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Fatigue driving detection method and system based on AdaBoost algorithm

A fatigue driving and detection method technology, which is applied in the field of computer vision, can solve the problems of insufficient reliability, large errors, and high cost, and achieve the effects of strong robustness, high detection accuracy, and improved fatigue detection accuracy

Inactive Publication Date: 2017-12-19
CHINA UNIV OF GEOSCIENCES (WUHAN)
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Problems solved by technology

[0007] The technical problem to be solved by the present invention is that, in view of one or more technical defects in the above-mentioned current fatigue driving detection method, such as large error, high cost, and insufficient reliability, the present invention provides a fatigue detection method based on the AdaBoost algorithm. Driving detection method and system

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  • Fatigue driving detection method and system based on AdaBoost algorithm
  • Fatigue driving detection method and system based on AdaBoost algorithm
  • Fatigue driving detection method and system based on AdaBoost algorithm

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Embodiment Construction

[0080] The principles and features of the present invention are described below in conjunction with the accompanying drawings, and the examples given are only used to explain the present invention, and are not intended to limit the scope of the present invention.

[0081] Traditional AdaBoost algorithm (Yoav Freund and Robert E S chapire. A decision-theoretic generalization of on-line learning and an application to boosting. Journal of Computer and System Sciences, 1997,55(1):119-139.), algorithm flow description as follows:

[0082] Sample set: select n samples, the i-th sample (x i ,y i ) consists of two elements, x i represents the variable, y i represents the variable x i belongs to the category, this sample can be expressed as a set S={(x i ,y i )|i=1,2,...,n}, x i ∈X,y i ∈Y={-1,+1}, i=1,2,...,n, X is the set of all variables, Y is the set of categories.

[0083] Initialization: For each sample (x i ,y i )∈S, denote D 1 (x i ,y i )=1 / n;

[0084] Training pr...

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Abstract

The invention discloses a fatigue driving detection method and system based on an AdaBoost algorithm. The method comprises steps that firstly, for a weight distribution distortion phenomenon of a traditional AdaBoost algorithm, an improved algorithm based on weight distribution adjustment is proposed; secondly, the improved AdaBoost algorithm is utilized to respectively detect face, eye opening and mouth opening states and calculate eye blink frequency and yawn frequency; and lastly, a fatigue index is calculated, a state of a driver is determined according to the fatigue index, the state includes three levels including a sober level, a mild fatigue level and a fatigue level, and corresponding measures can be adopted. The algorithm is advantaged in that the algorithm is simple and easy, use environment requirements are low, strong robustness is realized, detection precision is high, and the algorithm can be applied to fatigue driving detection in intelligent driving occasions.

Description

technical field [0001] The invention relates to the technical field of computer vision, in particular to a fatigue driving detection method and system based on the AdaBoost algorithm. Background technique [0002] With the rapid development of my country's economy, the number of car ownership is gradually increasing. While automobiles bring great convenience to our daily life, they also bring many problems, such as the gradual deterioration of urban traffic environment, increasingly serious traffic jams, and frequent occurrence of traffic accidents. The occurrence of traffic accidents has both external and human factors. The external factors are mainly rainy and snowy weather, which makes road driving difficult, and the dark light affects the driver's sight. External factors can be partially avoided by controlling travel and increasing road visibility; human factors need to be avoided by strengthening supervision and adopting technical means. The country has effectively cur...

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Application Information

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IPC IPC(8): G06K9/00G06K9/62
CPCG06V20/597G06F18/2148G06F18/241
Inventor 魏龙生陈珺刘玮罗林波罗大鹏
Owner CHINA UNIV OF GEOSCIENCES (WUHAN)
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