Eye Blink Based Fatigue Detection for Prevention of Computer Vision Syndrome
Eye Blink Based Fatigue Detection for Prevention of Computer Vision Syndrome
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发表时间：
2009
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通讯作者：
M. Divjak;H. Bischof
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作者：
M. Divjak;H. Bischof
生活在信息社会，我们花了很多时间在视觉显示单元，如计算机显示器或电视屏幕前。这对我们的生活既有积极的影响，也有消极的影响。负面影响主要与健康有关，其中一个主要问题是越来越多的人受到计算机视觉综合症（CVS）的影响[1]。大多数与CVS相关的问题都可以通过适当的预防措施来避免，但大多数计算机用户都忽略了它们。为了帮助补救这种情况，我们提出了一个计算机视觉系统的原型，用于基于实时眨眼的眼睛疲劳检测，这是导致CVS的常见症状。我们的程序通过安装在计算机监视器上的网络摄像头记录用户的视频，处理帧并根据用户的眼睛动态和眨眼模式检测危险行为。实验结果表明，该系统能够检测与长期使用计算机的疲劳行为的常见情况下。我们相信，经常使用拟议的系统可以显着减少CVS症状的长期计算机工作者。然而，所使用的技术也可以应用于其他类似应用，例如驾驶员疲劳检测、人机交互等。
Living in information society we spend a lot of time in front of visual display units such as computer monitors or TV screens. This has positive as well as negative effects on our lives. Negative effects are mostly health related and one major concern is the increasing number of people affected by the Computer Vision Syndrome (CVS) [1]. Most CVS-related problems can be avoided by suitable preventive actions, but the majority of computer users ignore them. To help remedy the situation we present a prototype of a computer vision system for real-time eye blink based detection of eye fatigue, which is a common symptom leading towards CVS. Our program records video of the user by a computer monitor mounted web-camera, processes the frames and detects hazardous behaviour based on user’s eye dynamics and blink patterns. Experimental results show that the proposed system is capable of detecting common cases of fatigued behaviour linked with long-term computer use. We believe regular use of the proposed system could significantly reduce the CVS symptoms for long-time computer workers. However, the techniques used can also be applied to other similar applications, such as driver fatigue detection, human-computer interaction, etc.