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Driver visual dispersion detection method based on a deep fusion neural network

A technology of neural network and detection method, which is applied in the field of driver's visual dispersion detection based on deep fusion neural network, which can solve the problems of constraining system portability, high hardware dependence, and difficult installation and use of the system

Pending Publication Date: 2019-04-05
山东派蒙机电技术有限公司
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AI Technical Summary

Problems solved by technology

However, the system is very dependent on hardware, and additional hardware facilities need to be installed on the vehicle, which greatly restricts the portability of the system
Therefore, such systems are difficult to install and use on ordinary cars

Method used

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  • Driver visual dispersion detection method based on a deep fusion neural network
  • Driver visual dispersion detection method based on a deep fusion neural network
  • Driver visual dispersion detection method based on a deep fusion neural network

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Embodiment Construction

[0020] The present invention will be described in detail below in conjunction with the accompanying drawings.

[0021] In the present invention, use the CCD camera to obtain the image of the driver, use the random forest model obtained through training and the current regression model to locate the position of the facial feature point, and extract the image of the eye region; Rigid head movement, use the optimization method to obtain the driver's head posture; then, combine the driver's attention direction and the area division position in the car, and build a deep fusion neural network model according to the eye image and head posture parameters, And use different data sets for pre-training and fine-tuning, the eye image and head pose parameters are used as the input of the model, and the driver's line of sight area is obtained according to the output of the model. Such as figure 1 As shown, the detection method includes the following steps:

[0022] 1. Obtain the facial fe...

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Abstract

The invention discloses a driver visual dispersion detection method based on a deep fusion neural network, which is used for detecting the sight attention of a driver in real time. The method comprises the following steps: (1) acquiring a driver face image, and tracking facial feature points of a driver by adopting local binary features (LBF); (2) positioning and extracting an image of the eye region according to the positions of the facial feature points of the eye region; (3) estimating the head posture by adopting an N-point perspective (PnP) algorithm according to the positions of the facial feature points, and obtaining head posture parameters of the driver in three directions; And (4) estimating the driver sight direction based on the deep hybrid neural network. According to the invention, the attention of a driver can be effectively detected.

Description

technical field [0001] The invention relates to the technical field of vehicle driving, in particular to a method for detecting distraction of driver's vision based on a deep fusion neural network. Background technique [0002] At present, the driver's visually distracted driving is the main factor leading to traffic accidents. According to the research of the National Highway Traffic Safety Administration, the proportion of traffic accidents caused by driver distraction is more than 70%. Driver's visually distracted driving refers to the diversion of the driver's visual attention from focusing on the road and driving operations to other behaviors, such as looking at mobile phones, reading files, making calls, eating, and operating on-board electronic devices. Studies have shown that performing other non-driving-related tasks while driving will aggravate the driver's cognitive load, and with the increasing functions of mobile phones and automotive electronic devices, this p...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06V40/197G06V20/597G06N3/045G06F18/2413G06F18/24147
Inventor 赵磊罗映
Owner 山东派蒙机电技术有限公司
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