Accurate gaze tracking from single camera using Gabor corner detector

Li Xia, Bin Sheng, Wen Wu, Lizhuang Ma, Ping Li

Research output: Journal article publicationJournal articleAcademic researchpeer-review

15 Citations (Scopus)


Most of the existing gaze tracking schemes with high accuracy and high speed depend on infra-red (IR) lights and multi-cameras, which leads to high complexity of apparatus and high cost. Besides, many proposed approaches hardly offer a full discussion and solution of eye blink issue. In this paper, we propose a novel gaze tracking scheme which is capable of tracking eye movements in high accuracy. Our scheme incorporates the eye corner information extracted using a novel eye corner detector. This detector is developed based on the Gabor Wavelet Transform and the Structure Tensor. Gabor Wavelet Transform decomposes an image in multi-scales and multi-orientations, thus is robust against lighting variation and tiny shift. We abstract the distribution statistics of the feature points in the eye region and re-express it as a connectivity graph. Based on such abstraction we propose a novel solution to the eye blink issue which obtains a high successful detection rate. After implementation, our scheme is proven to be accurate compared with the state of the art. Notably, only one web camera is employed in our scheme without any auxiliary light source or cameras.

Original languageEnglish
Pages (from-to)221-239
Number of pages19
JournalMultimedia Tools and Applications
Issue number1
Publication statusPublished - Jan 2016


  • Corner detector
  • Gaze tracking
  • Pupil center estimation
  • Single camera

ASJC Scopus subject areas

  • Software
  • Media Technology
  • Hardware and Architecture
  • Computer Networks and Communications


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