Simulation results for an innovative point-of-regard sensor using neural networks

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A major obstacle in point-of-regard monitoring for human-computer interaction has been the contaminating effect of head movement. A novel solution to this problem has been simulated. A multi-layer perceptron converts the distorted pattern of four infrared sources, reflected in the cornea of the user, into an estimate for the point-of-regard. Using an idealised model of the eye the simulation combined vertical, horizontal, pitch and yaw head movements with eye excursions typical of individuals seated in front of a computer display. Results show that the method is capable of dramatically reducing the effects of small head movements. Under these viewing conditions the error in the point-of-regard estimate exhibited a standard deviation of under 0.5 mm. I is concluded that such a scheme could form an attractive solution to the long-standing problem of head movement artefact.

Original languageEnglish
Pages (from-to)230-237
Number of pages8
JournalNeural computing & applications
Issue number4
Publication statusPublished - 1997


  • human-computer interaction
  • point-of-regard
  • sensor
  • eye model
  • multi-layer perceptron
  • head movement artefact

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