Dual-camera acquisition for accurate measurement of three-dimensional eye movements

  • Sunu Wibirama, Supan Tungjitkusolmun, Chuchart Pintavirooj
  • IEEJ Transactions on Electrical and Electronic Engineering, April 2013, Wiley
  • DOI: 10.1002/tee.21845

An image processing technique to detect vertigo through eye movements

What is it about?

Video-oculography (VOG) is a computer-aided diagnosis device that tracks eye movements based on analysis of a recorded video. The system consists of a special goggle with near infrared illumination and infrared-sensitive cameras. VOG implements digital image processing techniques to estimate spatial positions of the pupil and iris pattern. Computing these positions frame-by-frame and converting the positions to angular coordinates, the system provides information of eye movements, with which classification of vertigo diseases can be performed by either the VOG system or the medical doctor. In this paper, we suggest a new approach for accurate measurement of three-dimensional eye movements employing dual-camera acquisition. Two calibrated mini CCD cameras are used to capture two simultaneous images of one eye. Center-of-mass and template-matching algorithms are utilized to obtain two-dimensional coordinates of the center of pupil and iris striation. Instead of asking each subject to fulfill intricate calibration steps, a novel and simpler technique to solve geometric distortion are presented by utilizing direct linear transformation (DLT) algorithm which requires only one preliminary calibration procedure for each camera without changing any camera installation. The DLT algorithm is then used to extract three-dimensional coordinates of the center of the pupil and iris striation from prior two-dimensional coordinates, allowing the three-dimensional angular positions of the eye to be computed. Real-time eyeball visualization based on tracking results is incorporated to help clinicians diagnose eye movements. Experimental results show that our system has high accuracy, as the average errors in the horizontal, vertical, and torsional angular positions were confined to 0.15°, 0.14°, and 0.20°, respectively. Real-time implementation demonstrates that our system can be used in clinical routines to observe either voluntary or involuntary human eye movements.

Why is it important?

Brain cancer is normally caused by tumor growing inside intracranial tissue in the brain, central nervous system, or meninges of the brain. Brain cancer has been devoted as dominant disease of all cancer cases spreading in human central nervous system. Vertigo is a common symptom reported among patients suffering from brain cancer, particularly if the cancer spread throughout parts of brain related to vision, hearing, and balance system (vestibule-ocular system). Vertigo usually causes false sensation of spinning and dizziness. Although vertigo is also possibly caused by aging or abnormality in balance system, early diagnosis of vertigo is important to observe existing of brain tumor. Diagnosis of vertigo is normally performed with Dix-Hallpike test. The test requires a patient to be positioned from sitting to supine position, with the head turned 45 degrees to one side and extended about 45 degrees backward. Once supine, the eyes are typically observed for about 30 seconds. The medical doctor observes vertigo by identifying particular eye movements. If no vertigo symptoms ensue, the participant is brought back to sitting. Although manual observation is useful for experienced medical doctor, inexperienced and young doctor may find it difficult to determine the type and the cause of vertigo. In this case, computer-aided diagnosis is useful for providing an objective diagnosis of vertigo.


Dr.Eng. Sunu Wibirama
Universitas Gadjah Mada

Our system has been the first system in the world that estimates vertigo through accurate 3D reconstruction of human's eyeball. The developed method is useful, particularly for engineers working on physiological optics, image analysis, and development of medical devices for an ophthalmologist.

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The following have contributed to this page: Dr.Eng. Sunu Wibirama