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A study on road accidents stated that 20% of accidents are based on drivers' fatigue. Even though there are solutions based on mechanical and electrical sensor-based systems with capturing of driving patterns, lane monitoring etc., but failed to detect fatigue accurately. Recent developments in computer vision led to revolution in detecting objects, movement tracking etc. In this work, the main objective is to develop a nonintrusive system that can detect fatigue of any human and issues a timely warning. Drivers, who do not take orderly breaks while driving for long distances ran into a high chance of turning drowsy, which they frequently fail to recognize early enough. This system captures the feed of the driver using a web camera and tracks the movement of an eye lids using Stacking Ensemble Classifier. The tiredness or fatigue can be detected with recognition of eye closing pattern based on facial landmarks. Performance of the proposed work is better in terms of accuracy with low computational complexity, when compared with other existing works. So, when abnormalities are identified, the system alert the driver in the form of beeps or slowdown the acceleration, there by prevents number of road accidents.