基于多特征的駕駛員不安全行為檢測(cè)的研究
[Abstract]:Since China's entry into the World Trade Organization (WTO), China's economy has developed vigorously, the national infrastructure has been gradually improved, the standard of living of the people has been greatly improved, and the number of private cars has increased year by year, resulting in frequent traffic accidents. The life and property of the people have a major impact, seriously affecting the efficiency of transportation. Therefore, it is of great practical value and social significance to develop the driver's safety behavior supervision system, which is helpful to strengthen the driver's safety consciousness and carry out the safe driving operation. At present, the driver safety behavior assistant system based on computer vision mainly focuses on the driver's mental state and fatigue driving direction, and whether the driving safety depends on whether the driver's driving behavior conforms to the safe operation rules or not. Therefore, in this paper, the driver's driving behavior itself as a starting point, unsafe driving behavior detection. The main contents of this paper are as follows: (1) starting with the driver's specific behavior during driving, the author divides the driver's hand movement behavior into two categories: the driver's hand movement trend and the position of the hand on the steering wheel. The steering information and gear information of the vehicle are used to judge the movement trend of the driver's hand, and the position of the driver's hand is located by the computer vision technology. (2) the steering wheel in the captured image is located by using the elliptical detection technology. In order to get the region of interest, through a lot of statistical analysis, the Gao Si skin color model is established. According to the obtained Gao Si skin color model, the probability of pixels belonging to the skin color region in the image is calculated. The driver's hand is separated from the background by the threshold segmentation of Otsu. In order to make the skin color detection results adapt to different external environments, an adaptive Gao Si skin color model is proposed. (3) according to the driver's behavior characteristics collected, the skin color model is proposed. Driver behavior classification decision tree is trained to recognize driving behavior, and a large number of samples are used to verify the feasibility of the method.
【學(xué)位授予單位】:天津大學(xué)
【學(xué)位級(jí)別】:碩士
【學(xué)位授予年份】:2016
【分類號(hào)】:U463.6;TP391.41
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