Detecting Driver Sleepiness using Convolutional Neural Networks

The development in computer vision has aided drivers the form of automatic self-driving cars etc. accidents are caused by driver's exhaustion and drowsiness about 20%. Its carriages a dangerous issue for which numerous methods were proposed. However, they not appropriate real-time implementation. major encounters confronted these approaches forcefulness to handle dissimilarity human face lightning conditions. Our intention is implement smart operating system that can lower rate road considerably. This method enables us find features like eye closure percentage, eye-mouth aspect ratios, blink rate, yawning, head movement, In this classification, driver uninterruptedly observed using webcam. car driver’s facial along with movements cascade classifier. Eye images pull out fed Custom designed Convolutional Neural Network categorizing whether both left right closed. Based on sorting, score considered. Upon finding being detected drowsy high alarm will be raised.