Multi-feature fusion driver abnormal expression recognition method

A multi-feature fusion and facial expression recognition technology, applied in character and pattern recognition, instruments, computer components, etc., can solve problems such as data transmission delay, lack of fatigue behavior recognition, inconvenient application, etc., to improve accuracy, improve efficiency, and be good The effect of social benefits

Inactive Publication Date: 2019-10-15
WUHAN INSTITUTE OF TECHNOLOGY
View PDF8 Cites 13 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

When the vehicle passes through a road section with poor signal, data transmission will be delayed
Invention 201610835397.5 uses the method of blink detection and recognition for fatigue monitoring, but lacks th

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Multi-feature fusion driver abnormal expression recognition method
  • Multi-feature fusion driver abnormal expression recognition method
  • Multi-feature fusion driver abnormal expression recognition method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0048] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0049] Such as figure 1 As shown, the multi-feature fusion driver's abnormal expression recognition method in the embodiment of the present invention realizes real-time tracking and recognition of the driver using the on-board camera in a complex traffic scene, detects its abnormal actions, and triggers an alarm signal. The method includes the following steps:

[0050] S1. Use the on-board camera to detect the driver in real time, and detect whether there is a driver's face in the video; if it exists, mark the position of the driver's face as an input image for further analyzing the details of his...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a multi-feature fusion driver abnormal expression recognition method. The multi-feature fusion driver abnormal expression recognition method comprises the steps: S1, tracking and monitoring expression actions of a driver in real time through a camera installed on the driver side; S2, precisely identifying expression details in the real-time driver video; S3, detecting the positions of the eyes, and judging whether the eyes are tired or not; S4, positioning the edge contour of the mouth, and judging whether yawn action occurs or not; S5, detecting a head action, and judging whether fatigue occurs or not; S6, weighting the detection results of the eye state, the mouth state and the head motion state, finally judging whether fatigue occurs or not, and outputting the detection results; and S7, combining the identification result of the current frame as an estimated position of subsequent frame identification, and respectively detecting actions in subsequent frames to realize continuous detection and identification of abnormal behaviors of the driver. According to the invention, real-time monitoring and alarm triggering can be carried out, a driver is warned andreminded, and traffic accidents are prevented, and the safety in the driving process is ensured.

Description

technical field [0001] The invention relates to the fields of fatigue detection, human-computer interaction and video image pattern recognition, in particular to a multi-feature fusion driver abnormal expression recognition method. Background technique [0002] The road traffic in modern society is becoming more and more prosperous, and the traffic accidents that follow are showing a trend of frequent occurrence. Fatigue driving is an important cause of traffic accidents. How to effectively track the driver's fatigue driving and call the police is the key to reducing the occurrence of traffic accidents. an important measure. Among them, the abnormal driving behavior detection based on computer vision monitoring is a new research hotspot and direction. Novidia has launched the AI ​​Co-Pilot assisted driving system, which uses the on-board camera to obtain the driver's image video, combined with artificial intelligence algorithms Face recognition, head tracking, and eye movem...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G06K9/00G06K9/62
CPCG06V40/165G06V20/597G06F18/2411G06F18/253
Inventor 徐国庆
Owner WUHAN INSTITUTE OF TECHNOLOGY
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products