CN115423868A - Spatial positioning linkage calibration method of video monitoring camera - Google Patents
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Abstract
The invention belongs to the technical field of camera positioning, and particularly discloses a space positioning linkage calibration method of a video monitoring camera.
Description
Technical Field
The invention belongs to the technical field of camera positioning, and relates to a space positioning linkage calibration method of a video monitoring camera.
Background
With the development of cities, the real-time monitoring of urban traffic becomes more and more important, and the establishment of a comprehensive traffic image management system is the target of traffic departments, so that the importance of monitoring management of video monitoring cameras in roads is highlighted under the background, and the spatial positioning and calibration processing of the video monitoring cameras is taken as the primary guarantee of urban traffic monitoring, so that the importance of the video monitoring cameras is self-evident.
The current video surveillance camera with spatial positioning is mainly used for positioning the surveillance scene of the video surveillance camera when performing position calibration, namely, mark points are placed at the preset positions around the camera, and the monitoring object of the video surveillance camera is not subjected to positioning analysis, so that certain limitation exists, and the video surveillance camera is embodied in the following aspects:
1. the road video monitoring camera is mainly used for monitoring the running condition of a road vehicle, and the current space positioning method is not suitable for the scene, cannot realize the optimization of the monitoring of the running condition of the road vehicle and cannot improve the monitoring effect of the running condition of the road vehicle;
2. the road video monitoring camera is also used for monitoring illegal vehicles in the road, and the vehicles can be abnormally driven due to various factors in the driving process of the road, such as serious overspeed during driving, the vehicles are rapidly positioned and intervened by contacting road traffic management personnel, so that larger loss is avoided, the abnormal vehicles are not analyzed in the prior art, the abnormal vehicles are not subjected to linkage calibration, and the positioning accuracy of the abnormal vehicles and the processing timeliness of the abnormal vehicles cannot be improved;
3. the camera quality of the road video monitoring camera is easily interfered by the external environment, and is not intelligently adjusted at present, so that the monitoring quality and the monitoring effect of the road video monitoring camera cannot be guaranteed, the feasibility of monitoring vehicle positioning is also reduced from another aspect, and the workload of road traffic managers cannot be effectively reduced.
Disclosure of Invention
In view of this, in order to solve the problems in the background art, a spatial positioning linkage calibration method for a video surveillance camera is proposed;
the purpose of the invention can be realized by the following technical scheme:
the invention provides a spatial positioning linkage calibration method of a video monitoring camera, which comprises the following steps:
s1, path information acquisition: acquiring basic information corresponding to an appointed analysis path, positioning a position corresponding to each intersection from the basic information, dividing the appointed analysis path into each road section, numbering the road sections according to a set sequence, and sequentially marking the road sections as 1,2,. I,. N, and acquiring corresponding equipment layout information and road information in each road section, wherein the equipment comprises a radar velocimeter and a video monitoring camera;
s2, acquiring information of a running vehicle: acquiring the speed of each running vehicle currently corresponding to each road section through a radar velocimeter arranged in each road section, and acquiring the image of the current running vehicle through a video monitoring camera arranged in each road section;
s3, analyzing vehicle running information: analyzing the speed corresponding to the current running vehicles in each road section, thereby carrying out type calibration on the running vehicles in each road section;
s4, vehicle linkage tracking: when the calibration type of a running vehicle in a certain road section is an abnormal type, recording the running vehicle as a target positioning vehicle, taking the road section as an initial positioning road section, extracting the position of the initial positioning road section and the current running vehicle image, performing linkage analysis on a video monitoring camera to obtain a linkage camera of the target positioning vehicle, and starting the linkage camera to acquire the detailed information of the target positioning vehicle;
s5, vehicle violation information feedback: feeding back the types of running vehicles in each road section and the detailed information of target positioning vehicles to road traffic managers;
s6, analyzing vehicle image information: analyzing images corresponding to the current running vehicles in each road section, and thus regulating and controlling and analyzing the video monitoring cameras in each road section;
s7, camera shooting regulation and control processing: and correspondingly regulating and controlling according to the regulation and control analysis result of the video monitoring cameras in each section.
As a preferred scheme, the basic information corresponding to the specified analysis path specifically includes a position corresponding to the specified analysis path and a position corresponding to each intersection in the specified analysis path.
As a preferred scheme, the arrangement information of the radar velocimeter is the arrangement position of the radar velocimeter; the video monitoring camera layout information comprises video monitoring camera layout positions, video monitoring camera initial set focal lengths and initial set aperture values; the road information includes the number of lanes and the width corresponding to each lane.
As a preferred scheme, the analysis of the speed corresponding to each current running vehicle in each road section includes the following steps:
extracting the layout positions of the radar velocimeters from the corresponding equipment layout information in each road section, and positioning the limited vehicle speed corresponding to each road section from the GIS map;
based on the position corresponding to the specified analysis path, extracting historical average traffic flow and historical average pedestrian flow corresponding to the specified analysis path from a road pipeline information base, and further setting the traffic weight of the specified analysis path and recording the traffic weight as epsilon;
the running vehicles in each road section are numbered according to a set sequence, and are marked as 1,2,. J,. M in sequence, so that the running vehicles pass through an analysis formula
Analyzing to obtain a speed compliance evaluation index lambda corresponding to each current running vehicle in each road section ij I is indicated as a link number, i =1, 2.. N.j is indicated as each running vehicleNo., j =1,2 Define the limit i Expressed as a defined vehicle speed, v, corresponding to the ith road segment ij And the speed corresponding to the jth running vehicle in the ith road section is expressed, e is expressed as a natural constant, Δ v is a set vehicle reference running speed difference, and μ is a set vehicle speed evaluation correction factor.
As a preferred scheme, the setting of the assigned analysis path traffic weight is performed, and the specific setting process refers to the following steps:
respectively recording the historical average traffic flow and the historical average pedestrian flow corresponding to the specified analysis path as
And
and importing a path traffic weight calculation formula
In the method, a traffic weight epsilon corresponding to the designated analysis path is obtained, where R 'and C' are respectively expressed as the set reference passenger flow rate and the reference traffic flow rate, a1 and a2 are respectively expressed as the occupancy weights corresponding to the set passenger flow rate and the traffic flow rate, a1 > 0, a2 > 0, and a1+ a2=1.
As a preferred scheme, the type calibration is performed on each running vehicle in each road segment, and the specific calibration mode refers to the following steps:
comparing a speed compliance evaluation index corresponding to each current running vehicle in each road section with a set standard vehicle speed compliance evaluation index, if the speed compliance evaluation index corresponding to a current running vehicle in a certain road section is greater than or equal to the standard vehicle speed compliance evaluation index, calibrating the compliance type of the current running vehicle in the road section, otherwise, judging that the running vehicle in the road section is a violation vehicle, and executing a second step;
and secondly, comparing the speed compliance evaluation index corresponding to the violation vehicle in the road section with the set speed compliance evaluation index range corresponding to each level of violation, if the speed compliance evaluation index corresponding to the violation vehicle in the road section is in the speed compliance evaluation index range corresponding to a certain level of violation, carrying out the level violation calibration on the violation vehicle in the road section, otherwise, carrying out the abnormal type calibration on the violation vehicle in the road section, and further carrying out the type calibration on the running vehicles in each road section in the mode.
As a preferred scheme, the video surveillance camera performs linkage analysis, and the specific analysis process is as follows:
extracting the current running vehicle image in the initial positioning road section, and positioning the running index in the lane corresponding to the target positioning vehicle from the current running vehicle image;
if the advancing index in the lane corresponding to the target positioning vehicle is a left-turn index, positioning a video monitoring camera arranged in a road section corresponding to the left-turn direction of the initial positioning road section from the GIS map, and using the video monitoring camera as a linkage camera of the target positioning vehicle;
if the advancing index in the lane corresponding to the target positioning vehicle is a right-turn index, positioning a video monitoring camera arranged in a road section corresponding to the right-turn direction of the initial positioning road section from the GIS map, and using the video monitoring camera as a linkage camera of the target positioning vehicle;
and if the running index in the lane corresponding to the target positioning vehicle is a straight-going index, extracting the position corresponding to the initial positioning road section, positioning the next road section corresponding to the initial positioning road section from the specified analysis path, and using the next road section as a linkage camera of the target positioning vehicle, thereby obtaining the linkage camera of the target positioning vehicle.
Preferably, the detailed information of the target vehicle specifically includes a license plate number, a body color, a body size, a driver face image and a position.
Preferably, the analyzing the image corresponding to each current driving vehicle in each road segment includes the following steps:
extracting the current running vehicle image in each road section, dividing the image corresponding to the current running vehicle in each road section into sub-images according to the division mode of the plane network format, and extracting the current running vehicle image from each sub-imagePixel value and luminance value, and are denoted as f it And l it T denotes the number corresponding to each sub-image, t =1, 2.... D;
based on the pixel values and the brightness values in the sub-images corresponding to the road sections, the average pixel values and the average brightness values corresponding to the current running vehicle images of the road sections are obtained through average value calculation and are respectively recorded as
And
screening out maximum pixel value, minimum pixel value, maximum brightness value and minimum brightness value from pixel values and brightness values in sub-images corresponding to each path, and respectively recording as f max i 、f min i 、l max i And l min i ；
Substituting the pixel value and brightness value of each sub-image corresponding to each path into the aperture adjustment calculation formula
In the method, the aperture adjustment evaluation index delta of the video monitoring camera in each road section is obtained i F 'and l' are set reference pixel values and reference brightness values of shot images of the video monitoring camera, b1, b2, b3 and b4 are respectively expressed as duty weighting factors corresponding to set image pixel deviation, pixel uniformity, brightness deviation and brightness uniformity, and eta is a set correction coefficient;
extracting the number of lanes and the width corresponding to each lane from the image corresponding to the current running vehicle in each road section, and respectively recording the number of lanes and the width as s i And w i r R denotes a lane number, and r =1,2
Calculating to obtain a focal length adjustment evaluation index gamma of the video monitoring camera in each road section i ，s 0 i Is shown asThe number of lanes, w 'corresponding to the i road segments' ir The width corresponding to the r-th lane in the ith road section is shown, b5 and b6 are respectively shown as the weight factors corresponding to the set number of lanes and the lane width, k is the set image scaling ratio, and delta w is the set allowable lane width difference.
As a preferred scheme, the regulation and control analysis is performed on the video surveillance cameras in each road section, and the specific analysis process is as follows:
comparing the aperture adjustment evaluation index of the video monitoring camera in each road section with a set standard aperture adjustment evaluation index, if the aperture adjustment evaluation index of the video monitoring camera in a certain road section is greater than or equal to the standard aperture adjustment evaluation index, marking the road section as an aperture adjustment road section, and extracting the number corresponding to each aperture adjustment road section;
positioning a standard aperture value of the video monitoring camera in each aperture adjusting section from a camera information base based on an aperture adjusting evaluation index of the video monitoring camera in each aperture adjusting section, and subtracting the standard aperture value of the video monitoring camera in each aperture adjusting section from an initial setting aperture value of the video monitoring camera in each aperture adjusting section to obtain an aperture difference of the video monitoring camera in each aperture adjusting section;
if the aperture difference of the video monitoring camera in a certain aperture adjusting section is a positive value, judging that the aperture regulation and control mode of the video monitoring camera in the aperture adjusting section is to improve aperture regulation and control, otherwise, judging that the aperture regulation and control mode of the video monitoring camera in the aperture adjusting section is to reduce aperture regulation and control, so as to obtain the aperture regulation and control mode of the video monitoring camera in each aperture adjusting section, and taking the aperture difference of the video monitoring camera in each aperture adjusting section as an aperture regulation and control value;
comparing the focus adjustment evaluation index of the video monitoring camera in each section with a set standard focus adjustment evaluation index, if the focus adjustment evaluation index of the video monitoring camera in a certain section is greater than or equal to the standard focus adjustment evaluation index, recording the section as a focus adjustment section, extracting a number corresponding to each focus adjustment section, and performing the same analysis according to the aperture regulation mode and aperture regulation value analysis mode of the video monitoring camera in each aperture adjustment section to obtain the focus regulation mode and focus regulation value of the video monitoring camera in each focus adjustment section.
Compared with the prior art, the invention has the following beneficial effects:
(1) According to the space positioning linkage calibration method of the video monitoring camera, provided by the invention, the driving information and the vehicle image of the vehicle in each road section in the specified path are collected, so that the violation analysis is carried out on each vehicle, the abnormal vehicle is further tracked in a linkage manner, and meanwhile, the regulation and control analysis of the video monitoring camera is carried out based on the image corresponding to the vehicle, so that the problem that the monitoring object of the video monitoring camera is not subjected to positioning analysis in the prior art is effectively solved, the limitation in the prior art is broken, the scene applicability of the space positioning linkage calibration method of the video monitoring camera is improved, the optimization of road running condition monitoring is realized, the monitoring effect of the running of the road vehicle is greatly improved, the intelligent level of the running management of the road vehicle is improved, convenience is provided for the follow-up road traffic manager to master the running information of the road vehicle, and the development of the road management work corresponding to the follow-up road traffic manager is promoted.
(2) The invention analyzes the speed condition of each vehicle in each road section, thereby carrying out type calibration, extracting the position of the vehicle calibrated to be abnormal and the advancing index of the lane, carrying out linkage analysis of the video monitoring camera, and moving the linkage camera of the abnormal vehicle to monitor the detailed information of the vehicle, effectively improving the timeliness and the accuracy of positioning the abnormal vehicle, avoiding greater loss caused by factors such as vehicle runaway and the like, simultaneously improving the response efficiency of the abnormal vehicle, and maintaining the safety and the stability of road operation to the maximum extent.
(3) According to the invention, the images corresponding to the current running vehicles in each road section are analyzed, so that the video monitoring cameras in each road section are regulated and analyzed, and then the video monitoring cameras in each road section are correspondingly regulated and controlled, so that the intelligent regulation of the video monitoring cameras is realized, the monitoring quality and the monitoring effect of the road video monitoring cameras are effectively ensured, and the feasibility of monitoring vehicle positioning is greatly improved from another aspect, thereby effectively lightening the workload of road traffic managers, improving the management level of road traffic and further reducing traffic disputes.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the description below are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a flow chart of the steps of the method of the present invention.
Detailed Description
While the foregoing is directed to embodiments of the present invention, other and further embodiments of the invention may be devised without departing from the basic scope thereof, and the scope thereof is determined by the claims that follow.
Referring to fig. 1, the present invention provides a public transportation environment monitoring, analyzing and managing method based on big data, which includes the following steps:
s1, path information acquisition: acquiring basic information corresponding to an appointed analysis path, positioning a position corresponding to each intersection from the basic information, dividing the appointed analysis path into each road section, numbering the road sections according to a set sequence, sequentially marking the road sections as 1,2,. I,. N, and acquiring corresponding equipment layout information and road information in each road section, wherein the equipment comprises a radar velocimeter and a video monitoring camera;
specifically, the basic information corresponding to the specified analysis path specifically includes a position corresponding to the specified analysis path and a position corresponding to each intersection in the specified path;
further, the arrangement information of the radar velocimeter is the arrangement position of the radar velocimeter; the video monitoring camera layout information comprises video monitoring camera layout positions, video monitoring camera initial set focal lengths and initial set aperture values; the road information comprises the number of lanes and the width corresponding to each lane;
s2, acquiring information of a running vehicle: acquiring the speed of each running vehicle currently corresponding to each road section through each radar velocimeter arranged in each road section, and acquiring the image of the current running vehicle through a video monitoring camera arranged in each road section;
s3, analyzing vehicle running information: analyzing the speed corresponding to the current running vehicles in each road section, thereby carrying out type calibration on the running vehicles in each road section;
exemplarily, the speed corresponding to each current running vehicle in each road segment is analyzed, and the specific analysis process comprises the following steps:
a1, extracting the layout position of a radar velocimeter from corresponding equipment layout information in each road section, and positioning a limited vehicle speed corresponding to each road section from a GIS map;
a2, based on the position corresponding to the specified analysis path, extracting the historical average traffic flow and the historical average pedestrian flow corresponding to the specified analysis path from the road pipeline information base, further setting the traffic weight of the specified analysis path, and marking as epsilon,
and
respectively representing historical average traffic flow and historical average pedestrian flow corresponding to a specified analysis path, respectively representing R 'and C' as set reference pedestrian flow and reference traffic flow, respectively representing a1 and a2 as ratio weights corresponding to the set pedestrian flow and the set pedestrian flow, wherein a1 is greater than 0, a2 is greater than 0, and a1+ a2=1;
a3, numbering the running vehicles in each road section according to a set sequence, and sequentially marking the running vehicles as 1,2,. J,. M, thereby passing through an analysis formula
Analyzing to obtain the speed compliance evaluation index lambda corresponding to the current running vehicles in each road section ij I denotes a link number, i =1, 2.. N, j denotes a running vehicle number, and j =1, 2.. A Define a limit i Expressed as a defined vehicle speed, v, corresponding to the ith road segment ij The speed corresponding to the jth running vehicle in the ith road section is expressed, e is expressed as a natural constant, Δ v is a set vehicle reference running speed difference, and μ is a set vehicle speed evaluation correction factor;
in another example, the type of each traveling vehicle in each road segment is calibrated in the following manner:
comparing the speed compliance evaluation index corresponding to the current running vehicle in each road section with a set standard vehicle speed compliance evaluation index, if the speed compliance evaluation index corresponding to the current running vehicle in a certain road section is greater than or equal to the standard vehicle speed compliance evaluation index, calibrating the compliance type of the current running vehicle in the road section, otherwise, judging that the running vehicle in the road section is a violation vehicle, and executing a second step;
secondly, comparing the speed compliance assessment index corresponding to the violation vehicle in the road section with the set speed compliance assessment index range corresponding to each level of violation, if the speed assessment index corresponding to the violation vehicle in the road section is in the speed compliance assessment index range corresponding to a certain level of violation, carrying out the level violation calibration on the violation vehicle in the road section, otherwise, carrying out the abnormal type calibration on the violation vehicle in the road section, and further carrying out the type calibration on the running vehicles in each road section in the mode, wherein the violation levels comprise a level one violation, a level two violation and a level three violation;
s4, vehicle linkage tracking: when the calibration type of a running vehicle in a certain road section is an abnormal type, recording the running vehicle as a target positioning vehicle, taking the road section as an initial positioning road section, extracting the position of the initial positioning road section and the current running vehicle image, performing linkage analysis on a video monitoring camera to obtain a linkage camera of the target positioning vehicle, and starting the linkage camera to acquire the detailed information of the target positioning vehicle;
specifically, the video monitoring camera is used for linkage analysis, and the specific analysis process is as follows:
extracting the image of the current running vehicle in the initial positioning road section, and positioning the running index in the lane where the target positioning vehicle is located;
if the advancing index in the lane corresponding to the target positioning vehicle is a left-turn index, positioning a video monitoring camera arranged in a road section corresponding to the left-turn direction of the initial positioning road section from the GIS map, and using the video monitoring camera as a linkage camera of the target positioning vehicle;
if the advancing index in the lane corresponding to the target positioning vehicle is a right-turn index, positioning a video monitoring camera arranged in a road section corresponding to the right-turn direction of the initial positioning road section from the GIS map and using the video monitoring camera as a linkage camera of the target positioning vehicle;
if the traveling index in the lane corresponding to the target positioning vehicle is a straight-ahead index, extracting the position corresponding to the initial positioning road section, further positioning the next road section corresponding to the initial positioning road section from the specified analysis path, and using the next road section as a linkage camera of the target positioning vehicle, thereby obtaining the linkage camera of the target positioning vehicle;
according to the embodiment of the invention, the speed condition of each vehicle in each road section is analyzed, so that type calibration is carried out, the position of the vehicle calibrated to be in an abnormal type and the advancing index of the lane in which the vehicle is positioned are extracted, so that linkage analysis of the video monitoring camera is carried out, and the linkage camera of the abnormal vehicle is called to monitor the detailed information of the vehicle, so that the timeliness and the accuracy of positioning the abnormal vehicle are effectively improved, the greater loss caused by factors such as vehicle runaway and the like is avoided, the response efficiency of the abnormal vehicle is improved, and the safety and the stability of road operation are maintained to the greatest extent.
Further, the detail information of the target vehicle specifically comprises a license plate number, a vehicle body main body color, a vehicle body size, a driver face image and a position;
it should be noted that, the vehicle detail information is collected to provide positioning convenience and processing convenience for road traffic managers;
s5, vehicle violation information feedback: feeding back the types of running vehicles in each road section and the detailed information of target positioning vehicles to road traffic managers;
s6, analyzing vehicle image information: analyzing images corresponding to the current running vehicles in each road section, and thus regulating and controlling and analyzing the video monitoring cameras in each road section;
it should be noted that, analyzing the image corresponding to each current driving vehicle in each road segment, the analyzing process includes the following steps:
p1, extracting the current running vehicle image in each road section, dividing the image corresponding to the current running vehicle in each road section into sub-images according to the division mode of the plane network format, extracting pixel values and brightness values from the sub-images, and respectively marking the pixel values and the brightness values as f it And l it T denotes the number corresponding to each sub-image, t =1, 2.... D;
p2, calculating an average pixel value and an average brightness value corresponding to the current running vehicle image of each road section through an average value based on the pixel value and the brightness value in each sub-image corresponding to each road section, and recording the average pixel value and the average brightness value as the current running vehicle image of each road section
And
p3, screening out a maximum pixel value, a minimum pixel value, a maximum brightness value and a minimum brightness value from the pixel values and the brightness values of the sub-images corresponding to the road sections, and respectively recording the maximum pixel value, the minimum pixel value, the maximum brightness value and the minimum brightness value as f max i 、f min i 、l max i And l min i ；
P4, substituting the pixel values and the brightness values in the sub-images corresponding to the road sections into an aperture adjustment calculation formula
In the method, the aperture adjustment evaluation index delta of the video monitoring camera in each road section is obtained i F 'and l' are set reference pixel values and reference brightness values of shot images of the video monitoring camera, b1, b2, b3 and b4 are respectively expressed as ratio weight factors corresponding to set image pixel deviation, pixel uniformity, brightness deviation and brightness uniformity, and eta is a set correction coefficient;
p5, extracting the number of lanes and the width corresponding to each lane from the image corresponding to the current running vehicle in each road section, and respectively recording the number of lanes and the width as s i And w i r R denotes a lane number, and r =1,2
Calculating to obtain a focal length adjustment evaluation index gamma of the video monitoring camera in each road section i ，s 0 i Represents the number of lanes, w 'corresponding to the ith road segment' ir The width corresponding to the r-th lane in the ith road section is shown, b5 and b6 are respectively shown as the weight factors corresponding to the set number of lanes and the lane width, k is the set image scaling ratio, and delta w is the set allowable lane width difference.
It should be further noted that the video surveillance cameras in each road section are regulated and analyzed, and the specific analysis process is as follows:
k1, comparing the aperture adjustment evaluation index of the video monitoring camera in each road section with a set standard aperture adjustment evaluation index, if the aperture adjustment evaluation index of the video monitoring camera in a certain road section is greater than or equal to the standard aperture adjustment evaluation index, marking the road section as an aperture adjustment road section, and extracting the number corresponding to each aperture adjustment road section;
k2, positioning the standard aperture value of the video monitoring camera in each aperture adjusting section from the camera information base based on the aperture adjusting evaluation index of the video monitoring camera in each aperture adjusting section, and subtracting the standard aperture value of the video monitoring camera in each aperture adjusting section from the initial setting aperture value of the video monitoring camera in each aperture adjusting section to obtain the aperture difference of the video monitoring camera in each aperture adjusting section;
k3, if the aperture difference of the video monitoring cameras in a certain aperture adjusting section is a positive value, judging that the aperture adjusting mode of the video monitoring cameras in the aperture adjusting section is to improve aperture adjustment, otherwise, judging that the aperture adjusting mode of the video monitoring cameras in the aperture adjusting section is to reduce aperture adjustment, so as to obtain the aperture adjusting mode of the video monitoring cameras in each aperture adjusting section, and taking the aperture difference of the video monitoring cameras in each aperture adjusting section as an aperture adjusting value;
k4, comparing the focal length adjustment evaluation index of the video monitoring camera in each section with a set standard focal length adjustment evaluation index, if the focal length adjustment evaluation index of the video monitoring camera in a certain section is greater than or equal to the standard focal length adjustment evaluation index, marking the section as a focal length adjustment section, extracting a number corresponding to each focal length adjustment section, and performing the same analysis according to the aperture regulation and control mode of the video monitoring camera in each aperture adjustment section and the analysis mode of the aperture regulation and control value to obtain the focal length regulation and control mode and the focal length regulation and control value of the video monitoring camera in each focal length adjustment section;
according to the embodiment of the invention, the images corresponding to the current running vehicles in each road section are analyzed, so that the video monitoring cameras in each road section are regulated and analyzed, and then the video monitoring cameras in each road section are correspondingly regulated and controlled, the intelligent regulation of the video monitoring cameras is realized, the monitoring quality and the monitoring effect of the road video monitoring cameras are effectively ensured, the feasibility of monitoring vehicle positioning is greatly improved from another aspect, the workload of road traffic managers is effectively reduced, the management level of road traffic is improved, and thus traffic disputes are reduced.
S7, camera shooting regulation and control processing: and correspondingly regulating and controlling according to the regulation and control analysis result of the video monitoring cameras in each section.
Specifically, corresponding regulation and control including aperture regulation and control and focal length regulation and control are carried out according to the regulation and control analysis result of the video monitoring cameras in each road section;
and further, aperture regulation and control are carried out according to the aperture regulation and control mode and the aperture regulation and control value of the video monitoring camera in each aperture regulation section, and focal length regulation and control are carried out according to the focal length regulation and control mode and the focal length regulation and control value of the video monitoring camera in each focal length regulation section.
It should be noted that the aperture of the camera determines the brightness of the captured image and also affects the clarity of the captured image, the more suitable the aperture brightness is, the higher the imaging quality is, and the focal length of the camera determines the imaging size and the imaging range of the captured image, so that the aperture and the focal length of the video surveillance camera need to be adjusted, controlled and analyzed.
According to the embodiment of the invention, the driving information and the vehicle images of the vehicles in each road section in the designated path are collected, so that violation analysis is carried out on each vehicle, further the abnormal vehicles are tracked in a linkage manner, meanwhile, the regulation and control analysis of the video monitoring camera is carried out on the basis of the images corresponding to the vehicles, the problem that the monitoring object of the video monitoring camera is not subjected to positioning analysis in the prior art is effectively solved, the limitation in the prior art is broken, the scene applicability of the video monitoring camera space positioning linkage calibration method is improved, and the optimization of road running condition monitoring is realized, so that the monitoring effect of the running of the road vehicles is greatly improved, the intelligent level of the running management of the road vehicles is improved, convenience is provided for the follow-up road traffic managers to master the running information of the road vehicles, and the development of the follow-up road traffic managers to correspond to the road management work is promoted.
The foregoing is merely exemplary and illustrative of the principles of the present invention and various modifications, additions and substitutions of the specific embodiments described herein may be made by those skilled in the art without departing from the principles of the present invention or exceeding the scope of the claims set forth herein.
Claims (10)
1. A space positioning linkage calibration method of a video monitoring camera is characterized by comprising the following steps: the method comprises the following steps:
s1, path information acquisition: acquiring basic information corresponding to an appointed analysis path, positioning a position corresponding to each intersection from the basic information, dividing the appointed analysis path into each road section, numbering the road sections according to a set sequence, sequentially marking the road sections as 1,2,. I,. N, and acquiring corresponding equipment layout information and road information in each road section, wherein the equipment comprises a radar velocimeter and a video monitoring camera;
s2, acquiring information of a running vehicle: the method comprises the steps that speed collection is conducted on currently corresponding running vehicles in all road sections through radar speed measuring instruments arranged in all road sections, and meanwhile images of the currently running vehicles are collected through video monitoring cameras arranged in all road sections;
s3, analyzing vehicle running information: analyzing the speed corresponding to each current running vehicle in each road section, and calibrating the type of each running vehicle in each road section;
s4, vehicle linkage tracking: when the calibration type of a running vehicle in a certain road section is an abnormal type, recording the running vehicle as a target positioning vehicle, taking the road section as an initial positioning road section, extracting the position of the initial positioning road section and the current running vehicle image, performing linkage analysis on a video monitoring camera to obtain a linkage camera of the target positioning vehicle, and starting the linkage camera to acquire the detailed information of the target positioning vehicle;
s5, vehicle violation information feedback: feeding back the type of each running vehicle in each road section and the detailed information of the target positioning vehicle to a road traffic manager;
s6, analyzing vehicle image information: analyzing images corresponding to the current running vehicles in each road section, and thus regulating and controlling and analyzing the video monitoring cameras in each road section;
s7, camera shooting regulation and control processing: and correspondingly regulating and controlling according to the regulation and control analysis result of the video monitoring cameras in each section.
2. The spatial positioning linkage calibration method of the video monitoring camera according to claim 1, characterized in that: the basic information corresponding to the specified analysis path specifically includes a position corresponding to the specified analysis path and a position corresponding to each intersection in the specified path.
3. The spatial positioning linkage calibration method of the video monitoring camera according to claim 1, characterized in that: the arrangement information of the radar velocimeters is the arrangement positions of the radar velocimeters; the video monitoring camera layout information comprises video monitoring camera layout positions, video monitoring camera initial set focal lengths and initial set aperture values; the road information includes the number of lanes and the width corresponding to each lane.
4. The spatial positioning linkage calibration method of the video monitoring camera according to claim 1, characterized in that: the method comprises the following steps of analyzing the speed corresponding to each current running vehicle in each road section, wherein the specific analysis process comprises the following steps:
extracting the arrangement position of the radar velocimeter from the corresponding equipment arrangement information in each road section, thereby positioning the limited vehicle speed corresponding to each road section from the GIS map;
based on the position corresponding to the specified analysis path, extracting historical average traffic flow and historical average pedestrian flow corresponding to the specified analysis path from a road pipeline information base, and further setting the traffic weight of the specified analysis path and recording the traffic weight as epsilon;
the running vehicles in each road section are numbered according to a set sequence, and are marked as 1,2,. J,. M in sequence, so that the running vehicles pass through an analysis formula
Analyzing to obtain a speed compliance evaluation index lambda corresponding to each current running vehicle in each road section ij I denotes a link number, i =1, 2.. N, j denotes a running vehicle number, and j =1, 2.. A Define a limit i Expressed as a defined vehicle speed, v, corresponding to the ith road segment ij And the speed corresponding to the jth running vehicle in the ith road section is expressed, e is expressed as a natural constant, Δ v is a set vehicle reference running speed difference, and μ is a set vehicle speed evaluation correction factor.
5. The spatial positioning linkage calibration method of the video monitoring camera according to claim 4, characterized in that: the specified analysis path traffic weight setting is carried out, and the specific setting process refers to the following steps:
respectively recording the historical average traffic flow and the historical average pedestrian flow corresponding to the specified analysis path as
And
and importing a path traffic weight calculation formula
The traffic weight epsilon corresponding to the designated analysis path is obtained, wherein R 'and C' are respectively expressed as the set reference passenger flow and the reference traffic flow, a1 and a2 are respectively expressed as the ratio weights corresponding to the set passenger flow and the traffic flow, a1 is greater than 0, a2 is greater than 0, and a1+ a2=1.
6. The spatial positioning linkage calibration method of the video surveillance camera according to claim 4, characterized in that: the type calibration is performed on each running vehicle in each road section, and the specific calibration mode refers to the following steps:
comparing the speed compliance evaluation index corresponding to the current running vehicle in each road section with a set standard vehicle speed compliance evaluation index, if the speed compliance evaluation index corresponding to the current running vehicle in a certain road section is greater than or equal to the standard vehicle speed compliance evaluation index, calibrating the compliance type of the current running vehicle in the road section, otherwise, judging that the running vehicle in the road section is a violation vehicle, and executing a second step;
and secondly, comparing the speed compliance assessment index corresponding to the violation vehicle in the road section with the set speed compliance assessment index range corresponding to each level of violation, if the speed assessment index corresponding to the violation vehicle in the road section is in the speed compliance assessment index range corresponding to a certain level of violation, carrying out the level violation calibration on the violation vehicle in the road section, otherwise, carrying out the abnormal type calibration on the violation vehicle in the road section, and further carrying out the type calibration on the running vehicles in each road section in the mode.
7. The spatial positioning linkage calibration method of the video monitoring camera according to claim 1, characterized in that: the video monitoring camera is used for linkage analysis, and the specific analysis process is as follows:
extracting the current running vehicle image in the initial positioning road section, and positioning the running index in the lane corresponding to the target positioning vehicle from the current running vehicle image;
if the traveling index in the lane corresponding to the target positioning vehicle is a left-turn index, positioning a video monitoring camera arranged in a road section corresponding to the left-turn direction of the initial positioning road section from the GIS map and using the video monitoring camera as a linkage camera of the target positioning vehicle;
if the advancing index in the lane corresponding to the target positioning vehicle is a right-turn index, positioning a video monitoring camera arranged in a road section corresponding to the right-turn direction of the initial positioning road section from the GIS map, and using the video monitoring camera as a linkage camera of the target positioning vehicle;
and if the running index in the lane corresponding to the target positioning vehicle is a straight-going index, extracting the position corresponding to the initial positioning road section, positioning the next road section corresponding to the initial positioning road section from the specified analysis path, and using the next road section as a linkage camera of the target positioning vehicle, thereby obtaining the linkage camera of the target positioning vehicle.
8. The spatial positioning linkage calibration method of the video monitoring camera according to claim 1, characterized in that: the detail information of the target vehicle specifically comprises a license plate number, a vehicle body color, a vehicle body size, a driver face image and a position.
9. The spatial positioning linkage calibration method of the video surveillance camera according to claim 4, characterized in that: the analysis of the images corresponding to the current running vehicles in each road section comprises the following steps:
extracting the current running vehicle image in each road section, dividing the image corresponding to the current running vehicle in each road section into sub-images according to the division mode of the plane network format, extracting pixel values and brightness values from the sub-images, and respectively marking the pixel values and the brightness values as f it And l it T denotes the number corresponding to each sub-image, t =1, 2.... D;
based on the pixel values and the brightness values in the sub-images corresponding to the road sections, the average pixel values and the average brightness values corresponding to the current running vehicle images of the road sections are obtained through average value calculation and are respectively recorded as
And
screening out maximum pixel value, minimum pixel value, maximum brightness value and minimum brightness value from pixel values and brightness values in sub-images corresponding to each path, and respectively recording as f max i 、f min i 、l max i And l min i ；
Substituting the pixel value and brightness value of each sub-image corresponding to each path into the aperture adjustment calculation formula
In the method, the aperture adjustment evaluation index delta of the video monitoring camera in each section is obtained i F 'and l' are reference pixel values and reference luminance values of the set photographed image of the video surveillance camera, and b1, b2, b3, and b4 are respectively expressed asSetting ratio weight factors corresponding to the image pixel deviation, the pixel uniformity, the brightness deviation and the brightness uniformity, wherein eta is a set correction coefficient;
extracting the number of lanes and the width corresponding to each lane from the image corresponding to the current running vehicle in each road section, and respectively recording the number of lanes and the width as s i And w i r R denotes a lane number, and r =1,2
Calculating to obtain a focal length adjustment evaluation index gamma of the video monitoring camera in each road section i ，s 0 i Indicates the number of lanes, w 'corresponding to the ith road segment' ir The width corresponding to the r-th lane in the ith road section is shown, b5 and b6 are respectively shown as the weight factors corresponding to the set number of lanes and the lane width, k is the set image scaling ratio, and delta w is the set allowable lane width difference.
10. The spatial positioning linkage calibration method of the video surveillance camera according to claim 9, characterized in that: the method comprises the following steps of regulating and controlling and analyzing the video surveillance cameras in each road section, wherein the specific analysis process comprises the following steps:
comparing the aperture adjustment evaluation index of the video monitoring camera in each road section with a set standard aperture adjustment evaluation index, if the aperture adjustment evaluation index of the video monitoring camera in a certain road section is greater than or equal to the standard aperture adjustment evaluation index, marking the road section as an aperture adjustment road section, and extracting the number corresponding to each aperture adjustment road section;
positioning a standard aperture value of the video monitoring camera in each aperture adjusting section from a camera information base based on an aperture adjusting evaluation index of the video monitoring camera in each aperture adjusting section, and subtracting the standard aperture value of the video monitoring camera in each aperture adjusting section from an initial setting aperture value of the video monitoring camera in each aperture adjusting section to obtain an aperture difference of the video monitoring camera in each aperture adjusting section;
if the aperture difference of the video monitoring camera in a certain aperture adjusting section is a positive value, judging that the aperture regulation and control mode of the video monitoring camera in the aperture adjusting section is to improve aperture regulation and control, otherwise, judging that the aperture regulation and control mode of the video monitoring camera in the aperture adjusting section is to reduce aperture regulation and control, so as to obtain the aperture regulation and control mode of the video monitoring camera in each aperture adjusting section, and taking the aperture difference of the video monitoring camera in each aperture adjusting section as an aperture regulation and control value;
comparing the focal length adjustment evaluation index of the video monitoring camera in each section with a set standard focal length adjustment evaluation index, if the focal length adjustment evaluation index of the video monitoring camera in a certain section is greater than or equal to the standard focal length adjustment evaluation index, recording the section as a focal length adjustment section, extracting a number corresponding to each focal length adjustment section, and performing the same analysis according to the aperture regulation and control mode of the video monitoring camera in each aperture adjustment section and the analysis mode of the aperture regulation and control value to obtain the focal length regulation and control mode and the focal length regulation and control value of the video monitoring camera in each focal length adjustment section.
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