Etracker: A mobile gaze-tracking system with near-eye display based on a combined gaze-tracking algorithm

Bin LI, Hong FU, Desheng WEN, WaiLun LO

Research output: Contribution to journalArticlespeer-review

19 Citations (Scopus)

Abstract

Eye tracking technology has become increasingly important for psychological analysis, medical diagnosis, driver assistance systems, and many other applications. Various gaze-tracking models have been established by previous researchers. However, there is currently no near-eye display system with accurate gaze-tracking performance and a convenient user experience. In this paper, we constructed a complete prototype of the mobile gaze-tracking system ‘Etracker’ with a near-eye viewing device for human gaze tracking. We proposed a combined gaze-tracking algorithm. In this algorithm, the convolutional neural network is used to remove blinking images and predict coarse gaze position, and then a geometric model is defined for accurate human gaze tracking. Moreover, we proposed using the mean value of gazes to resolve pupil center changes caused by nystagmus in calibration algorithms, so that an individual user only needs to calibrate it the first time, which makes our system more convenient. The experiments on gaze data from 26 participants show that the eye center detection accuracy is 98% and Etracker can provide an average gaze accuracy of 0.53° at a rate of 30–60 Hz. Copyright © 2018 by the authors. Licensee MDPI, Basel, Switzerland.
Original languageEnglish
Article number1626
JournalSensors
Volume18
Issue number5
Early online date19 May 2018
DOIs
Publication statusPublished - May 2018

Citation

Li, B., Fu, H., Wen, D., & Lo, W. (2018). Etracker: A mobile gaze-tracking system with near-eye display based on a combined gaze-tracking algorithm. Sensors, 18(5). Retrieved from https://doi.org/10.3390/s18051626

Keywords

  • Gaze tracking
  • Infrared camera sensor
  • Near-eye viewing device
  • CNNs
  • Mobile eye tracker

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