Abstract
Abstract : In this report, we summarize our efforts in developing real time non-intrusive technology-for monitoring human fatigue. Through this research, we have developed state of the art technologies and a prototype fatigue monitor for real time non-intrusive human fatigue monitoring. Our contributions include: 1) the development of various computer vision techniques for real-time and non-intrusive extraction of multiple fatigue parameters related to eyelid movements, gaze, head movement, and facial expressions, 2) the development of a probabilistic framework based on the Bayesian networks to model and integrate contextual and visual cues information for robust and accurate fatigue detection, and 3) systematic and scientific validation of the fatigue monitor. Experimental validation of our techniques using human subjects demonstrates the good measurement accuracy of our techniques. In addition, the validation also verifies the validity of the proposed fatigue parameters as well as that of the composite fatigue index computed by our fatigue monitor.
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