• Amandeep Kaur
• Dr. Parveen Kakkar

Sleep deprivation is one of the major causes of driver’s drowsiness that leads to severe road accidents. Hence, it is necessary to develop systems to detect driver’s drowsiness and prevent many accidents, physical injuries and economic losses. Lane position monitoring, vehicle pattern monitoring, behavioral and physiological measures have been explored to detect whether the driver is drowsy or fatigued. Behavioral measures such as eye blinking frequency, PERCLOS (percentage of eye lid closure), Head tilting, driver’s direction of attention and yawning detection are mostly used in drowsiness detection and alert systems. This paper presents a thorough review of yawning detection techniques as yawning is not only useful in driver fatigue detection system but also in operator attentiveness detection, human well-being assessment and studying the intentions of people with a tongue disability. Yawning detection consists of three principle steps that are face detection, mouth detection and yawning observation. Viola Jones algorithm is widely used for face and mouth detection. A vast number of techniques have been examined to detect yawning in the past. The current growth of deep learning requires that these algorithms or techniques be revisited to evaluate their accuracy in detection of yawning. Efficient and accurate yawning measurement is needed to develop robust and reliable systems. This paper will discuss recent techniques and algorithms for yawning detection based on ANN, computer vision, machine learning and deep learning. It also lists various publicly available databases used for yawning detection.

Yawning detection, driver drowsiness, machine learning, neural networks, computer vision

"Yawning Detection for Driver Drowsiness Measurement: A Review ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 4, page no.320-325, April-2019, Available :http://www.jetir.org/papers/JETIR1904758.pdf

"Yawning Detection for Driver Drowsiness Measurement: A Review ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 4, page no. pp320-325, April-2019, Available at : http://www.jetir.org/papers/JETIR1904758.pdf