
doi: 10.1109/is3c.2016.72
This study develops a real-time drowsiness detection system based on grayscale image processing and PERCLOS to determine if the driver is fatigued. The proposed system comprises three parts: first, it calculates the approximate position of the driver's face in grayscale images, and then uses a small template to analyze the eye positions, second, it uses the data from the previous step and PERCLOS to establish a fatigue model, and finally, based on the driver's personal fatigue model, the system continuously monitors the driver's state. Once the driver exhibits fatigue, the system alerts the driver to stop driving and take a rest.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 45 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
