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

Meng Liu,Hai Liu,Youfu Li

doi:10.1109/access.2020.2999633

Abstract

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 images to determine gaze vectors. By combining 3D salient pixels and gaze vectors, the auto-calibration can be achieved with our calibration method. Finally, the 3D gaze point is obtained through the calibrated gaze vectors, and the point cloud is generated from the RGBD camera. The experimental result shows that the proposed system can achieve an average accuracy of 3.7° in the range of 1 m to 4 m indoors and 4.0° outdoors. The proposed system also presents a great improvement in depth measurement, which is sufficient for tracking users' visual attention in real scenes.

Highlights

Gaze estimation is the process of predicting where someone is looking, either as gaze directions or as points of regard (PoR) in space
Gaze estimation systems can be generally classified into remote devices and head-mounted devices (HMD) [5]
ARCHITECTURE FOR HMD A head-mounted eye tracking system consists of two parts

Summary

Introduction

Gaze estimation is the process of predicting where someone is looking, either as gaze directions or as points of regard (PoR) in space. Estimating users’ gaze vectors or gaze points will be of great help to understand human activities. Gaze estimation systems have been applied in many fields, such as human-machine interactions [2], assisted driving [3], and surgery assistance [4]. Gaze estimation systems can be generally classified into remote devices and head-mounted devices (HMD) [5]. The remote device is a screen-based interaction system that works at a distance from the subject [6].

Methods

Conclusion