CN107067794A - A kind of indoor vehicle Position Fixing Navigation System and method based on Computer Vision - Google Patents
A kind of indoor vehicle Position Fixing Navigation System and method based on Computer Vision Download PDFInfo
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- CN107067794A CN107067794A CN201611019433.7A CN201611019433A CN107067794A CN 107067794 A CN107067794 A CN 107067794A CN 201611019433 A CN201611019433 A CN 201611019433A CN 107067794 A CN107067794 A CN 107067794A
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/14—Traffic control systems for road vehicles indicating individual free spaces in parking areas
- G08G1/141—Traffic control systems for road vehicles indicating individual free spaces in parking areas with means giving the indication of available parking spaces
- G08G1/143—Traffic control systems for road vehicles indicating individual free spaces in parking areas with means giving the indication of available parking spaces inside the vehicles
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/20—Instruments for performing navigational calculations
- G01C21/206—Instruments for performing navigational calculations specially adapted for indoor navigation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/40—Scenes; Scene-specific elements in video content
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/60—Type of objects
- G06V20/62—Text, e.g. of license plates, overlay texts or captions on TV images
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V2201/00—Indexing scheme relating to image or video recognition or understanding
- G06V2201/08—Detecting or categorising vehicles
Abstract
The present invention relates to a kind of indoor vehicle Position Fixing Navigation System based on Computer Vision and method, including：Image collecting device, server, vehicle user terminal and communication equipment；Described image harvester is used to catch vehicle on the move, using communication equipment to the server real time transmitting image data positioned at backstage；There is the positional information for having image collecting device in the electronic map of parking garage, electronic map in vehicle-mounted user terminal, the positional information of image collecting device can be also labeled in server module；The moving vehicle information that image collecting device is obtained is sent to server by communication equipment, and the server on backstage sends the position of user's vehicle after image procossing to vehicle user terminal.
Description
Technical field
The invention belongs to the vehicle positioning technology field in intelligent parking system, and in particular to one kind is based at video image
The indoor vehicle Position Fixing Navigation System and method of reason, realize positioning in real time.
Background technology
With the development of China's economic construction, Car ownership is more and more, and the demand to large parking lot is also more next
It is bigger, at the same extensive underground parking there are problems that with a varied topography, room it is difficult look for, circuit.Therefore, improve ground
The vehicle location degree of accuracy in lower parking lot and parking stall utilization rate enjoy all circles to pay close attention to.
GPS technology is conventional navigation system, but GPS, when being applied to indoor, signal is easily blocked, and positioning precision can be by
Very big influence, or even failure；IBeacon technologies compensate for the deficiency of GPS technology, provide the user a kind of low cost, more
The positioning tracking technology of power saving, position that can be according to user and demand, intelligent electronic is provided by application program for mobile terminal
Service.Because iBeacon is smaller, it is impossible to long-range, maintenance difficulties are big, not manageability；Wifi positioning is using existing wireless
Network, coordinates WIFI marks and related mobile device such as mobile phone, computer etc., in conjunction with corresponding location algorithm, the positioning of realization
System.At least can be, by an AP signal, as long as focus is powered, no matter how to encrypt in the middle any point in hollow of city,
It will position to transmission signal around and have very big error.
Compared with the indoor positioning navigation system used at present, the system substitutes WLAN base station transmission signal, passes
Defeated speed is fast, as long as the place of light-illuminating indoors, can realize the numbers such as prolonged upload high-resolution portrait and animation
According to.System receiving terminal selection is camera, the relatively far and near position of vehicle and camera is determined by the shooting of camera, more
Mend that indoor signal is weak and defect of later maintenance, it is possible to achieve be accurately positioned.
The content of the invention
It is an object of the invention to：Overcoming the deficiencies in the prior art, there is provided a kind of indoor cart based on Computer Vision
Position Fixing Navigation System and method, using the indoor positioning technologies based on camera, are not only simple in structure, applicability is wide, operation
It is convenient, but also the moving object detection and tracking carried out under varying environment can be promoted.
To realize object above, the present invention solves the technical scheme of key technical problem：
A kind of indoor vehicle Position Fixing Navigation System based on Computer Vision, it is characterised in that including：Image collector
Put, server, vehicle user terminal and communication equipment；Described image harvester is used to catch vehicle on the move, using logical
Believe equipment to the server real time transmitting image data positioned at backstage；There is parking garage in vehicle-mounted user terminal electronically
There is the positional information of image collecting device in figure, electronic map, the positional information of image collecting device can also be labeled in server
In；The moving vehicle information that image collecting device is obtained is sent to server by communication equipment, and the server on backstage is by figure
As target vehicle is extracted and tracked to Processing Algorithm, vehicle location is obtained by geometrical relationship computing, then to vehicle user terminal
Send the position of user's vehicle；Server also pushes the empty parking space information of parking space information and user's selection to user simultaneously, and
The navigation information of the empty parking space position selected from user vehicle location to user, so as to realize the real-time positioning of vehicle in parking lot
Navigation.
Described image harvester is made up of multiple video cameras, and each video camera is fixed, and has certain inclination downwards
Angle.
In the server, extracted by image processing algorithm and tracking target vehicle is as follows：
(1) mixed Gauss model is modeled, by the video sequence image for calculating image acquisition device in a period of time
In each pixel average gray value and pixel variance, Gaussian Mixture mould is constituted with K Gaussian Profile to each pixel
Type is modeled, and K values take 3-5；
(2) more new model, in each pixel and K Gaussian Profile in mixed Gauss model of the moment t to picture frame
Match somebody with somebody, for unmatched Gaussian Profile, then their average and covariance matrix are constant；The Gaussian Profile of matching needs to update every
The weight of the parameter of individual Gaussian Profile and each Gaussian Profile, sorts each Gaussian Profile according to weight, adds new Gaussian Profile
Carry out model modification；
(3) foreground detection, the weight obtained using step (2) and the ratio of standard deviation are divided K Gauss of each pixel
Cloth carries out descending sort, because the Gaussian Profile of most possible description Steady Background Light process is located at before sequence, B Gauss before taking
Distribution is as background model, and each pixel value at current time is matched with obtained preceding B Gaussian Profile, exists
Match somebody with somebody, the pixel is then background dot；Otherwise the pixel is detected as moving target, as moving vehicle；
(4) target vehicle track and localization, the prospect using step (3) acquisition is used as initial target information of vehicles
CamShift algorithms are combined with Kalman filter algorithm, realize accurately identifying and positioning to following instant moving vehicle,
So as to complete target vehicle track and localization.
In the server, the calculating process for obtaining vehicle location coordinate by geometrical relationship computing is as follows：
(1) according to camera pin-hole model and camera position, setting angle and the video image of acquisition basic parameter meter
Video camera vertical angle of view and the maximum angle α and minimum angle β of ground level y-axis are calculated, and camera horizon visual angle is regarded in level
The projection at angle and ground level y-axis angle γ；
α=arctan (H/y1)
β=arctan (H/ (y1+y2))
γ=acrtan (x1/y1)
(2) determine that target actual coordinate P (x, y) in the picture, x, y represent fortune respectively according to step (1) result of calculation
Moving-target parking lot coordinate position,
The vehicle user terminal is mobile phone, car-mounted terminal, platform computer.
Described communication equipment is Wireless Telecom Equipment, is placed in inside user terminal.
A kind of indoor vehicle positioning navigation method based on Computer Vision, is realized as follows：Pacify indoor parking many places
Device has video camera, for catching vehicle on the move, using server real time transmitting image data from camera to backstage；Car
Carry the positional information for having video camera in the electronic map for having parking garage in user terminal, electronic map, the position of video camera
Information can be also labeled on the server on backstage, and the moving vehicle information that video camera is obtained is sent to the server on backstage, service
Device extracts and tracked target vehicle by image processing algorithm, obtains vehicle location by geometrical relationship computing, and use to vehicle
Family terminal sends the position of user's vehicle；The empty parking space that server also pushes parking space information and user's selection to user simultaneously is believed
Breath, and from user vehicle location to user select empty parking space position navigation information, so as to realize vehicle in parking lot
Real-time location navigation.
The advantage of the present invention compared with prior art is：Using the technical scheme of the above, monitoring camera and moving vehicle
Combination, service end to user push parking lot empty parking space information, determine user's vehicle location and user selection empty parking space
Information, the navigation information of the empty parking space position selected from user vehicle location to user.So as to realize the reality of vehicle in parking lot
When location navigation, provide one kind for car owner and look for parking stall, the solution of intelligent parking can be very good to take the photograph using parking lot monitoring
As resource, parking efficiency is improved, it is practical, it can preferably serve car owner.
Brief description of the drawings
Fig. 1 shows measuring principle figure of the present invention；
The indoor vehicle location navigation flow chart of Fig. 2 display present invention.
Embodiment
Below by embodiment combination accompanying drawing, the invention will be further described.
As shown in figure 1, the indoor vehicle Position Fixing Navigation System of the invention based on Computer Vision, including image collector
Put, server, vehicle user terminal (mobile phone, car-mounted terminal, platform computer etc.), communication equipment, image collector is set to multiple
Shooting, each video camera is fixed on certain position, and has certain angle of inclination (30 degree of -50 degree) downwards.The present invention
Described indoor vehicle Position Fixing Navigation System implementation process is as follows：Parking garage many places, which are respectively mounted, is equipped with video camera, for catching
Catch vehicle on the move, using server real time transmitting image data from camera to backstage；There is interior in vehicle-mounted user terminal
There is the positional information of video camera in the electronic map in parking lot, electronic map, the positional information of video camera can also be labeled in backstage
Server on, the moving vehicle information that video camera is obtained is sent to the server on backstage, and server passes through image processing algorithm
Extract and tracking target vehicle, vehicle location is obtained by geometrical relationship computing, and user's vehicle is sent to vehicle user terminal
Position；Server also pushes the empty parking space information of parking space information and user's selection to user simultaneously, and from user vehicle position
The navigation information of the empty parking space position of user's selection is put, so as to realize the real-time location navigation of vehicle in parking lot.
Geometrical relationship computing obtains vehicle location, and Fig. 1 is obtains vehicle coordinate, and video camera is fixed, and has certain downwards
Angle of inclination (generally taking 30 degree of -50 degree).P (x, y) points are vehicle location, and p (μ, ν) is it in video camera imaging plane
The image plane coordinate of characteristic point.H is vertical range of the video camera to ground, y1It is that video camera vertical angle of view is projected on the ground
Minimum distance, y1+y2It is the maximum distance of video camera vertical angle of view projection on the ground, x1It is when video camera vertical angle of view is on ground
During closest on face, the distance of its horizontal view angle projection on the ground.α (0 ° of 50 ° of ＜ α ＜) and β (0 ° of 10 ° of ＜ β ＜) points
Not Wei video camera vertical angle of view and ground level y-axis minimum and maximum angle, γ (0 ° of 45 ° of ＜ γ ＜) is camera horizon visual angle
Projection and ground level y-axis angle in horizontal view angle.
Shown in Fig. 1, from the geometrical relationship of video camera vacuum mould, H, y1, y2And x1Value situation about can measure
Under, α in figure, the size of beta, gamma can be obtained easily.Target P (x, y) can be further obtained behind the α drawn, beta, gamma angle to exist
Transverse and longitudinal coordinate x and y under coordinate system.Derive relational expression as follows：
α=arctan (H/y1)
β=arctan (H/ (y1+y2))
γ=acrtan (x1/y1)
In above formula, u, v represents target signature line number on the image plane and columns, S respectivelyxAnd SyImage is represented respectively
Plane total line number in the x and y direction and columns.
Image algorithm obtains realization of goal real-time tracking, according to mixed Gaussian algorithm, by calculating image in a period of time
The average gray value and pixel variance of each pixel, are used each pixel in the video sequence image of harvester collection
K (K values take 3-5) Gaussian Profiles constitute gauss hybrid models to model, and a part for these Gaussian Profiles represents moving target
Pixel value, another part represents the pixel value of background.Gauss of distribution function can be represented with following formula：
X in formulai,tFor the variable of color point, d represents Xi,tDimension it is (usual during the mixed Gaussian background modeling of gray level image
Take d=1), μi,tFor average, Σi,tFor covariance matrix, and(ωi,tFor weight).
Then Gauss model is updated, in each pixel and the K Gauss point in mixed Gauss model of the moment t to present frame
Cloth is matched, and for unmatched Gaussian Profile, then their average and covariance matrix are constant；The Gaussian Profile of matching needs more
The parameter and the weight of each Gaussian Profile of new each Gaussian Profile, average can be updated according to such as following formula by updating Gaussian Profile
And standard deviation：
ωi,t=(1- α) ωi,t-1+αMi,t
μi,t=(1- β) μi,t-1+β
Wherein α (0≤α≤1) is customized turnover rate, and β is parameter learning rate, σi,tFor standard deviation.If current pixel
Being distributed for the mixed Gauss model of color variance of point all mismatches, then is mixed the minimum of weight in Gauss model that
Individual model is replaced with new model.New model is with Xi,tFor average, and initialize a larger standard deviation sigma0It is smaller with one
Weight.Remaining model keeps original parameter constant, but weight can decay, and update according to the following formula：ωi,t=(1- α) ωi,t-1
The Detection and Extraction of moving vehicle are foreground detection, according to new pixel value all parameters of mixed Gauss model more
Newly, according toRatio size descending sort is carried out to K Gaussian Profile of each pixel, because most possible description is stable
The Gaussian Profile of context process is located at before sequence, and B Gaussian Profile is remaining to be used as prospect mould as background model before taking
Type.
Wherein τ is total head threshold value (being usually 0.7), and expression can describe the Gaussian Profile weight sum of scene background most
Small value.By each pixel value X at current timei,tMatched with obtained preceding B Gaussian Profile, there is matching, the pixel
Point is then background dot；Otherwise the pixel is detected as moving target, as moving vehicle.
B represents Gaussian Profile number, and t represents the time, and i represents Gaussian component, wi,jRepresent i-th of Gaussian component of t
Weight coefficient, namely weight.
Target vehicle track and localization is finally realized, the moving foreground object obtained according to foreground detection obtains initial target car
Information, is combined using CamShift algorithms with Kalman filter algorithm, is realized to the accurate of following instant moving vehicle
Identification and positioning, so as to complete target vehicle track and localization.
The vehicle coordinate Information locating obtained by the moving vehicle got in real time and by geometrical relationship include with
Family vehicle termination, next needs to obtain parking lot empty parking space information.As shown in Fig. 2 whole flow process, which is vehicle, enters parking lot
Empty parking space information is sent to user by backstage, and user sends vehicle coordinate according to backstage and empty parking space information selects empty parking space, and
The navigation information provided according to backstage, realizes quick parking, vehicle location and navigation is realized with this system help user.
As the improvement of the present invention, parking space information is stored in backstage by service end, when user needs to look for car, can be to clothes
Business end sends request, and the parking space information that service end retrieval is bound with information of vehicles to be checked is sent to user, and according to the position of user
Put, navigation way, user terminal displays parking space information and navigation information are pushed to user.So as to look for car to provide one for the convenience of the user
Planting may.
Further, the parking lot information obtained according to camera, it can be determined that parking space information and vehicular movement information, is protected
The real-time update of parking stall in parking lot is demonstrate,proved, facilitates other users to stop.In addition can be according to car owner apart from empty parking space or parking
Outlet is far and near pushes the optimal selection based on distance parking for car owner, be also convenient for while saving car owner down time car owner from
Start-stop parking lot.
There is provided above example and to further improvement of the present invention explanation just for the sake of the description purpose of the present invention, and
It is not intended to limit the scope of the present invention.The scope of the present invention is defined by the following claims.The spiritual and original of the present invention is not departed from
The various equivalent alterations and modifications managed and made, all should cover within the scope of the present invention.
Claims (7)
1. a kind of indoor vehicle Position Fixing Navigation System based on Computer Vision, it is characterised in that including：Image collecting device,
Server, vehicle user terminal and communication equipment；Described image harvester is used to catch vehicle on the move, is set using communication
It is standby to the server real time transmitting image data positioned at backstage；There is the electronic map of parking garage in vehicle-mounted user terminal, electricity
There is the positional information of image collecting device in sub- map, the positional information of image collecting device can also be marked in the server；Figure
As the moving vehicle information that harvester is obtained by communication equipment is sent to server, the server on backstage passes through image procossing
Algorithm is extracted and tracking target vehicle, and vehicle location is obtained by geometrical relationship computing, is then sent and is used to vehicle user terminal
The position of family vehicle；Server also pushes the empty parking space information of parking space information and user's selection to user simultaneously, and from user
The navigation information for the empty parking space position that vehicle location is selected to user, so as to realize the real-time location navigation of vehicle in parking lot.
2. the indoor vehicle Position Fixing Navigation System according to claim 1 based on Computer Vision, it is characterised in that：Institute
State image collecting device to be made up of multiple video cameras, each video camera is fixed, and have certain angle of inclination downwards.
3. the indoor vehicle Position Fixing Navigation System according to claim 1 based on Computer Vision, it is characterised in that：Institute
State in server, extracted by image processing algorithm and tracking target vehicle is as follows：
(1) mixed Gauss model is modeled, each in the video sequence image by calculating a period of time interior image acquisition device
The average gray value and pixel variance of individual pixel, each pixel is constituted with K Gaussian Profile gauss hybrid models come
Modeling, K values take 3-5；
(2) more new model, is matched in moment t to each pixel of picture frame with K Gaussian Profile in mixed Gauss model, right
In unmatched Gaussian Profile, then their average and covariance matrix are constant；The Gaussian Profile of matching needs to update each high
The parameter of this distribution and the weight of each Gaussian Profile, sort each Gaussian Profile according to weight, add new Gaussian Profile and carry out
Model modification；
(3) foreground detection, the weight and the ratio of standard deviation obtained using step (2) is entered K Gaussian Profile of each pixel
Row descending sort, because the Gaussian Profile of most possible description Steady Background Light process is located at before sequence, B Gaussian Profile before taking
As background model, each pixel value at current time is matched with obtained preceding B Gaussian Profile, there is matching, should
Pixel is then background dot；Otherwise the pixel is detected as moving target, as moving vehicle；
(4) target vehicle track and localization, the prospect using step (3) acquisition is calculated as initial target information of vehicles using CamShift
Method is combined with Kalman filter algorithm, accurately identifying and positioning to following instant moving vehicle is realized, so as to complete mesh
Mark vehicle tracking positioning.
4. the indoor vehicle Position Fixing Navigation System according to claim 1 based on Computer Vision, it is characterised in that：Institute
State in server, the calculating process for obtaining vehicle location coordinate by geometrical relationship computing is as follows：
(1) taken the photograph according to camera pin-hole model and camera position, setting angle and the video image of acquisition Parameter Calculation
Camera vertical angle of view and the maximum angle α and minimum angle β of ground level y-axis, and camera horizon visual angle is in horizontal view angle
Projection and ground level y-axis angle γ；
α=arctan (H/y1)
β=arctan (H/ (y1+y2))
γ=acrtan (x1/y1)
(2) determine that target actual coordinate P (x, y) in the picture, x, y represent motion mesh respectively according to step (1) result of calculation
The coordinate position in parking lot is marked on,
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5. the indoor vehicle Position Fixing Navigation System according to claim 1 based on Computer Vision, it is characterised in that：Institute
Vehicle user terminal is stated for mobile phone, car-mounted terminal, platform computer.
6. the indoor vehicle Position Fixing Navigation System according to claim 1 based on Computer Vision, it is characterised in that：Institute
The communication equipment stated is Wireless Telecom Equipment, is placed in inside user terminal.
7. a kind of indoor vehicle positioning navigation method based on Computer Vision, its feature is as follows：Pacify indoor parking many places
Device has video camera, for catching vehicle on the move, using server real time transmitting image data from camera to backstage；Car
Carry the positional information for having video camera in the electronic map for having parking garage in user terminal, electronic map, the position of video camera
Information can be also labeled on the server on backstage, and the moving vehicle information that video camera is obtained is sent to the server on backstage, service
Device extracts and tracked target vehicle by image processing algorithm, obtains vehicle location by geometrical relationship computing, and use to vehicle
Family terminal sends the position of user's vehicle；The empty parking space that server also pushes parking space information and user's selection to user simultaneously is believed
Breath, and from user vehicle location to user select empty parking space position navigation information, so as to realize vehicle in parking lot
Real-time location navigation.
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| CN107888877A (en) * | 2017-11-13 | 2018-04-06 | 毛国强 | The method and its system of car tracing and acquisition of road traffic information |
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