Consumer Electronics, GCCE 2016., 7800320, 2016 IEEE 5th Global Conference on Consumer Electronics, GCCE 2016, Institute of Electrical and Electronics Engineers Inc., 5th IEEE Global Conference on Consumer Electronics, GCCE 2016, Kyoto, Japan, 11/10/16. https://doi.org/10.1109/GCCE.2016.7800320

Classification and tracking of large vehicles for night driving. / Lee, Jiann Der; Chen, Yong Sheng; Chien, Jong Chih.
2016 IEEE 5th Global Conference on Consumer Electronics, GCCE 2016. Institute of Electrical and Electronics Engineers Inc., 2016. 7800320 (2016 IEEE 5th Global Conference on Consumer Electronics, GCCE 2016).

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

TY - GEN

T1 - Classification and tracking of large vehicles for night driving

AU - Lee, Jiann Der

AU - Chen, Yong Sheng

AU - Chien, Jong Chih

PY - 2016/12/27

Y1 - 2016/12/27

N2 - Night driving is dangerous already, but when driving near a large vehicle, the danger multiplies. Because the attention of the driver at night could be distracted thus fail to pay attention to dangerously large vehicles, we propose a component for ADAS systems that will help alert the drivers to the presence of large vehicles. This component utilizes a combination of rear lights detector, LBP-based Adaboost classifier and a BOF classifier that uses patent-free feature extractors/descriptors to extract and verify the existence of large vehicles. The preliminary experimental results show that this combination of setup is feasible in achieving desired results.

AB - Night driving is dangerous already, but when driving near a large vehicle, the danger multiplies. Because the attention of the driver at night could be distracted thus fail to pay attention to dangerously large vehicles, we propose a component for ADAS systems that will help alert the drivers to the presence of large vehicles. This component utilizes a combination of rear lights detector, LBP-based Adaboost classifier and a BOF classifier that uses patent-free feature extractors/descriptors to extract and verify the existence of large vehicles. The preliminary experimental results show that this combination of setup is feasible in achieving desired results.

KW - BOF

KW - KAZE

KW - ORB

KW - night driving

UR - http://www.scopus.com/inward/record.url?scp=85010282168&partnerID=8YFLogxK

U2 - 10.1109/GCCE.2016.7800320

DO - 10.1109/GCCE.2016.7800320

M3 - 会议稿件

AN - SCOPUS:85010282168

T3 - 2016 IEEE 5th Global Conference on Consumer Electronics, GCCE 2016

BT - 2016 IEEE 5th Global Conference on Consumer Electronics, GCCE 2016

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 5th IEEE Global Conference on Consumer Electronics, GCCE 2016

Y2 - 11 October 2016 through 14 October 2016

ER -

Classification and tracking of large vehicles for night driving

Abstract

Publication series

Conference

Bibliographical note

Keywords

Access to Document

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