Publication
Driver drowsiness detection: a comparison between intrusive and non-intrusive signal acquisition methods
| dc.contributor.author | Oliveira, Licínio | |
| dc.contributor.author | Cardoso, Jaime | |
| dc.contributor.author | Lourenço, André | |
| dc.contributor.author | Ahlstrom, Christer | |
| dc.date.accessioned | 2019-04-16T10:10:24Z | |
| dc.date.available | 2019-04-16T10:10:24Z | |
| dc.date.issued | 2018 | |
| dc.description.abstract | Driver drowsiness is a major cause of road accidents, many of which result in fatalities. A solution to this problem is the inclusion of a drowsiness detector in vehicles to alert the driver if sleepiness is detected. To detect drowsiness, physiologic, behavioral (visual) and vehicle-based methods can be used, however, only measures that can be acquired non-intrusively are viable in a real life application. This work uses data from a real-road experiment with sleep deprived drivers to compare the performance of driver drowsiness detection using intrusive acquisition methods, namely electrooculogram (EOG), with camera based, non-intrusive, methods. A hybrid strategy, combining the described methods with electrocardiogram (ECG) measures, is also evaluated. Overall, the obtained results show that drowsiness detection performance is similar using non-intrusive camera based measures or intrusive EOG measures. The detection performance increases when combining two methods (ECG + visual) or (ECG + EOG). | pt_PT |
| dc.description.version | info:eu-repo/semantics/publishedVersion | pt_PT |
| dc.identifier.citation | OLIVEIRA, Licínio; [et al] – Driver drowsiness detection: a comparison between intrusive and non-intrusive signal acquisition methods. In Proceedings of the 2018 7th European Workshop on Visual Information Processing (EUVIP). Tampere, Finland: IEEE, 2018. ISSN 2164-974X. Pp. 1-6 | pt_PT |
| dc.identifier.issn | 2164-974X | |
| dc.identifier.issn | 2471-8963 | |
| dc.identifier.uri | http://hdl.handle.net/10400.21/9870 | |
| dc.language.iso | eng | pt_PT |
| dc.publisher | Institute of Electrical and Electronics Engineers | pt_PT |
| dc.relation | POCI-01-0145-FEDER-030707 - FCT | pt_PT |
| dc.relation | 688900 - European Unions Horizon 2020 research and innovation program | pt_PT |
| dc.subject | Driver drowsiness | pt_PT |
| dc.subject | Camera-based methods | pt_PT |
| dc.subject | ECG | pt_PT |
| dc.subject | EOG | pt_PT |
| dc.title | Driver drowsiness detection: a comparison between intrusive and non-intrusive signal acquisition methods | pt_PT |
| dc.type | conference object | |
| dspace.entity.type | Publication | |
| oaire.citation.conferencePlace | Nov 26-28, 2018 - Tampere, Finland | pt_PT |
| oaire.citation.endPage | 6 | pt_PT |
| oaire.citation.startPage | 1 | pt_PT |
| oaire.citation.title | 7th European Workshop on Visual Information Processing (EUVIP) | pt_PT |
| person.familyName | Cardoso | |
| person.familyName | Lourenço | |
| person.givenName | Jaime | |
| person.givenName | André | |
| person.identifier | R-000-6H2 | |
| person.identifier.ciencia-id | 6017-2B87-B242 | |
| person.identifier.orcid | 0000-0002-3760-2473 | |
| person.identifier.orcid | 0000-0001-8935-9578 | |
| person.identifier.rid | I-3286-2013 | |
| person.identifier.scopus-author-id | 9245302400 | |
| rcaap.rights | openAccess | pt_PT |
| rcaap.type | conferenceObject | pt_PT |
| relation.isAuthorOfPublication | e2f2c998-9a12-4af9-ad3a-fe57c4f7d951 | |
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