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Road rage emotion recognition method based on facial image and pulse information fusion

A facial image and emotion recognition technology, which is applied in the field of road rage emotion recognition, can solve the problems of single information source and low recognition rate of road rage emotion, and achieve the effect of improving the recognition rate

Active Publication Date: 2020-03-10
SHANDONG UNIV
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AI Technical Summary

Problems solved by technology

Constrained by traditional information collection and data processing technology, the objective analysis method of road rage emotion mainly uses facial images or voices as the information source, which has disadvantages such as single information source, and the recognition rate of road rage emotion cannot reach the actual application effect.

Method used

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  • Road rage emotion recognition method based on facial image and pulse information fusion
  • Road rage emotion recognition method based on facial image and pulse information fusion
  • Road rage emotion recognition method based on facial image and pulse information fusion

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Embodiment Construction

[0067] It should be pointed out that the following detailed description is exemplary and intended to provide further explanation to the present application. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0068] figure 1 The flow of the driver's road rage recognition method is given. The whole process includes four parts: the collection and preprocessing of the driver's original information, the feature extraction of the pulse and facial image information, the feature fusion dimensionality reduction, and the establishment of the road rage recognition model. . The information collection device includes an infrared high-speed camera and a wrist-worn wireless pulse collection terminal.

[0069] figure 2 The location of each collection device is given. exist figure 2 In the middle, the infrared high-speed camera is located on the ins...

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Abstract

The invention discloses a road rage mood recognizing method based on fusion of a face image and pulse information. The method includes the steps of collecting the face image and the pulse informationof a driver to be preprocessed, extracting characteristic vectors capable of reflecting the road rage mood of the driver from the face image and the pulse information, fusing the two types of extracted characteristics, establishing a driver road rage mood recognizing model on the basis of the data mining and machine learning related algorithm and technology, monitoring the mood state of the driverin real time, and judging the mood state of the driver in time. The real-time monitoring and judging of the road rage mood of the driver can be realized, and the adverse effects of the road rage on traffic safety can be effectively reduced.

Description

technical field [0001] The invention belongs to the field of traffic safety driving, in particular to a road rage recognition method based on the fusion of facial images and pulse information. Background technique [0002] With the continuous improvement of people's living standards and the rapid development of the transportation industry, the number of household cars, taxis, buses and various trucks has increased year by year, which has brought great convenience to people's daily travel and life, but with At the same time, the current road traffic situation has thus become more complicated. In addition, the fast-paced life and work make people more and more stressed. When this pressure is transferred to road traffic, it will cause various adverse consequences, and "road rage" is one of them. [0003] "Road rage" refers to the aggressive or angry behavior of motor vehicle drivers, which is mainly manifested in the use of insulting words or gestures, intentional driving in a...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): B60W40/08
CPCB60W40/08
Inventor 杨立才于申浩张成昱
Owner SHANDONG UNIV
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