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3D Gaze Estimation for Head-Mounted Eye Tracking System with Auto-Calibration Method

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成果类型:
期刊论文
作者:
Liu, Meng;Li, Youfu*;Liu, Hai
通讯作者:
Li, Youfu
作者机构:
[Li, Youfu; Liu, Hai; Liu, Meng] City Univ Hong Kong, Dept Mech Engn, Hong Kong, Peoples R China.
[Liu, Hai] Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan 430079, Peoples R China.
通讯机构:
[Li, Youfu] C
City Univ Hong Kong, Dept Mech Engn, Hong Kong, Peoples R China.
语种:
英文
关键词:
Head-mounted gaze tracking system;saliency maps;auto-calibration;3D gaze estimation
期刊:
IEEE Access
ISSN:
2169-3536
年:
2020
卷:
8
页码:
104207-104215
基金类别:
This work was supported in part by the Research Grants Council of Hong Kong Project under Grant CityU 11203619, and in part by the National Natural Science Foundation of China under Grant 61873220 and Grant 61875068.
机构署名:
本校为其他机构
院系归属:
国家数字化学习工程技术研究中心
摘要:
The general challenges of 3D gaze estimation for head-mounted eye tracking systems are inflexible marker-based calibration procedure and significant errors of depth estimation. In this paper, we propose a 3D gaze estimation with an auto-calibration method. To acquire the accurate 3D structure of the environment, an RGBD camera is applied as the scene camera of our system. By adopting the saliency detection method, saliency maps can be acquired through scene images, and 3D salient pixels in the scene are considered potential 3D calibration targets. The 3D eye model is built on the basis of eye ...

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