3D Gaze Estimation Using RGB-IR Cameras

Moayad Mokatren, Tsvi Kuflik, Ilan Shimshoni

Research output: Contribution to journalArticlepeer-review

Abstract

In this paper, we present a framework for 3D gaze estimation intended to identify the user’s focus of attention in a corneal imaging system. The framework uses a headset that consists of three cameras, a scene camera and two eye cameras: an IR camera and an RGB camera. The IR camera is used to continuously and reliably track the pupil and the RGB camera is used to acquire corneal images of the same eye. Deep learning algorithms are trained to detect the pupil in IR and RGB images and to compute a per user 3D model of the eye in real time. Once the 3D model is built, the 3D gaze direction is computed starting from the eyeball center and passing through the pupil center to the outside world. This model can also be used to transform the pupil position detected in the IR image into its corresponding position in the RGB image and to detect the gaze direction in the corneal image. This technique circumvents the problem of pupil detection in RGB images, which is especially difficult and unreliable when the scene is reflected in the corneal images. In our approach, the auto-calibration process is transparent and unobtrusive. Users do not have to be instructed to look at specific objects to calibrate the eye tracker. They need only to act and gaze normally. The framework was evaluated in a user study in realistic settings and the results are promising. It achieved a very low 3D gaze error (2.12°) and very high accuracy in acquiring corneal images (intersection over union— (Formula presented.) = 0.71). The framework may be used in a variety of real-world mobile scenarios (indoors, indoors near windows and outdoors) with high accuracy.

Original languageEnglish
Article number381
JournalSensors
Volume23
Issue number1
DOIs
StatePublished - Jan 2023

Bibliographical note

Funding Information:
This research was funded by The Council for Higher Education of Israel.

Publisher Copyright:
© 2022 by the authors.

Keywords

  • 3D gaze estimation
  • corneal imaging
  • eye tracking

ASJC Scopus subject areas

  • Analytical Chemistry
  • Information Systems
  • Biochemistry
  • Atomic and Molecular Physics, and Optics
  • Instrumentation
  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of '3D Gaze Estimation Using RGB-IR Cameras'. Together they form a unique fingerprint.

Cite this