Robust remote gaze estimation method based on multiple geometric transforms

Chunfei Ma, Kang A. Choi, Byeong Doo Choi, Sung-Jea Ko

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)


The remote gaze estimation (RGE) technique has been widely used as a natural interface in consumer electronic devices for decades. Although outstanding outcomes on RGE have been recently reported in the literature, tracking gaze under large head movements is still an unsolved problem. General RGE methods estimate a user's point of gaze (POG) using a mapping function representing the relationship between several infrared light sources and their corresponding corneal reflections (CRs) in the eye image. However, the minimum number of available CRs required for a valid POG estimation cannot be satisfied in those methods because the CRs often tend to be distorted or disappeared inevitably under the unconstrained eye and head movements. To overcome this problem, a multiple-transform-based method is proposed. In the proposed method, through three different geometric transform-based normalization processes, several nonlinear mapping functions are simultaneously obtained in the calibration process and then used to estimate the POG. The geometric transforms and mapping functions can be alternatively employed according to the number of available CRs even under large head movement. Experimental results on six subjects demonstrate the effectiveness of the proposed method.

Original languageEnglish
Article number083103
JournalOptical Engineering
Issue number8
Publication statusPublished - 2015 Aug 1


  • large head movement
  • multiple geometric transforms
  • reliability
  • remote gaze estimation
  • robustness

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics
  • Engineering(all)


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