Dual-Cameras-Based Driver’s Eye Gaze Tracking System with Non-Linear Gaze Point Refinement
The human eye gaze plays a vital role in monitoring people’s attention, and various efforts have been made to improve in-vehicle driver gaze tracking systems. Most of them build the specific gaze estimation model by pre-annotated data training in an offline way. These systems usually tend to have po...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-03-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/22/6/2326 |
| _version_ | 1797442328570363904 |
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| author | Yafei Wang Xueyan Ding Guoliang Yuan Xianping Fu |
| author_facet | Yafei Wang Xueyan Ding Guoliang Yuan Xianping Fu |
| author_sort | Yafei Wang |
| collection | DOAJ |
| description | The human eye gaze plays a vital role in monitoring people’s attention, and various efforts have been made to improve in-vehicle driver gaze tracking systems. Most of them build the specific gaze estimation model by pre-annotated data training in an offline way. These systems usually tend to have poor generalization performance during the online gaze prediction, which is caused by the estimation bias between the training domain and the deployment domain, making the predicted gaze points shift from their correct location. To solve this problem, a novel driver’s eye gaze tracking method with non-linear gaze point refinement is proposed in a monitoring system using two cameras, which eliminates the estimation bias and implicitly fine-tunes the gaze points. Supported by the two-stage gaze point clustering algorithm, the non-linear gaze point refinement method can gradually extract the representative gaze points of the forward and mirror gaze zone and establish the non-linear gaze point re-mapping relationship. In addition, the Unscented Kalman filter is utilized to track the driver’s continuous status features. Experimental results show that the non-linear gaze point refinement method outperforms several previous gaze calibration and gaze mapping methods, and improves the gaze estimation accuracy even on the cross-subject evaluation. The system can be used for predicting the driver’s attention. |
| first_indexed | 2024-03-09T12:40:14Z |
| format | Article |
| id | doaj.art-db37ff956f1b4caaaf7ee66dfcd4975a |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T12:40:14Z |
| publishDate | 2022-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-db37ff956f1b4caaaf7ee66dfcd4975a2023-11-30T22:19:26ZengMDPI AGSensors1424-82202022-03-01226232610.3390/s22062326Dual-Cameras-Based Driver’s Eye Gaze Tracking System with Non-Linear Gaze Point RefinementYafei Wang0Xueyan Ding1Guoliang Yuan2Xianping Fu3School of Information Science and Technology, Dalian Maritime University, Dalian 116026, ChinaSchool of Information Science and Technology, Dalian Maritime University, Dalian 116026, ChinaSchool of Information Science and Technology, Dalian Maritime University, Dalian 116026, ChinaSchool of Information Science and Technology, Dalian Maritime University, Dalian 116026, ChinaThe human eye gaze plays a vital role in monitoring people’s attention, and various efforts have been made to improve in-vehicle driver gaze tracking systems. Most of them build the specific gaze estimation model by pre-annotated data training in an offline way. These systems usually tend to have poor generalization performance during the online gaze prediction, which is caused by the estimation bias between the training domain and the deployment domain, making the predicted gaze points shift from their correct location. To solve this problem, a novel driver’s eye gaze tracking method with non-linear gaze point refinement is proposed in a monitoring system using two cameras, which eliminates the estimation bias and implicitly fine-tunes the gaze points. Supported by the two-stage gaze point clustering algorithm, the non-linear gaze point refinement method can gradually extract the representative gaze points of the forward and mirror gaze zone and establish the non-linear gaze point re-mapping relationship. In addition, the Unscented Kalman filter is utilized to track the driver’s continuous status features. Experimental results show that the non-linear gaze point refinement method outperforms several previous gaze calibration and gaze mapping methods, and improves the gaze estimation accuracy even on the cross-subject evaluation. The system can be used for predicting the driver’s attention.https://www.mdpi.com/1424-8220/22/6/2326driving environmentgaze trackingnon-linear refinement |
| spellingShingle | Yafei Wang Xueyan Ding Guoliang Yuan Xianping Fu Dual-Cameras-Based Driver’s Eye Gaze Tracking System with Non-Linear Gaze Point Refinement Sensors driving environment gaze tracking non-linear refinement |
| title | Dual-Cameras-Based Driver’s Eye Gaze Tracking System with Non-Linear Gaze Point Refinement |
| title_full | Dual-Cameras-Based Driver’s Eye Gaze Tracking System with Non-Linear Gaze Point Refinement |
| title_fullStr | Dual-Cameras-Based Driver’s Eye Gaze Tracking System with Non-Linear Gaze Point Refinement |
| title_full_unstemmed | Dual-Cameras-Based Driver’s Eye Gaze Tracking System with Non-Linear Gaze Point Refinement |
| title_short | Dual-Cameras-Based Driver’s Eye Gaze Tracking System with Non-Linear Gaze Point Refinement |
| title_sort | dual cameras based driver s eye gaze tracking system with non linear gaze point refinement |
| topic | driving environment gaze tracking non-linear refinement |
| url | https://www.mdpi.com/1424-8220/22/6/2326 |
| work_keys_str_mv | AT yafeiwang dualcamerasbaseddriverseyegazetrackingsystemwithnonlineargazepointrefinement AT xueyanding dualcamerasbaseddriverseyegazetrackingsystemwithnonlineargazepointrefinement AT guoliangyuan dualcamerasbaseddriverseyegazetrackingsystemwithnonlineargazepointrefinement AT xianpingfu dualcamerasbaseddriverseyegazetrackingsystemwithnonlineargazepointrefinement |