Detecting Driver Fatigue With Eye Blink Behavior
Traffic accidents, causing millions of deaths and billions of dollars in economic losses each year globally, have become a significant issue. One of the main causes of these accidents is drivers being sleepy or fatigued. Recently, various studies have focused on detecting drivers' sleep/wake st...
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| creator | Akin, Ali Kalkan, Habil |
| description | Traffic accidents, causing millions of deaths and billions of dollars in
economic losses each year globally, have become a significant issue. One of the
main causes of these accidents is drivers being sleepy or fatigued. Recently,
various studies have focused on detecting drivers' sleep/wake states using
camera-based solutions that do not require physical contact with the driver,
thereby enhancing ease of use. In this study, besides the eye blink frequency,
a driver adaptive eye blink behavior feature set have been evaluated to detect
the fatigue status. It is observed from the results that behavior of eye blink
carries useful information on fatigue detection. The developed image-based
system provides a solution that can work adaptively to the physical
characteristics of the drivers and their positions in the vehicle |
| doi_str_mv | 10.48550/arxiv.2407.02222 |
| format | Article |
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economic losses each year globally, have become a significant issue. One of the
main causes of these accidents is drivers being sleepy or fatigued. Recently,
various studies have focused on detecting drivers' sleep/wake states using
camera-based solutions that do not require physical contact with the driver,
thereby enhancing ease of use. In this study, besides the eye blink frequency,
a driver adaptive eye blink behavior feature set have been evaluated to detect
the fatigue status. It is observed from the results that behavior of eye blink
carries useful information on fatigue detection. The developed image-based
system provides a solution that can work adaptively to the physical
characteristics of the drivers and their positions in the vehicle</description><identifier>DOI: 10.48550/arxiv.2407.02222</identifier><language>eng</language><subject>Computer Science - Computer Vision and Pattern Recognition</subject><creationdate>2024-07</creationdate><rights>http://creativecommons.org/licenses/by/4.0</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>228,230,776,881</link.rule.ids><linktorsrc>$$Uhttps://arxiv.org/abs/2407.02222$$EView_record_in_Cornell_University$$FView_record_in_$$GCornell_University$$Hfree_for_read</linktorsrc><backlink>$$Uhttps://doi.org/10.48550/arXiv.2407.02222$$DView paper in arXiv$$Hfree_for_read</backlink></links><search><creatorcontrib>Akin, Ali</creatorcontrib><creatorcontrib>Kalkan, Habil</creatorcontrib><title>Detecting Driver Fatigue With Eye Blink Behavior</title><description>Traffic accidents, causing millions of deaths and billions of dollars in
economic losses each year globally, have become a significant issue. One of the
main causes of these accidents is drivers being sleepy or fatigued. Recently,
various studies have focused on detecting drivers' sleep/wake states using
camera-based solutions that do not require physical contact with the driver,
thereby enhancing ease of use. In this study, besides the eye blink frequency,
a driver adaptive eye blink behavior feature set have been evaluated to detect
the fatigue status. It is observed from the results that behavior of eye blink
carries useful information on fatigue detection. The developed image-based
system provides a solution that can work adaptively to the physical
characteristics of the drivers and their positions in the vehicle</description><subject>Computer Science - Computer Vision and Pattern Recognition</subject><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>GOX</sourceid><recordid>eNpjYJA0NNAzsTA1NdBPLKrILNMzMjEw1zMwAgJOBgOX1JLU5JLMvHQFl6LMstQiBbfEksz00lSF8MySDAXXylQFp5zMvGwFp9SMxLLM_CIeBta0xJziVF4ozc0g7-Ya4uyhCzY7vqAoMzexqDIeZEc82A5jwioAAVcwCg</recordid><startdate>20240702</startdate><enddate>20240702</enddate><creator>Akin, Ali</creator><creator>Kalkan, Habil</creator><scope>AKY</scope><scope>GOX</scope></search><sort><creationdate>20240702</creationdate><title>Detecting Driver Fatigue With Eye Blink Behavior</title><author>Akin, Ali ; Kalkan, Habil</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-arxiv_primary_2407_022223</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Computer Science - Computer Vision and Pattern Recognition</topic><toplevel>online_resources</toplevel><creatorcontrib>Akin, Ali</creatorcontrib><creatorcontrib>Kalkan, Habil</creatorcontrib><collection>arXiv Computer Science</collection><collection>arXiv.org</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Akin, Ali</au><au>Kalkan, Habil</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Detecting Driver Fatigue With Eye Blink Behavior</atitle><date>2024-07-02</date><risdate>2024</risdate><abstract>Traffic accidents, causing millions of deaths and billions of dollars in
economic losses each year globally, have become a significant issue. One of the
main causes of these accidents is drivers being sleepy or fatigued. Recently,
various studies have focused on detecting drivers' sleep/wake states using
camera-based solutions that do not require physical contact with the driver,
thereby enhancing ease of use. In this study, besides the eye blink frequency,
a driver adaptive eye blink behavior feature set have been evaluated to detect
the fatigue status. It is observed from the results that behavior of eye blink
carries useful information on fatigue detection. The developed image-based
system provides a solution that can work adaptively to the physical
characteristics of the drivers and their positions in the vehicle</abstract><doi>10.48550/arxiv.2407.02222</doi><oa>free_for_read</oa></addata></record> |
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| subjects | Computer Science - Computer Vision and Pattern Recognition |
| title | Detecting Driver Fatigue With Eye Blink Behavior |
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