Abnormal Driving Behavior Detection Using Sparse Representation

Chien Yu Chiou; Pau-Choo Chung; Chun Rong Huang; Ming Fang Chang

doi:10.1109/ICS.2016.0085

Abnormal Driving Behavior Detection Using Sparse Representation

Chien Yu Chiou, Pau-Choo Chung, Chun Rong Huang, Ming Fang Chang

Institute of Computer and Communication Engineering

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

4 Citations (Scopus)

Abstract

To reduce the chance of traffic crashes, many driver monitoring systems (DMSs) have been developed. A DMS warns the driver under abnormal driving conditions. However, traditional approaches require enumerating abnormal driving conditions. In this paper, we propose a novel DMS, which models the driver's normal driving statuses based on sparse reconstruction. The proposed DMS compares the driver's statuses with his/her personal normal driving status model and identifies abnormal driving statuses that greatly change the driver's appearances. The experimental results show good performance of the proposed DMS to detect variant abnormal driver conditions.

Original language	English
Title of host publication	Proceedings - 2016 International Computer Symposium, ICS 2016
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	390-395
Number of pages	6
ISBN (Electronic)	9781509034383
DOIs	https://doi.org/10.1109/ICS.2016.0085
Publication status	Published - 2017 Feb 16
Event	2016 International Computer Symposium, ICS 2016 - Chiayi, Taiwan Duration: 2016 Dec 15 → 2016 Dec 17

Publication series

Name	Proceedings - 2016 International Computer Symposium, ICS 2016

Other

Other	2016 International Computer Symposium, ICS 2016
Country	Taiwan
City	Chiayi
Period	16-12-15 → 16-12-17

All Science Journal Classification (ASJC) codes

Computer Vision and Pattern Recognition
Hardware and Architecture
Computer Networks and Communications
Computer Science Applications

Access to Document

10.1109/ICS.2016.0085

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Cite this

Chiou, C. Y., Chung, P-C., Huang, C. R., & Chang, M. F. (2017). Abnormal Driving Behavior Detection Using Sparse Representation. In Proceedings - 2016 International Computer Symposium, ICS 2016 (pp. 390-395). [7858507] (Proceedings - 2016 International Computer Symposium, ICS 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICS.2016.0085

@inproceedings{cfbb1a789e8648cd8861cd98db941ca8,

title = "Abnormal Driving Behavior Detection Using Sparse Representation",

abstract = "To reduce the chance of traffic crashes, many driver monitoring systems (DMSs) have been developed. A DMS warns the driver under abnormal driving conditions. However, traditional approaches require enumerating abnormal driving conditions. In this paper, we propose a novel DMS, which models the driver's normal driving statuses based on sparse reconstruction. The proposed DMS compares the driver's statuses with his/her personal normal driving status model and identifies abnormal driving statuses that greatly change the driver's appearances. The experimental results show good performance of the proposed DMS to detect variant abnormal driver conditions.",

author = "Chiou, {Chien Yu} and Pau-Choo Chung and Huang, {Chun Rong} and Chang, {Ming Fang}",

year = "2017",

month = feb,

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doi = "10.1109/ICS.2016.0085",

language = "English",

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

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booktitle = "Proceedings - 2016 International Computer Symposium, ICS 2016",

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note = "2016 International Computer Symposium, ICS 2016 ; Conference date: 15-12-2016 Through 17-12-2016",

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Chiou, CY, Chung, P-C, Huang, CR & Chang, MF 2017, Abnormal Driving Behavior Detection Using Sparse Representation. in Proceedings - 2016 International Computer Symposium, ICS 2016., 7858507, Proceedings - 2016 International Computer Symposium, ICS 2016, Institute of Electrical and Electronics Engineers Inc., pp. 390-395, 2016 International Computer Symposium, ICS 2016, Chiayi, Taiwan, 16-12-15. https://doi.org/10.1109/ICS.2016.0085

Abnormal Driving Behavior Detection Using Sparse Representation. / Chiou, Chien Yu; Chung, Pau-Choo; Huang, Chun Rong; Chang, Ming Fang.

Proceedings - 2016 International Computer Symposium, ICS 2016. Institute of Electrical and Electronics Engineers Inc., 2017. p. 390-395 7858507 (Proceedings - 2016 International Computer Symposium, ICS 2016).

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

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N2 - To reduce the chance of traffic crashes, many driver monitoring systems (DMSs) have been developed. A DMS warns the driver under abnormal driving conditions. However, traditional approaches require enumerating abnormal driving conditions. In this paper, we propose a novel DMS, which models the driver's normal driving statuses based on sparse reconstruction. The proposed DMS compares the driver's statuses with his/her personal normal driving status model and identifies abnormal driving statuses that greatly change the driver's appearances. The experimental results show good performance of the proposed DMS to detect variant abnormal driver conditions.

AB - To reduce the chance of traffic crashes, many driver monitoring systems (DMSs) have been developed. A DMS warns the driver under abnormal driving conditions. However, traditional approaches require enumerating abnormal driving conditions. In this paper, we propose a novel DMS, which models the driver's normal driving statuses based on sparse reconstruction. The proposed DMS compares the driver's statuses with his/her personal normal driving status model and identifies abnormal driving statuses that greatly change the driver's appearances. The experimental results show good performance of the proposed DMS to detect variant abnormal driver conditions.

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