CN109145852A - A kind of driver fatigue state recognition method for opening closed state based on eyes - Google Patents
A kind of driver fatigue state recognition method for opening closed state based on eyes Download PDFInfo
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- CN109145852A CN109145852A CN201811009416.4A CN201811009416A CN109145852A CN 109145852 A CN109145852 A CN 109145852A CN 201811009416 A CN201811009416 A CN 201811009416A CN 109145852 A CN109145852 A CN 109145852A
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- G—PHYSICS
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- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/50—Context or environment of the image
- G06V20/59—Context or environment of the image inside of a vehicle, e.g. relating to seat occupancy, driver state or inner lighting conditions
- G06V20/597—Recognising the driver's state or behaviour, e.g. attention or drowsiness
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- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/18—Eye characteristics, e.g. of the iris
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Abstract
The invention discloses a kind of driver fatigue state recognition methods that closed state is opened based on eyes, including step 1: acquisition driver's video simultaneously carries out sub-frame processing, determines driver's face location；Step 2: driver eye positions being determined using calculus of finite differences, and Corner Detection is carried out to the white of the eye and eyeball boundary based on Harris algorithm, the area S for exposing eyeball are determined, as S≤0.35S0When, S0The area of eyeball when opening completely for human eye, then human eye is in closed-eye state；Step 3: determining driving fatigue coefficient k；Step 4: as k≤15%, driver is in waking state；As 15% < k≤50%, driver is in level-one fatigue, should remind driver；As k > 50%, driver is in second level fatigue, should sound an alarm, if driver is reactionless, force to stop.Framing can be carried out to driver's driving video and extracts image, and determining eyeball area is to determine that human eye opens closed state, it is as a result more acurrate to determine driver fatigue state according to driving fatigue coefficient.
Description
Technical field
The present invention relates to driving safety technical fields, and more particularly, the present invention relates to one kind to open closed state based on eyes
Driver fatigue state recognition method.
Background technique
Nowadays driver fatigue detection technique is more and more mature, and fatigue detection method can be divided mainly into three classes: based on driving
The person's of sailing behavioural characteristic, the detection method based on physiological driver's parameter and based on vehicle behavior feature.It is special according to driving behavior
Sign is detected: the behavioural characteristic of driver mainly includes two aspect of facial characteristics variation and hand exercise.Facial characteristics is main
Including head pose, eye state and mouth state；Hand exercise mainly includes the dynamics and rotation angle for operating steering wheel.It drives
The person's of sailing physiological parameter mainly includes electroencephalogram, electrocardiogram etc., but driver need to wear corresponding experimental facilities when due to detection,
There is certain interference for manipulation automobile, therefore applies and be subject to certain restrictions.Vehicle behavior mainly pass through detection direction disk corner,
The parameters such as car speed and angle of turn.
It is carried out in tired judgement existing based on the variation of driver's facial characteristics, when being judged by mouth, mainly
It is identified according to the opening width of mouth, but mouth opening width is very big when driver speaks or laughs at, will affect detection
Effect, accuracy reduce；It is main to be identified according to frequency of nodding when based on head pose, it needs to establish the three-dimensional of head and sits
Mark, as basic point with body certain point, it is also necessary to carry out projective transformation, and it is sometimes tired when can also lateral deviation head, it is computationally intensive；
When based on eyes closed degree, be broadly divided into two methods: the black picture element of eyeball is converted and is carried out based on perclos criterion
The state recognition of eyes, above-mentioned three kinds of methods can only carry out tired judgement, in the form of a single.
Summary of the invention
The present invention has designed and developed a kind of driver fatigue state recognition method that closed state is opened based on eyes, can be to driving
The person's of sailing driving video carries out framing and extracts image, and determines eyeball area to determine that human eye opens closed state, according to driving fatigue
Coefficient determines driver fatigue state, as a result more acurrate.
Technical solution provided by the invention are as follows:
A kind of driver fatigue state recognition method for being opened closed state based on eyes, is included the following steps:
Step 1: acquisition driver's video simultaneously carries out sub-frame processing, determines driver's face location；
Step 2: driver eye positions being determined using calculus of finite differences, and based on Harris algorithm to the white of the eye and eyeball boundary
Corner Detection is carried out, the area S for exposing eyeball is determined, as S≤0.35S0When, S0The area of eyeball when being opened completely for human eye, then
Human eye is in closed-eye state；
Step 3: determining driving fatigue coefficient are as follows:
Work as T0When > 0,
Work as T0When < 0,
Work as T0When=0,
Wherein, T0For environment temperature, T is vehicle interior temperature, and α is rainfall, and β is snowfall, and G is uitraviolet intensity, f (v),
G (v) is velocity function, and v is speed, and k is driving fatigue coefficient, and e is the truth of a matter of natural logrithm, N1For eye closing frame number, N is sum
Frame number；
Step 4: as k≤15%, driver is in waking state；
As 15% < k≤50%, driver is in level-one fatigue, should remind driver；
As k > 50%, driver is in second level fatigue, should sound an alarm, if driver is reactionless, force to stop.
Preferably, it in the step 1, acquires driver's video and extracts every frame image, be based on after pretreatment
Adaboost algorithm determines driver's face location.
Preferably, it in the step 2, chooses driver's top half face image and carries out difference, and not move
Background image of the image of target as difference.
Preferably, described to include: to the white of the eye and eyeball boundary progress Corner Detection based on Harris algorithm
Every frame image I (x, y) is calculated in the gradient I of x and y both directionx,Iy,
In formula,For convolution；
Calculate image I (x, y) x and y both direction product,
Ixx=Ix 2,Iyy=Iy 2,Ixy=Ix·Iy；
Using Gaussian function to Ix 2,Iy 2,Ix·IyGauss weighting is carried out, elements A, B, C of matrix M is obtained,
In formula, w is Gaussian function；
The Harris response R of each pixel is calculated, and zero is set to the R less than a certain threshold value t,
R={ R:detM- α (traceM)2< t },
In formula, detM is the determinant of matrix M, and traceM is the straight mark of matrix M, and α is empirical；
Non-maxima suppression is carried out in neighborhood, and determines the angle point in image.
Preferably, it is described expose eyeball area determination include:
When human eye is just opened completely, the angle point of three white of the eye and eyeball boundary is determined, then eyeball when human eye is opened completely
Area S0Are as follows:
In formula, a, b, c are respectively the linear distance between adjacent corner points；
When eyes have certain closure, it is based on Harris algorithm, determines the point in upper eyelid Yu eyeball demarcation line, this
When eyeball area S are as follows:
In formula, linear distance of the h between upper eyelid and the point of eyeball demarcation line.
Preferably, when continuous 5 frame image does not detect angle point, judge that driver is in sleep state.
It is of the present invention the utility model has the advantages that
(1) driver fatigue state recognition method of the present invention that closed state is opened based on eyes, can be to driver
Driving video carries out framing and extracts image, and determines eyeball area to determine that human eye opens closed state, according to driving fatigue coefficient
Determine driver fatigue state, it is as a result more acurrate.
(2) the present invention is based on the detection that Harris algorithm carries out eyes, it can not only differentiate the state of driver, it can be with
Judge the direction of motion of driver head, can be to prepare to turn left or turn right according to head movement walking direction vehicle.And
The area of black eyeball need to only be calculated when judge by carrying out fatigue, and calculation amount is small, detection accuracy height, and the white of the eye and black eyeball
Gray scale difference is very big, small by external interference, improves the effect of detection.
Detailed description of the invention
Fig. 1 is the flow chart of the driver fatigue state recognition method of the present invention that closed state is opened based on eyes.
Specific embodiment
Present invention will be described in further detail below with reference to the accompanying drawings, to enable those skilled in the art referring to specification text
Word can be implemented accordingly.
As shown in Figure 1, the present invention provides a kind of driver fatigue state recognition method that closed state is opened based on eyes, including
Following steps:
Step 1: acquisition driver's video simultaneously carries out sub-frame processing, determines driver's face location:
Frame image every for driver's video extraction of acquisition, is pre-processed, and interference and the enhancing image of noise are reduced
Effect carries out the positioning of face using adaboost algorithm.
Step 2: driver eye positions are determined using calculus of finite differences:
When carrying out the positioning of eyes with calculus of finite differences, in order to reduce calculation amount and improve accuracy, according to point of face
Cloth feature, interception top half facial image carry out difference.A frame is selected not have moving target at the beginning of motion detection
Background image of the image as difference, occur that present image and background image is started to do difference when moving target, when
At the end of moving object detection, background image is updated, carries out difference again when next moving target occurs.The knot of difference
Fruit can remove a part of noise, and can remove the static background region unrelated with moving object detection, using Background
As update mechanism, the variation of background and light can also be adapted to a certain extent.After carrying out difference processing, difference image
In only leave moving target and partial noise, be filtered hot-tempered processing again at this time.
Step 3: and Corner Detection is carried out to the white of the eye and eyeball boundary based on Harris algorithm, it specifically includes:
Every frame image I (x, y) is calculated in the gradient I of x and y both directionx,Iy,
In formula,For convolution；
Calculate image I (x, y) x and y both direction product,
Ixx=Ix 2,Iyy=Iy 2,Ixy=Ix·Iy；
Using Gaussian function to Ix 2,Iy 2,Ix·IyGauss weighting is carried out, elements A, B, C of matrix M is obtained,
In formula, w is Gaussian function；
The Harris response R of each pixel is calculated, and zero is set to the R less than a certain threshold value t,
R={ R:detM- α (traceM)2< t },
In formula, detM is the determinant of matrix M, and traceM is the straight mark of matrix M, and α is empirical；
Non-maxima suppression is carried out in neighborhood, and determines the angle point (i.e. Local modulus maxima) in image, and mobile is small
Window is smaller, and the angle point of detection is more accurate, therefore selects 3*3 size.
Certainly, when continuous 5 frame image does not detect angle point, judge that driver is in sleep state.
Step 4: determine the area S for exposing eyeball:
When human eye is just opened completely, the angle point of three white of the eye and eyeball boundary is determined, then eyeball when human eye is opened completely
Area S0Are as follows:
In formula, a, b, c are respectively the linear distance between adjacent corner points；
When eyes have certain closure, it is based on Harris algorithm, determines the point in upper eyelid Yu eyeball demarcation line, this
When eyeball area S are as follows:
In formula, linear distance of the h between upper eyelid and the point of eyeball demarcation line.
As S≤0.35S0When, then human eye is in closed-eye state.
Step 5: determining driving fatigue coefficient are as follows:
Work as T0When > 0,
Work as T0When < 0,
Work as T0When=0,
Wherein, T0For environment temperature (DEG C), T is vehicle interior temperature (DEG C), and α is rainfall (m), and β is snowfall (m), and G is purple
Outside line intensity (between 0~15), f (v), g (v) are velocity function, and v is speed (km/h), and k is driving fatigue coefficient, and e is nature
The truth of a matter of logarithm, N1For eye closing frame number, N is total frame number.
Step 6: as k≤15%, driver is in waking state；
As 15% < k≤50%, driver is in level-one fatigue, should remind driver；
As k > 50%, driver is in second level fatigue, should sound an alarm, if driver is reactionless, force to stop.
The driver fatigue state recognition method of the present invention that closed state is opened based on eyes can drive driver
Video carries out framing and extracts image, and determines eyeball area to determine that human eye opens closed state, to determine according to driving fatigue coefficient
Driver fatigue state, it is as a result more acurrate.
The present invention is based on the detections that Harris algorithm carries out eyes, can not only differentiate the state of driver, can also sentence
The direction of motion of disconnected driver head can be prepared to turn left or turn right according to head movement walking direction vehicle.And into
Row fatigue need to only calculate the area of black eyeball when judging, calculation amount is small, and detection accuracy is high, and the ash of the white of the eye and black eyeball
Degree difference is very big, small by external interference, improves the effect of detection.
Although the embodiments of the present invention have been disclosed as above, but its is not only in the description and the implementation listed
With it can be fully applied to various fields suitable for the present invention, for those skilled in the art, can be easily
Realize other modification, therefore without departing from the general concept defined in the claims and the equivalent scope, the present invention is simultaneously unlimited
In specific details and legend shown and described herein.
Claims (6)
1. a kind of driver fatigue state recognition method for opening closed state based on eyes, which comprises the steps of:
Step 1: acquisition driver's video simultaneously carries out sub-frame processing, determines driver's face location；
Step 2: driver eye positions being determined using calculus of finite differences, and the white of the eye and eyeball boundary are carried out based on Harris algorithm
Corner Detection determines the area S for exposing eyeball, as S≤0.35S0When, S0The area of eyeball when being opened completely for human eye, then human eye
In closed-eye state；
Step 3: determining driving fatigue coefficient are as follows:
Work as T0When > 0,
Work as T0When < 0,
Work as T0When=0,
Wherein, T0For environment temperature, T is vehicle interior temperature, and α is rainfall, and β is snowfall, and G is uitraviolet intensity, f (v), g (v)
For velocity function, v is speed, and k is driving fatigue coefficient, and e is the truth of a matter of natural logrithm, N1For eye closing frame number, N is total frame
Number；
Step 4: as k≤15%, driver is in waking state；
As 15% < k≤50%, driver is in level-one fatigue, should remind driver；
As k > 50%, driver is in second level fatigue, should sound an alarm, if driver is reactionless, force to stop.
2. the driver fatigue state recognition method of closed state is opened based on eyes as described in claim 1, which is characterized in that institute
It states in step 1, acquire driver's video and extracts every frame image, driver face is determined based on adaboost algorithm after pretreatment
Position.
3. the driver fatigue state recognition method of closed state is opened based on eyes as described in claim 1, which is characterized in that institute
It states in step 2, chooses driver's top half face image and carry out difference, and using the image of not moving target as difference
Background image.
4. the driver fatigue state recognition method of closed state is opened based on eyes as claimed in claim 3, which is characterized in that institute
It states and includes: to the white of the eye and eyeball boundary progress Corner Detection based on Harris algorithm
Every frame image I (x, y) is calculated in the gradient I of x and y both directionx,Iy,
In formula,For convolution；
Calculate image I (x, y) x and y both direction product,
Ixx=Ix 2,Iyy=Iy 2,Ixy=Ix·Iy；
Using Gaussian function to Ix 2,Iy 2,Ix·IyGauss weighting is carried out, elements A, B, C of matrix M is obtained,
In formula, w is Gaussian function；
The Harris response R of each pixel is calculated, and zero is set to the R less than a certain threshold value t,
R={ R:detM- α (traceM)2< t },
In formula, detM is the determinant of matrix M, and traceM is the straight mark of matrix M, and α is empirical；
Non-maxima suppression is carried out in neighborhood, and determines the angle point in image.
5. the driver fatigue state recognition method of closed state is opened based on eyes as claimed in claim 4, which is characterized in that institute
State expose eyeball area determination include:
When human eye is just opened completely, the angle point of three white of the eye and eyeball boundary is determined, then the face of eyeball when human eye is opened completely
Product S0Are as follows:
In formula, a, b, c are respectively the linear distance between adjacent corner points；
When eyes have certain closure, it is based on Harris algorithm, determines the point in upper eyelid Yu eyeball demarcation line, at this time eye
The area S of ball are as follows:
In formula, linear distance of the h between upper eyelid and the point of eyeball demarcation line.
6. the driver fatigue state recognition method of closed state is opened based on eyes as claimed in claim 5, which is characterized in that when
When continuous 5 frame image does not detect angle point, judge that driver is in sleep state.
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| CN116469085A (en) * | 2023-03-30 | 2023-07-21 | 万联易达物流科技有限公司 | Monitoring method and system for risk driving behavior |
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