Method and device for accurately automatically identifying driver unsafe behavior based on convolutional neural network

A convolutional neural network and automatic recognition technology, applied in the field of pattern recognition, which can solve problems such as unsatisfactory accuracy and the inability of neural network structure to handle actual situations.

Inactive Publication Date: 2019-07-09
田文洪 +3
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, a single neural network structure cannot handle complex actual situations, and its accuracy rate is unsatisfactory, requiring a more complex and advanced algorithm and model structure to complete

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  • Method and device for accurately automatically identifying driver unsafe behavior based on convolutional neural network
  • Method and device for accurately automatically identifying driver unsafe behavior based on convolutional neural network
  • Method and device for accurately automatically identifying driver unsafe behavior based on convolutional neural network

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Embodiment Construction

[0032] The specific implementation manners of the present invention will be described in further detail below according to the drawings and examples. The following examples are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0033] Such as figure 1 As shown in the device architecture diagram, the embodiment of the present invention provides a device for automatically identifying driver's unsafe behavior with high precision, where the unsafe behavior includes but is not limited to Figure three species, the device includes:

[0034]The monitoring module extracts real-time video streams and transmits them to the identification module. The identification module judges the three behaviors (calling, not wearing a seat belt, smoking) in parallel. Once a behavior occurs, it will trigger the alarm module. If not, continue to identify. When the alarm module is triggered, the driver will receive a corresponding alarm and b...

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Abstract

The embodiment of the invention discloses a method and device for accurately automatically identifying a driver unsafe behavior based on a convolutional neural network, and relates to the fields of image recognition, pattern recognition and automation. In the case of the problem of unsafe behavior detection of important cargo transportation or the driver of a passenger car, the method of DriverBeCog is provided; the method comprises the steps of using a capsule neural network and the convolutional neural network to extract real-time image characteristics of the driver; respectively performingtwo classifications on various behaviors in parallel; using a monitoring device back screen for real-time monitoring, issuing a warning for the unsafe behavior, and recording relevant information intoa database. The method adopts multiple models concurrent processing, and proposes the convolutional neural network model with few network layers, few parameters, small calculation amount and easy practicality; the recognition rate of the unsafe behavior exceeds existing achievements, which is beneficial to practical use; a weight parameter adjustment method solves the problem that a positive andnegative data volume gap is too large.

Description

technical field [0001] The invention relates to the fields of pattern recognition and safe driving behavior monitoring, in particular to a method and device for automatically identifying driver's unsafe behavior. Background technique [0002] As of the end of 2016, the number of motor vehicles in my country reached 290 million, including 194 million cars, 360 million motor vehicle drivers, and more than 310 million car drivers. A large number of cars have caused a large number of traffic accidents, and many of these traffic accidents are caused by uncivilized and unsafe traffic behaviors, such as smoking with one hand or making a phone call, and controlling the car with one hand; Insufficient awareness, there are still a large number of cases of not wearing seat belts. For important cargo transportation or passenger vehicles, the harm caused by accidents is huge. Therefore, society has a strong demand for systems that can automatically identify driver violations and issue ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): B60W40/09B60W50/14
CPCB60W40/09B60W50/14
Inventor 不公告发明人
Owner 田文洪
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