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Driver fatigue monitoring system based on deep learning

A technology of driver fatigue and deep learning, which is applied in the field of video image processing and visual monitoring, can solve the problems of not considering the dynamic change characteristics of fatigue features, the decline of detection efficiency of detection algorithms, and the improvement of system detection performance, etc., to achieve face detection Increased efficiency, stable and accurate monitoring, and increased safety

Inactive Publication Date: 2020-09-04
CHANGSHA CHAOCHUANG ELECTRONICS TECH
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Problems solved by technology

However, the method based on image appearance features is easily affected by the external lighting environment and image background, so it is easy to cause the detection performance of the detection algorithm to decline.
In addition, the detection method based on static image features does not consider the dynamic characteristics of fatigue features, which is not conducive to the improvement of the detection performance of the developed system to a certain extent.

Method used

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  • Driver fatigue monitoring system based on deep learning
  • Driver fatigue monitoring system based on deep learning
  • Driver fatigue monitoring system based on deep learning

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Embodiment Construction

[0039] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0040] In the description of the present invention, it should be understood that the orientations or positional relationships indicated by "front", "rear", "left", "right", "upper" and "lower" in terms are based on those shown in the accompanying drawings. Orientation or positional relationship is only for the convenience of describing the present invention and simplifying the description, and does not indicate or imply that the referred device or element must ...

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Abstract

The invention discloses a driver fatigue monitoring system based on deep learning and a using method of the driver fatigue monitoring system, and the driver fatigue monitoring system based on deep learning comprises an image acquisition module, a face detection module, an image processing module and a server module, the invention provides the driver fatigue monitoring system based on deep learningand the using method of the driver fatigue monitoring system. By means of the fatigue monitoring system, behaviors such as fatigue driving, dangerous driving and sight deviation of a driver can be monitored on a current hardware platform.

Description

technical field [0001] The invention relates to the technical field of video image processing and visual monitoring, in particular to a driver fatigue monitoring system based on deep learning. Background technique [0002] Automobile safety has increasingly become a problem that people must consider. In addition to the car itself, if the driver does not have good driving habits, the passengers will also be unsafe, and even the safety equipment will not be able to play its due role. Such as fatigue driving, drunk driving, smoking driving, speeding, driving without seat belts, etc., once an accident occurs, the consequences will be unimaginable, so safety awareness is the first priority of car driving! Human illegal behavior is the main cause of traffic accidents. The proportion of accidents caused by human illegal behavior is 95.24%, and the number of deaths is 95.42%. [0003] The basic elements of road traffic are people, vehicles and roads, among which drivers play a par...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62G06N3/04G08B21/06
CPCG08B21/06G06V40/171G06V20/597G06N3/044G06F18/2414
Inventor 李吉成李建东曲原蒋海军刘云剑陈远益
Owner CHANGSHA CHAOCHUANG ELECTRONICS TECH
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