Publication:
Driver Drowsiness Detection Using Eye-Closeness Detection

Simple item page
dc.contributor.authorOraan Khunpisuthen_US
dc.contributor.authorTaweechai Chotchinasrien_US
dc.contributor.authorVarakorn Koschakosaien_US
dc.contributor.authorNarit Hnoohomen_US
dc.contributor.otherMahidol Universityen_US
dc.date.accessioned2018-12-21T07:20:34Z
dc.date.accessioned2019-03-14T08:03:25Z
dc.date.available2018-12-21T07:20:34Z
dc.date.available2019-03-14T08:03:25Z
dc.date.issued2017-04-21en_US
dc.description.abstract© 2016 IEEE. The purpose of this paper was to devise a way to alert drowsy drivers in the act of driving. One of the causes of car accidents comes from drowsiness of the driver. Therefore, this study attempted to address the issue by creating an experiment in order to calculate the level of drowsiness. A requirement for this paper was the utilisation of a Raspberry Pi Camera and Raspberry Pi 3 module, which were able to calculate the level of drowsiness in drivers. The frequency of head tilting and blinking of the eyes was used to determine whether or not a driver felt drowsy. With an evaluation on ten volunteers, the accuracy of face and eye detection was up to 99.59 percent.en_US
dc.identifier.citationProceedings - 12th International Conference on Signal Image Technology and Internet-Based Systems, SITIS 2016. (2017), 661-668en_US
dc.identifier.doi10.1109/SITIS.2016.110en_US
dc.identifier.other2-s2.0-85019252594en_US
dc.identifier.urihttps://repository.li.mahidol.ac.th/handle/20.500.14594/42373
dc.rightsMahidol Universityen_US
dc.rights.holderSCOPUSen_US
dc.source.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85019252594&origin=inwarden_US
dc.subjectComputer Scienceen_US
dc.titleDriver Drowsiness Detection Using Eye-Closeness Detectionen_US
dc.typeConference Paperen_US
dspace.entity.typePublication
mu.datasource.scopushttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85019252594&origin=inwarden_US

Files

Collections

Scopus 2016-2017