Abnormal Driving Behavior Detection Using Sparse Representation

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

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

4 Citations (Scopus)


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 languageEnglish
Title of host publicationProceedings - 2016 International Computer Symposium, ICS 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
ISBN (Electronic)9781509034383
Publication statusPublished - 2017 Feb 16
Event2016 International Computer Symposium, ICS 2016 - Chiayi, Taiwan
Duration: 2016 Dec 152016 Dec 17

Publication series

NameProceedings - 2016 International Computer Symposium, ICS 2016


Other2016 International Computer Symposium, ICS 2016

All Science Journal Classification (ASJC) codes

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


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