Essay On Computer Vision Syndrome

As the number of people using computers increases, so is the increase in number of people, who suffer from symptoms, which are commonly known as Computer Vision Syndrome (CVS). This condition results from focusing eyes on a computer or other display device for long and uninterrupted period. The symptoms include headaches, blurred vision, fatigue, eyestrain, dry eyes, irritated eyes, double vision, dizziness, and difficulty in refocusing the eyes. These improper lighting conditions (i.e. glare or bright overhead lighting) or air moving past the eyes (e.g. overhead vents, direct air from a fan, etc.) [1] further aggravate these symptoms. Blinking helps to spread the tear film and moisten the surface of the eye, otherwise reduced rate of blinking leads to Dry Eye. Typical complaints experienced by intensive computing work (more than 3 hours per day) include dryness, redness, burning, sandy-gritty eye irritation or sensitivity to light and eye fatigue [2].
According to the National Institute for Occupational Safety and Health, computer vision syndrome affects about 90% of the people who spend three hours or more a day at a

The Gabor filter measures distance between detected top and bottom arc in eye region. This distance varies for open and closed eyes. Further, variance map is used to detect distribution of intensities from the mean value in an image sequence. Since, the intensity of pixels located in eye region changes during the blink, this can also be used for eye blink detection, as discussed in [11]. Another eye blink detection is reported in [12], where eye contour extraction is used as a deformable model represented by several landmarks as the eye contour shape. This model learns as each landmark appears, and thus fits it in the actual frame to update eye shape. After this, the distance measurement between upper and lower eyelid represents eye