Abstract
Removing explicit user calibration is indeed an appealing goal for gaze tracking systems. In this paper, a novel auto-calibration method is proposed to achieve the 3D point of regard (PoR) prediction for the head-mounted gaze tracker. Our method chooses an RGBD sensor as the scene camera to capture 3D structures of the environment and treats salient regions as possible 3D calibration targets. In order to improve efficiency, the bag of words (BoW) algorithm is applied to calculate scene images' similarity and eliminate redundant maps. After elimination, the translation relationship between eye cameras and the scene camera can be determined by uniting calibration targets with gaze vectors, and 3D gaze points are obtained by transformed gaze vectors and the point cloud of environment. The experiment results indicate that our method achieves effective performance on 3D gaze estimation for head-mounted gaze trackers, which can promote engineering applications of human-computer interaction technology in many areas. ©2020 IEEE.
| Original language | English |
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| Title of host publication | 2020 IEEE International Conference on Mechatronics and Automation (ICMA) |
| Publisher | IEEE |
| Pages | 588-593 |
| ISBN (Electronic) | 978172864168 |
| ISBN (Print) | 9781728164151 |
| DOIs | |
| Publication status | Published - 2020 |
| Event | 17th IEEE International Conference on Mechatronics and Automation (ICMA 2020) - Beijing, China Duration: 13 Oct 2020 → 16 Oct 2020 http://2020.ieee-icma.org/ |
Publication series
| Name | IEEE International Conference on Mechatronics and Automation, ICMA |
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| ISSN (Electronic) | 2152-744X |
Conference
| Conference | 17th IEEE International Conference on Mechatronics and Automation (ICMA 2020) |
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| Abbreviated title | IEEE ICMA 2020 |
| Place | China |
| City | Beijing |
| Period | 13/10/20 → 16/10/20 |
| Internet address |
Research Keywords
- 3D gaze estimation
- auto-calibration
- head-mounted gaze tracker
- human-computer interaction