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Method and device for identifying fatigue state of driver based on feature selection and integration of face multi-region classifiers

A fatigue state and feature selection technology, applied in character and pattern recognition, acquisition/recognition of facial features, instruments, etc., can solve the problems of driver fatigue state recognition methods and device disclosure, achieve comprehensive and rich facial description information, and improve Recognition performance, recognition rate improvement effect

Inactive Publication Date: 2017-05-31
NORTHEAST AGRICULTURAL UNIVERSITY
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Problems solved by technology

However, no driver fatigue state recognition method and device based on similar ideas have been disclosed.

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  • Method and device for identifying fatigue state of driver based on feature selection and integration of face multi-region classifiers
  • Method and device for identifying fatigue state of driver based on feature selection and integration of face multi-region classifiers
  • Method and device for identifying fatigue state of driver based on feature selection and integration of face multi-region classifiers

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Embodiment Construction

[0068] Attached below Figures 1 to 3 , to further describe the specific implementation of the invention, the following is only used to illustrate the implementation method of the technical solution of the present invention more clearly and in detail, but not to limit the protection scope of the present invention.

[0069] refer to figure 2 , the present invention realizes early warning of the driver's fatigue state, including two processes of training and identification, wherein the training process needs to evaluate and select the features extracted from each area, so as to generate a simplified feature set corresponding to each area, and based on these The reduced feature set trains a set of C4.5 classifiers, and only needs to extract these features for classification in the recognition process.

[0070] Specifically, the training process includes the following steps:

[0071] Step 1: Obtain human face video frames through a program through a video recording device.

[...

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Abstract

The invention provides a method and a device for identifying the fatigue state of a driver based on feature selection and integration of face multi-region classifiers, relating to the technical field of the identification of the fatigue state of the driver. According to the method and the device, a relatively stable and reliable identification result is given out, so that a fatigue behavior can be relatively timely detected, and the early warning can be given to the driver earlier. The method comprises a training process and an identifying process. In the training process, features extracted in each region need to be evaluated and selected so as to generate a simplified feature set corresponding to each region, and a group of C4.5 classifiers are trained based on the simplified feature sets; and in the identifying process, the features need to be extracted for classification. A face region is divided in the two processes, and static features and sequence descriptive features relevant with fatigue behaviors in each face region are extracted. According to the method and the device, the identification performance of the fatigue state of the driver is effectively improved, and the relatively high average identification rate of the fatigue state of the driver is achieved by virtue of the simplified feature sets.

Description

technical field [0001] The invention belongs to the technical field of driver fatigue state recognition in pattern recognition, and specifically designs a method and device for driver fatigue state recognition based on feature selection and classifier integration technology, using face multi-region simplified features. Background technique [0002] Identifying the driver's fatigue state is a challenging pattern recognition problem. The existing technology is mainly aimed at two obvious manifestations of fatigue, namely, the blinking frequency becomes slower, the eye opening becomes smaller, and the characteristics of yawning appear. to identify. There are certain deficiencies in judging the driver’s state by only focusing on these two significant features. First, this recognition technology is often unable to give early warning of driver fatigue, and can only give a warning when the driver is almost dozing off. In fact, the driver is already in danger at this time. Secondl...

Claims

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Application Information

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IPC IPC(8): G06K9/00
CPCG06V40/169G06V40/166G06V40/174G06V40/172G06V20/597
Inventor 杜勇王玉郑书朋
Owner NORTHEAST AGRICULTURAL UNIVERSITY
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