{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,30]],"date-time":"2026-03-30T21:43:43Z","timestamp":1774907023646,"version":"3.50.1"},"reference-count":23,"publisher":"Wiley","license":[{"start":{"date-parts":[[2020,11,28]],"date-time":"2020-11-28T00:00:00Z","timestamp":1606521600000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["51874300"],"award-info":[{"award-number":["51874300"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61976217"],"award-info":[{"award-number":["61976217"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["KC18082"],"award-info":[{"award-number":["KC18082"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Xuzhou Key R&D Program","award":["51874300"],"award-info":[{"award-number":["51874300"]}]},{"name":"Xuzhou Key R&D Program","award":["61976217"],"award-info":[{"award-number":["61976217"]}]},{"name":"Xuzhou Key R&D Program","award":["KC18082"],"award-info":[{"award-number":["KC18082"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Computational Intelligence and Neuroscience"],"published-print":{"date-parts":[[2020,11,28]]},"abstract":"<jats:p>In view of the fact that the detection of driver\u2019s distraction is a burning issue, this study chooses the driver\u2019s head pose as the evaluation parameter for driving distraction and proposes a driver distraction method based on the head pose. The effects of single regression and classification combined with regression are compared in terms of accuracy, and four kinds of classical networks are improved and trained using 300W-LP and AFLW datasets. The HPE_Resnet50 with the best accuracy is selected as the head pose estimator and applied to the ten-category distracted driving dataset SF3D to obtain 20,000 sets of head pose data. The differences between classes are discussed qualitatively and quantitatively. The analysis of variance shows that there is a statistically significant difference in head posture between safe driving and all kinds of distracted driving at 95% and 90% confidence levels, and the postures of all kinds of driving movements are distributed in a specific Euler angle range, which provides a characteristic basis for the design of subsequent recognition methods. In addition, according to the continuity of human movement, this paper also selects 90 drivers\u2019 videos to analyze the difference in head pose between safe driving and distracted driving frame by frame. By calculating the spatial distance and sample statistics, the results provide the reference point, spatial range, and threshold of safe driving under this driving condition. Experimental results show that the average error of HPE_Resnet50 in AFLW2000 is 6.17\u00b0 and that there is an average difference of 12.4\u00b0 to 54.9\u00b0 in the Euler angle between safe driving and nine kinds of distracted driving on SF3D.<\/jats:p>","DOI":"10.1155\/2020\/9606908","type":"journal-article","created":{"date-parts":[[2020,11,29]],"date-time":"2020-11-29T20:20:09Z","timestamp":1606681209000},"page":"1-10","source":"Crossref","is-referenced-by-count":32,"title":["Driver Distraction Detection Method Based on Continuous Head Pose Estimation"],"prefix":"10.1155","volume":"2020","author":[{"given":"Zuopeng","family":"Zhao","sequence":"first","affiliation":[{"name":"1School of Computer Science and Technology & Mine Digitization Engineering Research Center of Ministry of Education of the \u2009People\u2019s Republic of China, China University of Mining and Technology, Xuzhou 221116, China"},{"name":"School of Computer Science and Technology, China University of Mining and Technology, Xuzhou 221116, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4781-5720","authenticated-orcid":true,"given":"Sili","family":"Xia","sequence":"additional","affiliation":[{"name":"1School of Computer Science and Technology & Mine Digitization Engineering Research Center of Ministry of Education of the \u2009People\u2019s Republic of China, China University of Mining and Technology, Xuzhou 221116, China"},{"name":"School of Computer Science and Technology, China University of Mining and Technology, Xuzhou 221116, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xinzheng","family":"Xu","sequence":"additional","affiliation":[{"name":"1School of Computer Science and Technology & Mine Digitization Engineering Research Center of Ministry of Education of the \u2009People\u2019s Republic of China, China University of Mining and Technology, Xuzhou 221116, China"},{"name":"School of Computer Science and Technology, China University of Mining and Technology, Xuzhou 221116, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lan","family":"Zhang","sequence":"additional","affiliation":[{"name":"1School of Computer Science and Technology & Mine Digitization Engineering Research Center of Ministry of Education of the \u2009People\u2019s Republic of China, China University of Mining and Technology, Xuzhou 221116, China"},{"name":"School of Computer Science and Technology, China University of Mining and Technology, Xuzhou 221116, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hualin","family":"Yan","sequence":"additional","affiliation":[{"name":"1School of Computer Science and Technology & Mine Digitization Engineering Research Center of Ministry of Education of the \u2009People\u2019s Republic of China, China University of Mining and Technology, Xuzhou 221116, China"},{"name":"School of Computer Science and Technology, China University of Mining and Technology, Xuzhou 221116, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yi","family":"Xu","sequence":"additional","affiliation":[{"name":"1School of Computer Science and Technology & Mine Digitization Engineering Research Center of Ministry of Education of the \u2009People\u2019s Republic of China, China University of Mining and Technology, Xuzhou 221116, China"},{"name":"School of Computer Science and Technology, China University of Mining and Technology, Xuzhou 221116, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7320-0669","authenticated-orcid":true,"given":"Zhongxin","family":"Zhang","sequence":"additional","affiliation":[{"name":"1School of Computer Science and Technology & Mine Digitization Engineering Research Center of Ministry of Education of the \u2009People\u2019s Republic of China, China University of Mining and Technology, Xuzhou 221116, China"},{"name":"School of Computer Science and Technology, China University of Mining and Technology, Xuzhou 221116, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","reference":[{"key":"1","doi-asserted-by":"publisher","DOI":"10.1518\/001872008x288376"},{"key":"2","first-page":"709","article-title":"Head pose estimation for driver assistance systems: a robust algorithm and experimental evaluation","author":"E. 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