Vision-based Detection of Mobile Device Use While Driving
The aim of this study was to explore the feasibility of an automatic vision-based solution to detect drivers using mobile devices while operating their vehicles. The proposed system comprises of modules for vehicle license plate localisation, driver’s face detection and mobile phone interaction. The...
| Main Author: | |
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| Format: | Thesis |
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Curtin University
2019
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| Online Access: | http://hdl.handle.net/20.500.11937/77108 |
| _version_ | 1848763817253666816 |
|---|---|
| author | Woo, Yew Meng |
| author_facet | Woo, Yew Meng |
| author_sort | Woo, Yew Meng |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | The aim of this study was to explore the feasibility of an automatic vision-based solution to detect drivers using mobile devices while operating their vehicles. The proposed system comprises of modules for vehicle license plate localisation, driver’s face detection and mobile phone interaction. The system were then implemented and systematically evaluated using suitable image datasets. The strengths and weaknesses of individual modules were analysed and further recommendations made to improve the overall system’s performance. |
| first_indexed | 2025-11-14T11:09:29Z |
| format | Thesis |
| id | curtin-20.500.11937-77108 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T11:09:29Z |
| publishDate | 2019 |
| publisher | Curtin University |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-771082019-12-06T00:31:30Z Vision-based Detection of Mobile Device Use While Driving Woo, Yew Meng The aim of this study was to explore the feasibility of an automatic vision-based solution to detect drivers using mobile devices while operating their vehicles. The proposed system comprises of modules for vehicle license plate localisation, driver’s face detection and mobile phone interaction. The system were then implemented and systematically evaluated using suitable image datasets. The strengths and weaknesses of individual modules were analysed and further recommendations made to improve the overall system’s performance. 2019 Thesis http://hdl.handle.net/20.500.11937/77108 Curtin University fulltext |
| spellingShingle | Woo, Yew Meng Vision-based Detection of Mobile Device Use While Driving |
| title | Vision-based Detection of Mobile Device Use While Driving |
| title_full | Vision-based Detection of Mobile Device Use While Driving |
| title_fullStr | Vision-based Detection of Mobile Device Use While Driving |
| title_full_unstemmed | Vision-based Detection of Mobile Device Use While Driving |
| title_short | Vision-based Detection of Mobile Device Use While Driving |
| title_sort | vision-based detection of mobile device use while driving |
| url | http://hdl.handle.net/20.500.11937/77108 |