CN109840510A - Monitoring method, device, storage medium and the electronic equipment of fatigue driving - Google Patents
Monitoring method, device, storage medium and the electronic equipment of fatigue driving Download PDFInfo
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Abstract
The embodiment of the present application discloses monitoring method, device, storage medium and the electronic equipment of a kind of fatigue driving.This method comprises: continuously acquiring the infrared image of driver's eye by infrared camera；The eye movement data of driver is determined according to the infrared image continuously acquired；The eye movement data is compared with the visual fatigue threshold value being previously obtained, determines whether driver is in a state of fatigue according to comparison result.By executing technical solution provided herein, the effect for improving the safety of vehicle drive may be implemented.
Description
Technical field
The invention relates to technical field of image processing more particularly to a kind of monitoring method of fatigue driving, device,
Storage medium and electronic equipment.
Background technique
With being gradually increased for scientific and technological level, household vehicle has become the first choice of users' trip.
Although driving vehicle driving is and its easily for driver.But at long range trip or night
Between when going on a journey, driver often enters fatigue driving state because of the fatigue of itself.Fatigue driving is naturally also to hand over
Interpreter therefore one of the main reason occurred, are directed to fatigue driving, use a variety of strategies at present, such as drive small more than 1
Shi Houhui periodically issues information warning to driver, and driver is reminded to be able to maintain the concentration of attention.However this side
Formula is relatively inflexible, can not judge whether driver has been in fatigue driving at any time, therefore the effect of information warning is also past
It is past lower.
Summary of the invention
The embodiment of the present application provides monitoring method, device, storage medium and the electronic equipment of a kind of fatigue driving, Ke Yishi
Now improve the effect of the safety of vehicle drive.
In a first aspect, the embodiment of the present application provides a kind of monitoring method of fatigue driving, this method comprises:
The infrared image of driver's eye is continuously acquired by infrared camera；
The eye movement data of driver is determined according to the infrared image continuously acquired；
The eye movement data is compared with the visual fatigue threshold value being previously obtained, driver is determined according to comparison result
It is whether in a state of fatigue.
Further, the eye movement data is being compared with the visual fatigue threshold value being previously obtained, according to comparison result
After determining whether driver is in a state of fatigue, the method also includes:
If it is determined that driver is in a state of fatigue, then alarm command is generated, so that alert device sounds an alarm prompt tone.
Further, the eye movement data is being compared with the visual fatigue threshold value being previously obtained, according to comparison result
Before determining whether driver is in a state of fatigue, the method also includes:
Obtain the big data of the eye movement data of driver；
According to the big data of the eye movement data of driver, analysis obtains visual fatigue threshold value.
Further, the big data of the eye movement data for obtaining driver, comprising:
It obtains in the normal driving eye movement data, fatigue driving eye movement data and close sleep eye movement data of preset quantity
Show parameter；Wherein, when the performance parameter includes: frequency of wink, direction of gaze and watches duration, twitching of the eyelid frequency and unit attentively
At least one of closure duration of interior eyes；
Correspondingly, analysis obtains visual fatigue threshold value according to the big data of the eye movement data of driver, comprising:
According to the arrangement to normal driving eye movement data, fatigue driving eye movement data and close sleep eye movement data, determine
Difference meets preset condition extremely in normal driving eye movement data and fatigue driving eye movement data and the eye movement data of close sleep
Few species diversity shows parameter；
Determine the visual fatigue threshold value of at least one difference performance parameter.
Further, the eye movement data is being compared with the visual fatigue threshold value being previously obtained, according to comparison result
Before determining whether driver is in a state of fatigue, the method also includes:
Obtain current environment intensity of illumination；
Correspondingly, the eye movement data is compared with the visual fatigue threshold value being previously obtained, determined according to comparison result
Whether driver is in a state of fatigue, comprising:
By the eye movement data with and the compatible visual fatigue threshold value of current environment intensity of illumination be compared, according to comparing
As a result determine whether driver is in a state of fatigue.
Second aspect, the embodiment of the present application also provides a kind of monitoring device of fatigue driving, which includes:
Infrared image obtains module, for continuously acquiring the infrared image of driver's eye by infrared camera；
Eye movement data determining module, for determining the eye movement data of driver according to the infrared image continuously acquired；
Fatigue state judgment module, for the eye movement data to be compared with the visual fatigue threshold value being previously obtained, root
Determine whether driver is in a state of fatigue according to comparison result.
Further, described device further include:
Alarm modules are used to then generate alarm command if it is determined that driver is in a state of fatigue, so that alert device is sent out
Alarm prompt tone out.
Further, described device further includes visual fatigue threshold determination module, and the visual fatigue threshold determination module includes:
Big data acquiring unit, the big data of the eye movement data for obtaining driver；
Visual fatigue Threshold Analysis unit, for the big data according to the eye movement data of driver, analysis obtains visual fatigue
Threshold value.
Further, the big data acquiring unit is specifically used for:
It obtains in the normal driving eye movement data, fatigue driving eye movement data and close sleep eye movement data of preset quantity
Show parameter；Wherein, when the performance parameter includes: frequency of wink, direction of gaze and watches duration, twitching of the eyelid frequency and unit attentively
At least one of closure duration of interior eyes；
Correspondingly, the visual fatigue Threshold Analysis unit is specifically used for:
According to the arrangement to normal driving eye movement data, fatigue driving eye movement data and close sleep eye movement data, determine
Difference meets preset condition extremely in normal driving eye movement data and fatigue driving eye movement data and the eye movement data of close sleep
Few species diversity shows parameter；
Determine the visual fatigue threshold value of at least one difference performance parameter.
Further, described device further include:
Intensity of illumination obtains module, for obtaining current environment intensity of illumination；
Correspondingly, the fatigue state judgment module, is specifically used for:
By the eye movement data with and the compatible visual fatigue threshold value of current environment intensity of illumination be compared, according to comparing
As a result determine whether driver is in a state of fatigue.
The third aspect, the embodiment of the present application provide a kind of computer readable storage medium, are stored thereon with computer journey
Sequence realizes the monitoring method of the fatigue driving as described in the embodiment of the present application when the program is executed by processor.
Fourth aspect, the embodiment of the present application provide a kind of electronic equipment, including memory, processor and are stored in storage
It can realize on device and when the computer program of processor operation, the processor execute the computer program as the application is real
Apply the monitoring method of fatigue driving described in example.
Technical solution provided by the embodiment of the present application continuously acquires the infrared of driver's eye by infrared camera
Image；The eye movement data of driver is determined according to the infrared image continuously acquired；By the eye movement data be previously obtained
Visual fatigue threshold value is compared, and determines whether driver is in a state of fatigue according to comparison result.By using the application institute
The effect for improving the safety of vehicle drive may be implemented in the technical solution of offer.
Detailed description of the invention
Fig. 1 is the flow chart of the monitoring method for the fatigue driving that the embodiment of the present application one provides；
Fig. 2 is the flow chart of the monitoring method for the fatigue driving that the embodiment of the present application two provides；
Fig. 3 is the structural schematic diagram of the monitoring device for the fatigue driving that the embodiment of the present application three provides；
Fig. 4 is the structural schematic diagram for a kind of electronic equipment that the embodiment of the present application five provides.
Specific embodiment
The application is described in further detail with reference to the accompanying drawings and examples.It is understood that this place is retouched
The specific embodiment stated is used only for explaining the application, rather than the restriction to the application.It also should be noted that in order to just
Part relevant to the application is illustrated only in description, attached drawing rather than entire infrastructure.
It should be mentioned that some exemplary embodiments are described as before exemplary embodiment is discussed in greater detail
The processing or method described as flow chart.Although each step is described as the processing of sequence by flow chart, many of these
Step can be implemented concurrently, concomitantly or simultaneously.In addition, the sequence of each step can be rearranged.When its operation
The processing can be terminated when completion, it is also possible to have the additional step being not included in attached drawing.The processing can be with
Corresponding to method, function, regulation, subroutine, subprogram etc..
Embodiment one
Fig. 1 is the flow chart of the monitoring method for the fatigue driving that the embodiment of the present application one provides, and the present embodiment is applicable to
The case where driving condition of driver is monitored, this method fatigue driving as provided by the embodiment of the present application
Monitoring device executes, which can be realized by the mode of software and/or hardware, and can be integrated in intelligent monitoring device and
In the electronic equipments such as other intelligent terminals.
As shown in Figure 1, the monitoring method of the fatigue driving includes:
S110, the infrared image that driver's eye is continuously acquired by infrared camera.
Wherein, infrared camera can be set in the front of driver's cabin, and the other positions in driver's cabin also can be set,
The face-image of user is mainly acquired using infrared camera, and then the infrared figure of eye of user is obtained from face-image
Picture.The power supply of infrared camera can be above the power supply unit of connection and vehicle, infrared camera can driver into
Row obtains the face-image of driver during driving.
In the present embodiment, the infrared image of the eye of the available driver of infrared camera, can also obtain view
Frequently, then by each frame image in video by image recognition means determine the infrared image of the eye of driver.Wherein, from
The infrared image that eye is obtained in face-image can be realized by image recognition and processing technique.
In the present embodiment, be using the reason of infrared camera: the temperature of human eye is higher than absolute temperature (- 273 DEG C),
With movement and eyeball mechanism difference, it there is molecule there are other eyeball tissue parts such as pupil and atom be random
Movement, surface just constantly infrared radiation.Infrared ray is a kind of electromagnetic wave, its wave-length coverage is 0.78~1000 μm,
Not for seen in human eye, it reflects the infrared radiation field of body surface, i.e. temperature field.Object temperature is different, and what is given off is infrared
Heat input is different, and temperature is higher, and the infrared energy given off is bigger.According to eye movement, the variation such as pupil size can be given off not
Same infrared energy.
S120, the eye movement data that driver is determined according to the infrared image continuously acquired.
Wherein, the eye movement data of driver includes but is not limited to frequency of wink, direction of gaze and watches duration, twitching of the eyelid attentively frequently
Rate and in the unit time eyes closure duration, can be carried out based on one such or is a variety of in the present embodiment
The analysis of eye movement data.Wherein, frequency of wink can be the number of winks of driver in the unit time；Direction of gaze and watch attentively
Duration can be driver and watch duration attentively to some angle in driving procedure；Twitching of the eyelid frequency can be in the unit time
The number of twitching of the eyelid event occurs for interior driver；The closure duration of eyes can be in one minute in unit time, driver
Member's time span of eyes closed every time it is cumulative, wherein can the eyes of driver relative to 20% opened completely with
Under be determined as driver's eyes closed.In the present embodiment, driver can be determined by the infrared image continuously acquired
Eye movement data.
S130, the eye movement data is compared with the visual fatigue threshold value being previously obtained, is driven according to comparison result determination
Whether in a state of fatigue sail personnel.
In the present embodiment, the fatigue threshold being previously obtained, which can be, in advance counts the eye movement data of preset quantity
What analysis obtained, it can also be and machine learning is carried out according to the history eye movement data to current driver, obtain driver
When eye movement data shows as fatigue driving, when can show as normal driving.It is tired according to currently available eye movement data and view
Labor threshold value is compared, so that it may determine whether driver is in a state of fatigue.
In the present embodiment, optionally, the eye movement data is being compared with the visual fatigue threshold value being previously obtained, root
Before determining whether driver is in a state of fatigue according to comparison result, the method also includes: obtain the eye movement of driver
The big data of data；According to the big data of the eye movement data of driver, analysis obtains visual fatigue threshold value.
Wherein, the big data of the eye movement data of the driver of acquisition can be in daily different time, to different
What the eye movement data in the driving procedure of driver was summarized, it can also be in advance by driver according to current
State demarcation is normal driving, fatigue driving and close to three kinds of states of sleep, and acquires driver's under every kind of state
Optical data, the benefit being arranged in this way are available with given data to find the difference of eye movement data under the various states of driver
It is different.Eye movement data can also be obtained using random, and school is carried out to obtained visual fatigue threshold value using above-mentioned given data
Just, to obtain more accurate visual fatigue threshold value.In the present embodiment, the benefit being arranged in this way is obtained using big data
Whether visual fatigue threshold value is more accurate, significantly more efficient can be monitored in fatigue driving state to driver, can
Play the effect of auxiliary driver's safe driving.
In the present embodiment, optionally, the eye movement data is being compared with the visual fatigue threshold value being previously obtained, root
Before determining whether driver is in a state of fatigue according to comparison result, the method also includes: it is strong to obtain current environment illumination
Degree；Correspondingly, the eye movement data is compared with the visual fatigue threshold value being previously obtained, driver is determined according to comparison result
Whether member in a state of fatigue, comprising: by the eye movement data with and the compatible visual fatigue threshold value of current environment intensity of illumination
It is compared, determines whether driver is in a state of fatigue according to comparison result.
Wherein intensity of illumination can be obtained by intensity of illumination sensor, the big of the pupil to driver can also be passed through
The small intensity of illumination identified to determine current driver's local environment.In the present embodiment, visual fatigue threshold can be being determined
The environment illumination intensity that driver is determined during value, classifies to different intensities of illumination, and calculate separately difference
Visual fatigue threshold value within the scope of intensity of illumination.And in the use process of this programme, the current environment of driver is obtained
Intensity of illumination, then can be with visual fatigue threshold value corresponding to current light intensity, the benefit being arranged in this way can be more quasi-
Whether true determination driver is in a state of fatigue.In the technical scheme, it can obtain within the scope of all intensities of illumination
Visual fatigue threshold value after, set a standard intensity of illumination, and the visual fatigue threshold value under the standard intensity of illumination is set as
Level threshold value, then the difference or multiple that obtain between the level threshold value under each intensity of illumination range and the normal intensity are closed
System, and then obtain the visual fatigue threshold value under different illumination intensity environment.
Technical solution provided by the embodiment of the present application continuously acquires the infrared of driver's eye by infrared camera
Image；The eye movement data of driver is determined according to the infrared image continuously acquired；By the eye movement data be previously obtained
Visual fatigue threshold value is compared, and determines whether driver is in a state of fatigue according to comparison result.By using the application institute
The effect for improving the safety of vehicle drive may be implemented in the technical solution of offer.
On the basis of above-mentioned each technical solution, optionally, by the eye movement data and the visual fatigue threshold that is previously obtained
Value is compared, after determining whether driver is in a state of fatigue according to comparison result, the method also includes: if it is determined that
Driver is in a state of fatigue, then generates alarm command, so that alert device sounds an alarm prompt tone.Wherein alert device can
To be vehicle-mounted sound box, prompt tone can be sounded an alarm by vehicle audio to prompt driver to be currently in fatigue driving
State, if need to suspend to drive and rest etc..In the present embodiment, the broadcasting of alarm sounds sound is carried out by vehicle-mounted sound box
When can preferably close other sound, such as broadcast sounds, play music etc., the benefit being arranged in this way is can to allow user's energy
It is enough to have enough attention to alarm sounds sound.
Embodiment two
Fig. 2 is the flow chart of the monitoring method for the fatigue driving that the embodiment of the present application two provides.The present embodiment is in above-mentioned reality
It is specific to optimize on the basis of applying example are as follows: the big data of the eye movement data for obtaining driver, comprising:
It obtains in the normal driving eye movement data, fatigue driving eye movement data and close sleep eye movement data of preset quantity
Show parameter；Wherein, when the performance parameter includes: frequency of wink, direction of gaze and watches duration, twitching of the eyelid frequency and unit attentively
At least one of closure duration of interior eyes；Correspondingly, according to the big data of the eye movement data of driver, analysis is obtained
Visual fatigue threshold value, comprising: according to the whole of normal driving eye movement data, fatigue driving eye movement data and close sleep eye movement data
Reason determines normal driving eye movement data and fatigue driving eye movement data and meets default item close to difference in the eye movement data of sleep
At least one difference of part shows parameter；Determine the visual fatigue threshold value of at least one difference performance parameter.
As shown in Fig. 2, the monitoring method of the fatigue driving includes:
S210, the normal driving eye movement data for obtaining preset quantity, fatigue driving eye movement data and close sleep eye movement number
Performance parameter in；Wherein, the performance parameter include: frequency of wink, direction of gaze and watch attentively duration, twitching of the eyelid frequency and
At least one of the closure duration of eyes in unit time.
Wherein, preset quantity can be 1,000,10,000, even more data, and normal driving eye movement data can be with
It is eye movement data of the driver in normal driving, fatigue driving eye movement data can be driver in fatigue driving
In the case of eye movement data, close to sleep eye movement data can be driver it is extremely tired, close to sleep driving situation under
Eye movement data.In the technical scheme, normal driving eye movement data and fatigue driving eye movement data can be chosen to visual fatigue
Threshold value is determined, and the benefit increased close to sleep eye movement data is can not only to verify to visual fatigue threshold value, can be with
The state of current driver is further discriminated between in the case where fatigue driving, if it is determined that the state of current driver is pole
Degree fatigue then can be already close to sleep state and directly generate braking, even flame-out control instruction of slowing down, to control vehicle
It is out of service, in this way can to avoid driver because lead to not make road conditions correct reaction close to sleep,
There is the danger of driving accident.
Wherein, when the performance parameter includes: frequency of wink, direction of gaze and watches duration, twitching of the eyelid frequency and unit attentively
At least one of closure duration of interior eyes.Above-mentioned at least one can be obtained in the state that driver is in different
Kind performance parameter.At least one performance parameter can be it is pre-set, be also possible to by subsequent step determine, at three kinds
Between state show difference it is maximum one or more performance parameter, in this way can by obtain eye movement data in this or
The multiple performance parameters of person are distinguished to whether driver is under fatigue driving state.
The arrangement of S220, basis to normal driving eye movement data, fatigue driving eye movement data and close sleep eye movement data,
It determines normal driving eye movement data and fatigue driving eye movement data and meets preset condition close to difference in the eye movement data of sleep
At least one difference show parameter.
Wherein, meeting preset condition is that can distinguish to the eye movement data of the driver under different conditions, example
Such as by taking frequency of wink as an example, under normal driving condition, the frequency of wink of driver is 8-10 times per minute, and in fatigue
The frequency of wink of driver under driving condition is 4-6 time per minute, then the difference of frequency of wink meets preset condition, can be with
Parameter is showed using frequency of wink as a species diversity.It should be understood that if the closure duration of eyes can also be in the unit time
There is specific difference in the state of difference, then the closure duration of eyes in the unit time can also be determined as a species diversity table
Existing parameter.
S230, the visual fatigue threshold value for determining at least one difference performance parameter.
In conjunction with above-mentioned example, it can determine that the visual fatigue threshold value of this difference of frequency of wink performance parameter is 7 times per minute.
S240, the infrared image that driver's eye is continuously acquired by infrared camera.
S250, the eye movement data that driver is determined according to the infrared image continuously acquired.
S260, the eye movement data is compared with the visual fatigue threshold value being previously obtained, is driven according to comparison result determination
Whether in a state of fatigue sail personnel.
In this course, the specific number of the difference performance parameter determined in available eye movement data by above-mentioned steps
Value, after obtaining this numerical value, the eye movement data can be compared with the visual fatigue being previously obtained threshold value, determined and driven
Whether personnel are in a state of fatigue.
It is worth noting that in the present embodiment, S210-S230 can be carried out in the arbitrary process before S260, S240
It is not limited to only carry out after S210-S230 with S250.
The present embodiment on the basis of the above embodiments, provides a kind of method of determining visual fatigue threshold value, is arranged in this way
Benefit be that the accuracy of visual fatigue threshold value can be improved, to determine whether driver is in fatigue driving state and provides reliably
Judgment basis, improve the accuracy of fatigue driving monitoring.
Embodiment three
Fig. 3 is the structural schematic diagram of the monitoring device for the fatigue driving that the embodiment of the present application three provides.As shown in figure 3, institute
State the monitoring device of fatigue driving, comprising:
Infrared image obtains module 310, for continuously acquiring the infrared image of driver's eye by infrared camera；
Eye movement data determining module 320, for determining the eye movement data of driver according to the infrared image continuously acquired；
Fatigue state judgment module 330, for the eye movement data to be compared with the visual fatigue threshold value being previously obtained,
Determine whether driver is in a state of fatigue according to comparison result.
Technical solution provided by the embodiment of the present application continuously acquires the infrared of driver's eye by infrared camera
Image；The eye movement data of driver is determined according to the infrared image continuously acquired；By the eye movement data be previously obtained
Visual fatigue threshold value is compared, and determines whether driver is in a state of fatigue according to comparison result.By using the application institute
The effect for improving the safety of vehicle drive may be implemented in the technical solution of offer.
On the basis of above-mentioned each technical solution, optionally, described device further include:
Alarm modules are used to then generate alarm command if it is determined that driver is in a state of fatigue, so that alert device is sent out
Alarm prompt tone out.
On the basis of above-mentioned each technical solution, optionally, described device further includes visual fatigue threshold determination module, described
Visual fatigue threshold determination module includes:
Big data acquiring unit, the big data of the eye movement data for obtaining driver；
Visual fatigue Threshold Analysis unit, for the big data according to the eye movement data of driver, analysis obtains visual fatigue
Threshold value.
On the basis of above-mentioned each technical solution, optionally, the big data acquiring unit is specifically used for:
It obtains in the normal driving eye movement data, fatigue driving eye movement data and close sleep eye movement data of preset quantity
Show parameter；Wherein, when the performance parameter includes: frequency of wink, direction of gaze and watches duration, twitching of the eyelid frequency and unit attentively
At least one of closure duration of interior eyes；
Correspondingly, the visual fatigue Threshold Analysis unit is specifically used for:
According to the arrangement to normal driving eye movement data, fatigue driving eye movement data and close sleep eye movement data, determine
Difference meets preset condition extremely in normal driving eye movement data and fatigue driving eye movement data and the eye movement data of close sleep
Few species diversity shows parameter；
Determine the visual fatigue threshold value of at least one difference performance parameter.
On the basis of above-mentioned each technical solution, optionally, described device further include:
Intensity of illumination obtains module, for obtaining current environment intensity of illumination；
Correspondingly, the fatigue state judgment module, is specifically used for:
By the eye movement data with and the compatible visual fatigue threshold value of current environment intensity of illumination be compared, according to comparing
As a result determine whether driver is in a state of fatigue.
Method provided by the application any embodiment can be performed in the said goods, has the corresponding functional module of execution method
And beneficial effect.
Example IV
The embodiment of the present application also provides a kind of storage medium comprising computer executable instructions, and the computer is executable
It instructs when being executed by computer processor for executing a kind of monitoring method of fatigue driving, this method comprises:
The infrared image of driver's eye is continuously acquired by infrared camera；
The eye movement data of driver is determined according to the infrared image continuously acquired；
The eye movement data is compared with the visual fatigue threshold value being previously obtained, driver is determined according to comparison result
It is whether in a state of fatigue.
Storage medium --- any various types of memory devices or storage equipment.Term " storage medium " is intended to wrap
It includes: install medium, such as CD-ROM, floppy disk or magnetic tape equipment；Computer system memory or random access memory, such as
DRAM, DDR RAM, SRAM, EDO RAM, Lan Basi (Rambus) RAM etc.；Nonvolatile memory, such as flash memory, magnetic medium
(such as hard disk or optical storage)；Register or the memory component of other similar types etc..Storage medium can further include other
Memory of type or combinations thereof.In addition, storage medium can be located at program in the computer system being wherein performed, or
It can be located in different second computer systems, second computer system is connected to computer by network (such as internet)
System.Second computer system can provide program instruction to computer for executing.Term " storage medium " may include can
To reside in different location two or more storage mediums of (such as in the different computer systems by network connection).
Storage medium can store the program instruction (such as being implemented as computer program) that can be performed by one or more processors.
Certainly, a kind of storage medium comprising computer executable instructions, computer provided by the embodiment of the present application
The policer operation for the fatigue driving that executable instruction is not limited to the described above can also be performed the application any embodiment and be provided
Fatigue driving monitoring method in relevant operation.
Embodiment five
The embodiment of the present application provides a kind of electronic equipment, can integrate in the electronic equipment provided by the embodiments of the present application tired
Please the monitoring device sailed.Fig. 4 is the structural schematic diagram for a kind of electronic equipment that the embodiment of the present application five provides.As shown in figure 4,
Present embodiments provide a kind of electronic equipment 400 comprising: one or more processors 420；Storage device 410, for storing
One or more programs, when one or more of programs are executed by one or more of processors 420, so that one
Or multiple processors 420 realize the monitoring method of fatigue driving provided by the embodiment of the present application, this method comprises:
The infrared image of driver's eye is continuously acquired by infrared camera；
The eye movement data of driver is determined according to the infrared image continuously acquired；
The eye movement data is compared with the visual fatigue threshold value being previously obtained, driver is determined according to comparison result
It is whether in a state of fatigue.
Certainly, it will be understood by those skilled in the art that processor 420 can also realize that the application any embodiment is provided
Fatigue driving monitoring method technical solution.
The electronic equipment 400 that Fig. 4 is shown is only an example, should not function and use scope to the embodiment of the present application
Bring any restrictions.
As shown in figure 4, the electronic equipment 400 includes processor 420, storage device 410, input unit 430 and output dress
Set 440；The quantity of processor 420 can be one or more in electronic equipment, in Fig. 4 by taking a processor 420 as an example；Electronics
Processor 420, storage device 410, input unit 430 and output device 440 in equipment can pass through bus or other modes
It connects, in Fig. 4 for being connected by bus 450.
Storage device 410 is used as a kind of computer readable storage medium, and it is executable to can be used for storing software program, computer
Program and module, such as the corresponding program instruction of the monitoring method of the fatigue driving in the embodiment of the present application.
Storage device 410 can mainly include storing program area and storage data area, wherein storing program area can store operation
Application program needed for system, at least one function；Storage data area, which can be stored, uses created number according to electronic equipment
According to etc..In addition, storage device 410 may include high-speed random access memory, it can also include nonvolatile memory, such as
At least one disk memory, flush memory device or other non-volatile solid state memory parts.In some instances, storage dress
Setting 410 can further comprise the memory remotely located relative to processor 420, these remote memories can be connected by network
It connects.The example of above-mentioned network includes but is not limited to internet, intranet, local area network, mobile radio communication and combinations thereof.
Input unit 430 can be used for receiving number, character information or the voice messaging of input, and generation and electronic equipment
User setting and function control related key signals input.Output device 440 may include the equipment such as display screen, loudspeaker.
The effect for improving the safety of vehicle drive may be implemented in electronic equipment provided by the embodiments of the present application.
Monitoring device, storage medium and the electronic equipment of the fatigue driving provided in above-described embodiment can be performed the application and appoint
The monitoring method of fatigue driving provided by embodiment of anticipating has and executes the corresponding functional module of this method and beneficial effect.Not
The technical detail of detailed description in the above-described embodiments, reference can be made to the monitoring of fatigue driving provided by the application any embodiment
Method.
Note that above are only the preferred embodiment and institute's application technology principle of the application.It will be appreciated by those skilled in the art that
The application is not limited to specific embodiment described here, be able to carry out for a person skilled in the art it is various it is apparent variation,
The protection scope readjusted and substituted without departing from the application.Therefore, although being carried out by above embodiments to the application
It is described in further detail, but the application is not limited only to above embodiments, in the case where not departing from the application design, also
It may include more other equivalent embodiments, and scope of the present application is determined by the scope of the appended claims.
Claims (10)
1. a kind of monitoring method of fatigue driving characterized by comprising
The infrared image of driver's eye is continuously acquired by infrared camera；
The eye movement data of driver is determined according to the infrared image continuously acquired；
The eye movement data is compared with the visual fatigue threshold value being previously obtained, whether driver is determined according to comparison result
It is in a state of fatigue.
2. the method according to claim 1, wherein by the eye movement data and the visual fatigue threshold that is previously obtained
Value is compared, after determining whether driver is in a state of fatigue according to comparison result, the method also includes:
If it is determined that driver is in a state of fatigue, then alarm command is generated, so that alert device sounds an alarm prompt tone.
3. the method according to claim 1, wherein by the eye movement data and the visual fatigue threshold that is previously obtained
Value is compared, before determining whether driver is in a state of fatigue according to comparison result, the method also includes:
Obtain the big data of the eye movement data of driver；
According to the big data of the eye movement data of driver, analysis obtains visual fatigue threshold value.
4. according to the method described in claim 3, it is characterized in that, it is described obtain driver eye movement data big data,
Include:
Obtain the performance in the normal driving eye movement data, fatigue driving eye movement data and close sleep eye movement data of preset quantity
Parameter；Wherein, the performance parameter includes: frequency of wink, direction of gaze and watches duration, twitching of the eyelid frequency attentively and in the unit time
At least one of closure duration of eyes；
Correspondingly, analysis obtains visual fatigue threshold value according to the big data of the eye movement data of driver, comprising:
According to the arrangement to normal driving eye movement data, fatigue driving eye movement data and close sleep eye movement data, determine normal
It drives eye movement data and fatigue driving eye movement data and meets at least the one of preset condition close to difference in the eye movement data of sleep
Species diversity shows parameter；
Determine the visual fatigue threshold value of at least one difference performance parameter.
5. the method according to claim 1, wherein by the eye movement data and the visual fatigue threshold that is previously obtained
Value is compared, before determining whether driver is in a state of fatigue according to comparison result, the method also includes:
Obtain current environment intensity of illumination；
Correspondingly, the eye movement data is compared with the visual fatigue threshold value being previously obtained, is determined and driven according to comparison result
Whether personnel are in a state of fatigue, comprising:
By the eye movement data with and the compatible visual fatigue threshold value of current environment intensity of illumination be compared, according to comparison result
Determine whether driver is in a state of fatigue.
6. a kind of monitoring device of fatigue driving characterized by comprising
Infrared image obtains module, for continuously acquiring the infrared image of driver's eye by infrared camera；
Eye movement data determining module, for determining the eye movement data of driver according to the infrared image continuously acquired；
Fatigue state judgment module, for the eye movement data to be compared with the visual fatigue threshold value being previously obtained, according to than
Relatively result determines whether driver is in a state of fatigue.
7. device according to claim 6, which is characterized in that described device further include:
Alarm modules are used to then generate alarm command if it is determined that driver is in a state of fatigue, so that alert device issues police
Report prompt tone.
8. device according to claim 6, which is characterized in that described device further includes visual fatigue threshold determination module, institute
Stating visual fatigue threshold determination module includes:
Big data acquiring unit, the big data of the eye movement data for obtaining driver；
Visual fatigue Threshold Analysis unit, for the big data according to the eye movement data of driver, analysis obtains visual fatigue threshold value.
9. a kind of computer readable storage medium, is stored thereon with computer program, which is characterized in that the program is held by processor
The monitoring method of fatigue driving according to any one of claims 1 to 5 is realized when row.
10. a kind of electronic equipment, including memory, processor and storage are on a memory and can be in the computer of processor operation
Program, which is characterized in that the processor is realized according to any one of claims 1 to 5 when executing the computer program
The monitoring method of fatigue driving.
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