CN205983875U - Early warning system passes in intersection based on computer vision - Google Patents
Early warning system passes in intersection based on computer vision Download PDFInfo
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- CN205983875U CN205983875U CN201620954440.5U CN201620954440U CN205983875U CN 205983875 U CN205983875 U CN 205983875U CN 201620954440 U CN201620954440 U CN 201620954440U CN 205983875 U CN205983875 U CN 205983875U
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Abstract
The utility model discloses an early warning system passes in intersection based on computer vision, including front -end collection module, video information processing module, internet transmission module, monitoring module and early warning module, the front -end collection module includes panoramic camera, feature camera and video coding equipment, panoramic camera, feature camera are connected with video coding equipment respectively, set up virtual coil at intersection location, and virtual coil is aimed at to the visual field of feature camera, and the visual field of panoramic camera includes intersection all directions visual angle. The utility model discloses need not bury the underground with equipment, installation and maintenance cost are lower.
Description
Technical field
This utility model is related to a kind of traffic safety early warning field and in particular to a kind of crossroad based on computer vision
The current early warning system of mouth.
Background technology
In construction site road, especially intersection, is the most dangerous region in road network, because construction site is
Open up, signal lighties and road instruction line are rare, and pedestrian does not concentrate, Construction traffic great majority are oversize vehicle, along with outer temporarily
Carry out sailing into of vehicle, become the Multiple trauma of vehicle accident.Pedestrian, vehicle pass through intersection when, often due to construction building
Thing leads to driver to produce vision dead zone with pedestrian, and external vehicle travels violates construction management regulation to construction specific road section, with
And car speed exceedes construction section safety value, these factors are likely to cause vehicle accident, in construction section traffic signal
Lamp is rare, it is especially desirable to note the generation of traffic safety hidden danger in the case of road is irregular.Traditional traffic prewarning system is simultaneously
It is not properly suited for the such geographical conditions in job site, and early warning range is not wide, technological means are single.
Utility model content
In order to overcome the shortcoming of prior art presence and a kind of not enough, this utility model friendship based on computer vision of offer
Cross road mouth passes through early warning system, carries out pre- when the vehicle being particularly applicable in construction site intersection passing is with pedestrian's abnormal conditions
Alert, the generation trying to forestall traffic accidents.
This utility model adopts the following technical scheme that：
A kind of intersection passing early warning system based on computer vision, at front end acquisition module, video information
Reason module, network transmission module, monitoring module and warning module；
Described front end acquisition module includes panoramic camera, feature video camera and video encoder, described panoramic shooting
Machine, feature video camera are connected with video encoder respectively, arrange virtual coil, feature video camera in intersection specific region
Visual field align virtual coil, the visual field of panoramic camera includes intersection all directions visual angle.
Described video information process module, specially industrial computer, described industrial computer pass through network transmission module respectively with prison
Control module and warning module connect, and described video encoder is connected with industrial computer.
Described monitoring module is made up of information terminal display device and database server.
Described warning module includes LED display.
Model IPC610 of described industrial computer.
Described panoramic camera and feature camera pedestal are located at the top in crossroad or T-shaped road junction.
Described virtual coil is rectangle.
The beneficial effects of the utility model：
(1) effective district can dividing engineering truck and non-engineering truck, thus carrying out automatical and efficient supervision, being easy to difference
Vehicle take different measures of control, for job site safety management provide convenient；
(2) position of moving target subsequent time can be estimated, thus to swarming into job site prohibited area
The vehicle of probability sends alarm, thus avoiding the generation of dangerous situation；
(3) it is capable of detecting when vehicle and the pedestrian of current direction composition vision dead zone, and shows safety instruction information, allow and drive
The person of sailing has grace time to take deceleration or parking measure；
(4) vehicle being passed through in job site, no matter being Construction traffic or external vehicle, carrying out information system management, building
Vertical data base, stores its species by the moment of job site, vehicle, the information such as licence plate.
(5) it is used for detecting that the high-definition camera of construction site scene is erected at the overhead on road surface it is not necessary to imbed equipment
Underground, installs and maintenance cost is relatively low.
Brief description
Fig. 1 is the structural representation of the present invention；
Fig. 2 is the structure in-site installation figure of the embodiment of the present invention；
Fig. 3 is embodiment of the present invention LED display display content schematic diagram；
Fig. 4 is the workflow diagram of the present invention.
Specific embodiment
With reference to embodiment and accompanying drawing, this utility model is described in further detail, but reality of the present utility model
Apply mode not limited to this.
Embodiment
As shown in Figure 1, Figure 2 and Figure 3, a kind of intersection passing early warning system based on computer vision implementing the present invention
System, including front end acquisition module, video information process module, network transmission module, monitoring module and warning module；
Described front end acquisition module includes panoramic camera 2, feature video camera 1 and video encoder, and described panorama is taken the photograph
Camera, feature video camera are connected with video encoder respectively, arrange virtual coil in intersection specific region, and feature images
The visual field align virtual coil 7 of machine, the visual field of panoramic camera includes intersection all directions visual angle；
Described video information process module, specially industrial computer 3, described industrial computer pass through network transmission module respectively with prison
Control module and warning module connect, and described video encoder is connected with industrial computer.
Described monitoring module is made up of information terminal display device 5 and database server 6；
Described warning module includes LED display 8.
Model IPC610 of described industrial computer.
Model CSD-P6-SMD3535 of described LED display, double copies power line, resolution is in more than 720P.
Described network transmission module is wireless network transmissions equipment 4.
Described panoramic camera and feature video camera should be erected at aerial on cross or T-shaped road junction corner road surface.
In the present embodiment, virtual coil is rectangle.
The present embodiment includes two feature video cameras and a panoramic camera, and LED has two pieces of display screens, display letter
Breath can facilitate each road vehicle to observe with pedestrian, as shown in Figure 3.
The panoramic camera collection large-scale scene information in intersection simultaneously exports to industrial computer the place carrying out video image
Reason；Virtual coil is set in crossing intersection part specific region, the visual field be aligned crossing intersection part specific region of feature video camera sets
Put virtual coil, capture the high-definition image of vehicle and export and carry out image procossing to industrial computer；The software profit installed on industrial computer
Complete vehicle, the detection of pedestrian, tracking, classification, position anticipation, identification vehicle license with Video processing and mode identification technology
Number, storage information of vehicles, output early warning signal etc.；The outfan of signal has LED display, database server, information terminal
Display device.LED display is used for showing early warning information, and database server is used for storage by construction site intersection
Information of vehicles, information terminal display device is used for the monitored picture of real-time display intersection and the reality synchronous with monitored picture
The design sketch of the functions such as the detection of existing vehicle and pedestrian, tracking, classification, position anticipation, early warning.
As shown in figure 4, a kind of intersection passing method for early warning based on computer vision, comprise the steps：
The vehicle of S1 panoramic camera Real-time Collection intersection and the video image of walk, feature video capture
The close-up image of each vehicle in virtual coil；
S2 extracts moving target according to video image, generates moving target travel information and has been extracted according to close-up image
Whole vehicle license information, described moving target includes vehicle and pedestrian, and described travel information includes vehicles or pedestrians to be passed through to hand over
The time period of cross road mouth, the center-of-mass coordinate of vehicles or pedestrians and direct of travel.
Described vehicle license information is by carrying out License Plate, Character segmentation, character recognition and color to close-up image
Obtained from identification.
S2.1 sets up mixed Gauss model to the video image of intersection scene, extracts foreground target, generates two-value
The moving target foreground picture changed；
S2.2 counts each moving target pixel number and the image coordinate of pixel, calculates the figure of moving target barycenter
As coordinate
Wherein M, N represent the Breadth Maximum of certain moving target and height in image respectively, and i represents pixel in image
Abscissa, j represents the vertical coordinate of pixel in image, xijRepresent the abscissa value of pixel in moving target, yijRepresent motion
The ordinate value of target pixel points；
S2.3 calculates the motion vector of moving target according to the image coordinate of the barycenter of moving target in adjacent 20 two field pictures,
Determine the direct of travel of moving target by motion vector, direct of travel can carry out universal formulation according to the difference of intersection.
S3 classifies to moving target, draws classification results；
Described classification results include engineering truck, non-engineering truck and pedestrian, and concrete steps include：
S3.1 extracts the profile of moving target, and draws, according to profile, the boundary rectangle surrounding profile, according to moving target
The ratio of width to height of boundary rectangle tentatively distinguishes vehicle target and pedestrian target；
If the ratio of width to height of moving target boundary rectangle be less than the empirical value that sets then it is assumed that moving target now as
Pedestrian；
If the ratio of width to height of moving target boundary rectangle be more than the empirical value that sets then it is assumed that moving target now as
The adhesion pedestrian target of engineering truck, non-engineering truck or multiple pedestrian's Adhesion formation；
S3.2, according to the histograms of oriented gradients feature of moving target, sets up grader mould using the algorithm of support vector machine
Type is distinguishing engineering truck, non-engineering truck and adhesion pedestrian target.
S3.2.1 collects the image of engineering truck, non-engineering truck and adhesion pedestrian, the size of unified image, sets up respectively
Sample set, if engineering truck sample set be set A, non-engineering truck sample set be set B, adhesion pedestrian sample collection be set C；
S3.2.2 using the set A in S3.2.1 and set B as just collecting, set C as negative collection, extract respectively and just collecting and bearing
The histograms of oriented gradients feature of collection, as the input of algorithm of support vector machine, generates sorter model one, described grader mould
Type one is used for carrying out two classification to vehicle with pedestrian；
S3.2.3 using the set A in S3.2.1 as just collecting, set B as negative collection, extract the side just collecting with negative collection respectively
To histogram of gradients feature as the input of algorithm of support vector machine, generate sorter model two, described sorter model dual-purpose
In two classification are carried out to engineering truck and non-engineering truck；
S3.2.4 extracts the correspondence original RGB figure of each moving target according to the boundary rectangle of each moving target extracting
Picture, extracts the histograms of oriented gradients feature of each moving target original RGB image；
The histograms of oriented gradients feature of each moving target original RGB image that S3.2.5 extracts is successively as grader
The input of model one, if output result is just then it is assumed that moving target now is vehicle, if output result is negative,
Think that moving target now is adhesion pedestrian；
The histograms of oriented gradients feature of the moving target that classification results in S3.2.5 are vehicle by S3.2.6 is as classification
The input of device model two, if output result is just then it is assumed that moving target now is engineering truck, if output result is
Bear then it is assumed that moving target now is non-engineering truck.
S4, according to classification results and travel information, calculates the gait of march of vehicle；
S4.1, according to classification results, chooses vehicle target as the object of calculating speed, does not calculate the gait of march of pedestrian；
S4.2, in video image, arranges two virtual detection lines by perpendicular to vehicle target direct of travel；Measure two again
On the corresponding real road of bar virtual detection line apart from △ D；Calculate vehicle in real time video image and successively reach two virtual inspections
The frame number F of survey line；
S4.3 according to sample frequency f of video image, on the corresponding real roads of two virtual detection lines apart from △ D, car
Successively reach the frame number F of two virtual detection lines, calculate gait of march V of vehicle：
S5 stores information of vehicles, the gait of march according to vehicle and the travel information by intersection, predicts described fortune
The center-of-mass coordinate of moving-target subsequent time position；
Described S5 specifically adopts the center-of-mass coordinate of Kalman filtering algorithm predicted motion target subsequent time position.Karr
Graceful filtering is a kind of estimation of recurrence, is divided into forecast period and more new stage, and in forecast period, Kalman filtering algorithm uses works as
The estimation of front moment state, makes the estimation to subsequent time state；In the more new stage, Kalman filtering algorithm is using to next
The predictive value that the observation optimization of moment state obtains in forecast period, to obtain a more accurate new estimation value.
It is specially：
S5.1 obtains the center-of-mass coordinate of a upper moment moving target and systemic velocity in video image, sets up moving target position
The predictive equation put, that is,：
X (t+1 | t)=AX (t | t)+w (t+1)
In formula：X (t+1 | t) is the state vector of the subsequent time moving target being predicted using current time；X(t|t)
For current time optimal State Estimation vector；A is state-transistion matrix；W (t+1) be process noise it is assumed that be desired for zero white
Noise, its covariance matrix is Q (t+1)；
Translational speed v specific formula for calculation on image for the described moving target barycenter is as follows：
Wherein t is the time interval in two moment, and △ d is the distance of t time moving target barycenter movement.
S5.2：The covariance matrix of more new state X (t+1 | t)：
P (t+1 | t)=AP (t | t) AT+Q(t+1)
Wherein：P (t+1 | t) expression X (t+1 | t) corresponding covariance, P (t | t) expression X (t | t) corresponding covariance, AT
Represent the transposed matrix of A,
S5.3：The measured value of the moving target state according to subsequent time, in conjunction with the subsequent time moving target predicting
State vector, calculate the optimization estimated value X (t+1 | t+1) of subsequent time moving target state：
X (t+1 | t+1)=X (t+1 | t)+Kg (t+1) (Z (t+1)-HX (t+1 | t))
Wherein Z (t+1) is the measured value of moving target subsequent time state, and H is calculation matrix, and wherein Kg (t+1) is card
Germania gain：
Kg (t+1)=P (t+1 | t) HT/(HP(t+1|t)HT+R(t+1))
Wherein R (t+1) is measurement noise covariance matrix, HTTransposed matrix for H；
S5.4：Update the covariance matrix P (t+1 | t+1) of subsequent time moving target state X (t+1 | t+1)：
P (t+1 | t+1)=(I-Kg (t+1) H) P (t+1 | t)
Wherein I is unit matrix.
Described abnormal conditions mainly include the speed that the speed of vehicle specifies beyond job site, and non-engineering truck sails construction into
The special area at scene, the current direction between the vehicle of intersection passing and vehicle, between vehicle and pedestrian constitutes vision
Blind area, vehicle and vehicle, vehicle and pedestrian have the probability colliding；
The special area of described job site refers to the non-engineering truck section that No entry of construction site management regulation；
Warning module generates corresponding warning information according to the early warning signal that industrial computer exports, including following several situations：
(1) monitoring image of over-speed vehicles is shown on information terminal display device and sends early warning voice；(2) show in information terminal
On equipment, display is sailed the monitoring image of non-engineering truck of job site special area into and is sent early warning voice；(3) in information
Show on terminal unit and have scene image when colliding probability between vehicle and pedestrian, vehicle and vehicle and send early warning
Voice and in LED screen display reminding poster.
Fig. 2 is the LED information screen mounting structure schematic diagram of warning module in the embodiment of the present invention, such as the road scene of Fig. 1
Shown in schematic diagram, the current direction of vehicle and pedestrian leads to the appearance of vision dead zone due to the construction area of construction section, now
Warning module output early warning information, to LED display, reminds vehicle and pedestrian to take care.
Above-described embodiment is this utility model preferably embodiment, but embodiment of the present utility model be not subject to described
The restriction of embodiment, other any without departing from the change made under spirit of the present utility model and principle, modify, replace
Generation, combination, simplification, all should be equivalent substitute mode, are included within protection domain of the present utility model.
Claims (7)
1. a kind of intersection passing early warning system based on computer vision is it is characterised in that including front end acquisition module, regarding
Frequency message processing module, network transmission module, monitoring module and warning module；
Described front end acquisition module includes panoramic camera, feature video camera and video encoder, described panoramic camera, spy
Write video camera to be connected with video encoder respectively, virtual coil, the regarding of feature video camera are set in intersection specific region
Field align virtual coil, the visual field of panoramic camera includes intersection all directions visual angle.
2. intersection passing early warning system according to claim 1 is it is characterised in that described video information process mould
Block, specially industrial computer, described industrial computer is connected with monitoring module and warning module respectively by network transmission module, described regards
Frequency encoding device is connected with industrial computer.
3. intersection passing early warning system according to claim 1 is it is characterised in that described monitoring module is whole by information
End display device and database server are constituted.
4. intersection passing early warning system according to claim 1 is it is characterised in that described warning module includes LED
Display screen.
5. intersection passing early warning system according to claim 2 is it is characterised in that the model of described industrial computer
IPC610.
6. intersection passing early warning system according to claim 1 is it is characterised in that described panoramic camera and feature
Camera pedestal is located at the top in crossroad or T-shaped road junction.
7. intersection passing early warning system according to claim 1 is it is characterised in that described virtual coil is rectangle.
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| CN201620954440.5U CN205983875U (en) | 2016-08-26 | 2016-08-26 | Early warning system passes in intersection based on computer vision |
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| CN201620954440.5U CN205983875U (en) | 2016-08-26 | 2016-08-26 | Early warning system passes in intersection based on computer vision |
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| CF01 | Termination of patent right due to non-payment of annual fee | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20170222 Termination date: 20190826 |