Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 정호기 | - |
dc.date.accessioned | 2018-02-06T05:20:39Z | - |
dc.date.available | 2018-02-06T05:20:39Z | - |
dc.date.issued | 2011-03 | - |
dc.identifier.citation | IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS,Vol.12 No.1 [2011],254-267 | en_US |
dc.identifier.issn | 1524-9050 | - |
dc.identifier.uri | http://ieeexplore.ieee.org/document/5688323/ | - |
dc.description.abstract | This paper presents a vision-based real-time gaze zone estimator based on a driver's head orientation composed of yaw and pitch. Generally, vision-based methods are vulnerable to the wearing of eyeglasses and image variations between day and night. The proposed method is novel in the following four ways: First, the proposed method can work under both day and night conditions and is robust to facial image variation caused by eyeglasses because it only requires simple facial features and not specific features such as eyes, lip corners, and facial contours. Second, an ellipsoidal face model is proposed instead of a cylindrical face model to exactly determine a driver's yaw. Third, we propose new features-the normalized mean and the standard deviation of the horizontal edge projection histogram-to reliably and rapidly estimate a driver's pitch. Fourth, the proposed method obtains an accurate gaze zone by using a support vector machine. Experimental results from 200 000 images showed that the root mean square errors of the estimated yaw and pitch angles are below 7 under both daylight and nighttime conditions. Equivalent results were obtained for drivers with glasses or sunglasses, and 18 gaze zones were accurately estimated using the proposed gaze estimation method. | en_US |
dc.description.sponsorship | This work was supported in part by Mando Corporation Ltd. and in part by the National Research Foundation of Korea through the Biometrics Engineering Research Center, Yonsei University, under Grant R112002105070030(2010). The Associate Editor for this paper was A. Amditis. | en_US |
dc.language.iso | en | en_US |
dc.publisher | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 445 HOES LANE, PISCATAWAY, NJ 08855-4141 USA | en_US |
dc.subject | Driver monitoring system | en_US |
dc.subject | forward collision warning (FCW) system | en_US |
dc.subject | gaze estimation | en_US |
dc.subject | head orientation estimation | en_US |
dc.subject | precrash system | en_US |
dc.title | Real-Time Gaze Estimator Based on Driver's Head Orientation for Forward Collision Warning System | en_US |
dc.type | Article | en_US |
dc.relation.no | 1 | - |
dc.relation.volume | 12 | - |
dc.identifier.doi | 10.1109/TITS.2010.2091503 | - |
dc.relation.page | 254-267 | - |
dc.relation.journal | IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS | - |
dc.contributor.googleauthor | Lee, S. J. | - |
dc.contributor.googleauthor | Jo, J. | - |
dc.contributor.googleauthor | Jung, H. G. | - |
dc.contributor.googleauthor | Park, K. R. | - |
dc.contributor.googleauthor | Kim, J. | - |
dc.relation.code | 2011214110 | - |
dc.sector.campus | S | - |
dc.sector.daehak | COLLEGE OF ENGINEERING[S] | - |
dc.sector.department | DEPARTMENT OF AUTOMOTIVE ENGINEERING | - |
dc.identifier.pid | hogijung | - |
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