CN117152892B - Sand theft prevention method and system based on video monitoring identification - Google Patents
Sand theft prevention method and system based on video monitoring identification Download PDFInfo
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Classifications
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B13/00—Burglar, theft or intruder alarms
- G08B13/18—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength
- G08B13/189—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems
- G08B13/194—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems using image scanning and comparing systems
- G08B13/196—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems using image scanning and comparing systems using television cameras
- G08B13/19602—Image analysis to detect motion of the intruder, e.g. by frame subtraction
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
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- G06V20/50—Context or environment of the image
- G06V20/52—Surveillance or monitoring of activities, e.g. for recognising suspicious objects
Abstract
The invention provides a method and a system for preventing sand theft based on video monitoring and identification, comprising the following steps: acquiring a map of an area to be monitored, and sketching a monitored road on the map; according to the monitoring road layout monitoring equipment, the monitoring equipment comprises a monitoring center platform and a plurality of monitors, and the monitoring center platform is in communication connection with all monitors; the monitoring center platform analyzes and judges whether sand stealing occurs according to the monitoring videos shot by all monitors; and if the sand stealing behavior is judged, the supervision center platform sends out alarm information. The monitor is reasonably and efficiently arranged by carrying out layout design on the area to be monitored, so that the effectiveness of monitoring is ensured on the basis of control cost; all monitoring videos are analyzed and judged through the monitoring center platform, so that the judgment accuracy is improved, further, the manpower waste caused after alarm information is sent out due to misjudgment can be avoided, and the problems of high cost and poor effect of the conventional illegal sand production monitoring scheme are solved.
Description
Technical Field
The invention relates to the technical field of video monitoring and recognition, in particular to a sand theft prevention method and system based on video monitoring and recognition.
Background
With the development of the chip semiconductor industry and the development of the civil engineering industry, the demand for sand is increasing. At present, natural sand is mainly obtained in river courses and the like through equipment such as sand extraction vessels and the like. Because natural sand is a non-renewable resource, natural sand resources in some areas are nearly exhausted. Under the driving of benefits, the illegal sand production behavior is frequently kept, so that the ecological balance of the river dike and the surrounding environment is destroyed, and the loss of natural resources and economic benefits of the country are caused.
In order to control illegal sand production, related departments send manpower to check, but the mode not only consumes a great deal of manpower, but also has an unsatisfactory supervision effect due to the limited manual control range. Based on this, relevant departments have still set up intelligent monitoring equipment, utilize computer technology intelligence to judge whether illegal sand production action has taken place through the video image that obtains near the river course, however this kind of mode needs to erect a large amount of monitoring equipment, and it erects and later maintenance cost is higher, and because be difficult to erect monitoring equipment in river course partial area, or receive geographical factor influence, can cause the control dead angle, and personnel are inconvenient close to, provide the machine that can take advantage of for illegal sand production.
Disclosure of Invention
The invention aims to provide a method and a system for preventing sand theft based on video monitoring and identification, which are used for solving the problems of high cost and poor effect of the existing scheme for monitoring illegal sand collection.
In order to solve the technical problems, the invention provides a sand theft prevention method based on video monitoring and identification, which comprises the following steps:
acquiring a map of an area to be monitored, and sketching a monitored road on the map;
according to the monitoring road layout monitoring equipment, the monitoring equipment comprises a supervision center platform and a plurality of monitors, and the supervision center platform is in communication connection with all the monitors;
the monitoring center platform analyzes and judges whether sand stealing occurs according to the monitoring videos shot by all the monitors;
and if the sand stealing behavior is judged, the supervision center platform sends out alarm information.
Optionally, in the method for preventing sand theft based on video monitoring and identification, the method for monitoring the road layout monitoring device includes:
setting a non-key road section, a key road section, key points and other road sections on the monitoring road, wherein the two ends of the non-key road section are key points;
acquiring coordinates of the key points and coordinates of two end points of the non-key road section;
Summarizing the coordinates of the key points and the coordinates of the two end points of the non-key road section, and removing the repeated coordinates to obtain the number of coordinates and a coordinate set, wherein the number of coordinates is the number of monitors, and each coordinate in the coordinate set is the installation position of each monitor.
Optionally, in the method for preventing sand theft based on video monitoring and identification, the method for monitoring the road layout monitoring device further includes:
removing the non-key road sections from the monitoring road to obtain a type of monitoring road;
and carrying out gridding processing on the class of monitoring roads according to the shooting range of the monitors, wherein each grid is provided with one monitor.
Optionally, in the method for preventing sand theft based on video monitoring and identification, the method for gridding the class of monitoring roads according to the shooting range of the monitor, where each grid is provided with a monitor includes:
let the shooting range of monitor be conical, and the conical bottom radius is r, then:
wherein R is the mounting height of the monitor, and θ is the viewing angle of the monitor;
gridding the monitoring roads so that the side length of each grid is not smaller than 2r;
And acquiring the central coordinate of each grid, wherein the central coordinate is the position of the monitor installed in each grid.
Optionally, in the method for preventing sand theft based on video monitoring and identification, the method for monitoring the road layout monitoring device further includes:
and if the grid comprises key points, the coordinates of the key points are the installation positions of the monitors.
Optionally, in the method for preventing sand theft based on video monitoring and identification, the method for judging whether sand theft occurs or not by the supervision center platform according to the monitoring video analysis shot by all monitors includes:
acquiring monitoring videos of all monitors, and extracting a target object from the monitoring videos;
judging whether the target objects extracted from the monitoring videos of different monitors are consistent, if so, summarizing the monitoring videos to obtain the existence time of the target objects;
if the existence time of the target object exceeds the preset time threshold, judging that sand theft occurs.
Optionally, in the method for preventing sand theft based on video monitoring and identification, the method for obtaining the monitoring videos of all the monitors and extracting the target object from the monitoring videos includes:
Coding all monitors according to the installation positions of the monitors to obtain identification codes of the monitors;
acquiring monitoring videos of all monitors, and carrying out framing treatment on each monitoring video to obtain a frame image corresponding to each monitor;
and processing the frame image by using a full-element AI label algorithm to extract a target object in the frame image.
Optionally, in the method for preventing sand theft based on video monitoring and identification, the method for judging whether the objects extracted from the monitoring videos of different monitors are consistent includes:
acquiring related information of targets in different monitoring videos, wherein the related information comprises video time points;
judging whether the time intervals between video time points of different monitoring videos with targets exceed an interval threshold, and if the time intervals do not exceed the interval threshold, extracting key feature points of the targets;
calculating the feature vector of each key feature point, and giving weight to each feature vector to obtain a feature vector set of each target object;
obtaining feature vectors with consistent feature points based on nearest neighbor matching, and obtaining the similarity of the target object based on the number and the weight of the feature vectors with consistent feature points;
And if the similarity of the target objects is greater than the similarity threshold, judging that the target objects are consistent.
Optionally, in the method for preventing sand theft based on video monitoring and identification, the method for sending out alarm information by the supervision center platform if the sand theft behavior is judged to occur includes:
if the sand stealing behavior is judged, the supervision center platform triggers an emergency response function, wherein the emergency response function comprises the following steps:
notifying an operator on duty according to a preset emergency response rule;
acquiring a final appearance position of a target object corresponding to sand stealing behavior, and sending the position to an attendant; and/or planning a blocking route according to the final appearance position of the target object corresponding to the sand stealing behavior, and sending the blocking route to an operator on duty.
In order to solve the technical problem, the invention also provides an anti-sand theft system based on video monitoring and identification, which comprises: a plurality of monitors; the monitoring center platform is in communication connection with all monitors; the supervision center platform comprises a video acquisition module, an analysis processing module and a decision notification module; the video acquisition module is used for acquiring a monitoring video shot by each monitor; the analysis processing module is used for analyzing and processing the monitoring video to judge whether sand stealing occurs or not; the decision notification module is used for sending out alarm information when the analysis processing module judges that sand theft occurs.
The invention provides a method and a system for preventing sand theft based on video monitoring identification, comprising the following steps: acquiring a map of an area to be monitored, and sketching a monitored road on the map; according to the monitoring road layout monitoring equipment, the monitoring equipment comprises a supervision center platform and a plurality of monitors, and the supervision center platform is in communication connection with all the monitors; the monitoring center platform analyzes and judges whether sand stealing occurs according to the monitoring videos shot by all the monitors; and if the sand stealing behavior is judged, the supervision center platform sends out alarm information. The monitor is reasonably and efficiently arranged by carrying out layout design on the area to be monitored, so that the effectiveness of monitoring is ensured on the basis of control cost; all monitoring videos are analyzed and judged through the monitoring center platform, so that the judgment accuracy is improved, further, the manpower waste caused after alarm information is sent out due to misjudgment can be avoided, and the problems of high cost and poor effect of the conventional illegal sand production monitoring scheme are solved.
Drawings
Fig. 1 is a flowchart of a method for preventing sand theft based on video monitoring and identification provided in this embodiment;
FIG. 2 is a diagram showing an example of a monitored road according to the present embodiment;
FIG. 3 is a logic diagram of object consistency determination according to the present embodiment;
fig. 4 is a schematic structural diagram of the anti-sand theft system based on video monitoring and identification according to the present embodiment;
fig. 5 is a schematic diagram of a specific structure and a function of the sand theft prevention system according to the present embodiment.
Detailed Description
The method and the system for preventing sand theft based on video monitoring identification provided by the invention are further described in detail below with reference to the accompanying drawings and the specific embodiments. It should be noted that the drawings are in a very simplified form and are all to a non-precise scale, merely for convenience and clarity in aiding in the description of embodiments of the invention. Furthermore, the structures shown in the drawings are often part of actual structures. In particular, the drawings are shown with different emphasis instead being placed upon illustrating the various embodiments.
It is noted that "first", "second", etc. in the description and claims of the present invention and the accompanying drawings are used to distinguish similar objects so as to describe embodiments of the present invention, and not to describe a specific order or sequence, it should be understood that the structures so used may be interchanged under appropriate circumstances. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
The embodiment provides a method for preventing sand theft based on video monitoring and identification, as shown in fig. 1, the method for preventing sand theft based on video monitoring and identification comprises the following steps:
s1, acquiring a map of an area to be monitored, and sketching a monitored road on the map;
s2, according to the monitoring road layout monitoring equipment, the monitoring equipment comprises a supervision center platform and a plurality of monitors, and the supervision center platform is in communication connection with all the monitors;
s3, the supervision center platform analyzes and judges whether sand theft occurs or not according to the monitoring videos shot by all the monitors;
and S4, if the sand stealing behavior is judged, the supervision center platform sends out alarm information.
According to the anti-sand theft method based on video monitoring identification, the monitor is reasonably and efficiently arranged by carrying out layout design on the area to be monitored, and the effectiveness of monitoring is ensured on the basis of control cost; all monitoring videos are analyzed and judged through the monitoring center platform, so that the judgment accuracy is improved, further, the manpower waste caused after alarm information is sent out due to misjudgment can be avoided, and the problems of high cost and poor effect of the conventional illegal sand production monitoring scheme are solved.
It should be noted that, in the specific application process, other steps may be added between the steps of the method, so as to improve the sand theft prevention performance or have other additional functions. Other modifications based on the above-described methods of the present application without departing from the spirit of the present application shall also fall within the scope of the present application.
Further, in this embodiment, step S1, a map of an area to be monitored is obtained, and a method for drawing a monitored road on the map includes:
s11, acquiring a map of the area to be monitored. Specifically, the area to be monitored generally comprises a river channel near the sand stope, and a map of the river channel near the sand stope with high precision can be obtained through satellites, or the map of the area to be monitored is drawn according to the exploitation evidence, drawings in related documents and other data. The map should be able to show the channel on which the sand mining ship can travel, the road on which trucks, tricycles and personnel can pass, and the places where sand is piled up, reserved or to be mined, etc. More precisely, the map should also be able to identify the length, width, etc. of the channel, road, etc. for subsequent calculation of the layout of the monitor.
And S12, according to geographic conditions, historical sand stealing behavior occurrence places, high risk areas and the like, the monitoring road is sketched on the map. Geographical conditions include natural river course that has already formed, road that the person lays, wharf, etc.; the historical sand stealing behavior is the place where sand stealing has occurred before, so that illegal sand sampling personnel are prevented from continuously working; the high-risk area is generally a place which is not easy to be reached by inspectors or a place which is not easy to be covered by monitoring, and a monitor can be specially arranged for the area to avoid monitoring dead angles.
Of course, in other embodiments, the principles of map source and road delineation may have other different designs, and the embodiment only uses the above examples to illustrate the possible solutions of the present application, and the scope of protection of the present application should not be limited thereto.
Still further, in this embodiment, step S2, the method for monitoring the road layout monitoring device according to the present invention includes:
s21, setting a non-key road section, a key point and other road sections on the monitored road, wherein the two ends of the non-key road section are key points. Specifically, in this embodiment, some road sections with low probability of sand theft are set as non-critical road sections, for example, road sections with probability of sand theft below 20%; setting a road section with higher probability of sand stealing as a key road section, such as a road section with more than 60% of sand stealing probability; other road segments than the non-critical road segment and the critical road segment. In practical application, the probability of sand theft is generally lower in the areas far away from the placer and the river bank, and the probability of sand theft is higher in the areas close to the placer, the warehouse and the hidden positions. And, in the present embodiment, the key points may include intersections of roads, entrances and exits of villages, end points of roads, docks and the like, and points where the probability of occurrence of sand theft is high, such as a sand storage point, a sand excavation point and the like.
S22, acquiring coordinates of the key points and coordinates of two end points of the non-key road section. Specifically, to facilitate installation of the subsequent monitor, the coordinates may be latitude and longitude coordinates, or scale coordinates formed with a specific reference object. The manner of coordinate acquisition is well known to those skilled in the art and will not be described in detail herein.
And S23, summarizing the coordinates of the key points and the coordinates of the two end points of the non-key road section, and removing the repeated coordinates to obtain the number of coordinates and a coordinate set, wherein the number of coordinates is the number of monitors, and each coordinate in the coordinate set is the installation position of each monitor. Considering that one end of a non-critical road segment is generally communicated with another road segment, and the intersection of the road is a key point coordinate, in this embodiment, the repeated coordinates are removed, so as to avoid calculation errors. Of course, in the actual application process, considering calculation deviation of the end point and the intersection point caused by actual conditions such as road width, the coordinates with the coordinate distance difference value within a certain range can be considered as repeated coordinates, if the distance difference between the two coordinates is smaller than 2m, the two coordinates are considered as repeated coordinates, and one of the two coordinates needs to be removed.
Fig. 2 shows an example of a layout of a monitor. As shown in fig. 2, gray lines represent monitored roads and black dots represent installed monitors. In this example, it can be seen that the sections where the monitor needs to be deployed in the area to be monitored include y1, y2, … …, y10 sections, so the total length l=y1+y2+ … … +y10 of the sections where the monitor needs to be deployed; the two ends of each road section are respectively provided with a monitor, the intersections of y10 and y1, y3, y5, y7 and y9 are respectively provided with a monitor, and the middle of the road of y9 and y10 is additionally provided with a monitor. Therefore, all monitoring roads can be covered by using the monitor, and the existence of monitoring dead angles is avoided. Of course, in other embodiments, since the layout of the monitored roads is different, the total length L of the monitored road segments (total length=sum of the lengths of all the monitored road segments) is also different, and the selection of the non-critical road segments in the monitored road segments is also required to be selected according to the actual situation, which is not described herein.
Taking the example shown in fig. 2 as an example, a point location set a= { x of monitor key points is obtained according to the monitoring area along the line and the important attention area 1 ，x 2 ，x 3 … … }, and the number of monitors corresponding to the key points is recorded as sum A The method comprises the steps of carrying out a first treatment on the surface of the Non-critical monitoring area road segment set b= { y 3 ,y 5 ,... } and the number of non-critical road segments is denoted sum B Since monitors are only arranged at the front and rear positions of the two ends of the non-critical road section, the number of monitors required for the non-critical road section is 2sum B The method comprises the steps of carrying out a first treatment on the surface of the Furthermore, in the present embodiment, the number sum of total monitors at this time C ＝sum A -2sum B 。
Preferably, in order to ensure the monitoring effectiveness, in this embodiment, step S2, the method for monitoring the road layout monitoring device further includes:
s24, removing the non-key road sections from the monitoring road to obtain a type of monitoring road;
s25, gridding the class of monitoring roads according to the shooting range of the monitors, wherein each grid is provided with one monitor.
Through gridding processing, the monitoring videos shot by a plurality of monitors are guaranteed to have geographic position consistency, and the number of monitors can be reduced as much as possible while monitoring blind areas are avoided, so that the cost is reduced.
Specifically, in this embodiment, the method for meshing the class of monitoring roads according to the shooting range of the monitor, where each mesh is provided with one monitor includes:
Let the shooting range of the monitor be conical (without considering the situation that the monitor sight is blocked), the bottom radius of the conical is r (i.e. the farthest distance the monitor can shoot), then:
wherein R is the mounting height of the monitor, and θ is the viewing angle of the monitor;
gridding the monitoring roads, numbering each grid to obtain n grids, and respectively marking each grid as D1, D2, … … and D n The total number of the grids is counted as sum g 。
And acquiring the central coordinate of each grid, wherein the central coordinate is the position of the monitor installed in each grid. Specifically, in the present embodiment, if the center coordinates of each grid are (m i ,n i ) The maximum value of the abscissa direction of the monitoring road is h, and the maximum value of the ordinate direction is l, and for each grid, the coordinate position of the deployment monitor is:
P Di ＝(h,n i ) Or (m) i -h,n i ) Wherein n is i ＜l，i＝1,2,……,n
Because the radius of the shooting range of the monitors is r, the shooting ranges of the adjacent monitors are ensured not to overlap by controlling the side length of the grid, so that the monitoring effect is ensured while the number of the monitors is reduced.
In the specific application process, the area of each grid can be different so as to adapt to different geographic environments and avoid the generation of monitoring dead angles. Of course, the area of each grid can also be adapted to the specifications of the monitors to be used, and when monitors with different monitoring ranges exist in the system, the areas and positions of the grids on which the monitors are installed should also be different.
Preferably, in the present embodiment, the number of monitors required for monitoring a road of one type is equal to the number sum of grids g Therefore, the number of monitors required for monitoring a road should satisfy:
in the above formula, since the width of the road can be covered by the monitor in general, only the length of the road, y, is considered i For monitoring the length of each road section of a road, y i I is the number of grids that can be divided for the road segment, with i being the grid length. Of course, in other embodiments, the relationship between the road size and the grid size needs to be set reasonably according to the monitoring range of the monitor.
In this embodiment, it is preferable that the side length dimension l of each grid is not less than 2r, i.e., l.gtoreq.2r, to control the number of monitors. The width of whole road can be covered to the control scope 2r of usual watch-dog, therefore, when setting up the watch-dog on the monitor road, the interval between the control watch-dog is not less than 2r can guarantee to be less in watch-dog quantity, guarantees can not appear the control blind area. In practical application, the side length of each grid can be set to be 2r, so that the calculation complexity of the monitor layout scheme can be reduced, and the monitoring videos shot by adjacent monitors can be spliced continuously.
In order to further reduce the number of monitors while ensuring the monitoring effect, in this embodiment, step S2, the method for monitoring the road layout monitoring device further includes:
s26, if the grid comprises key points, the coordinates of the key points are the installation positions of the monitors. That is, the monitor at the key point can be used to monitor the current grid area without additionally adding the monitor at the center point of the grid, thereby ensuring that the key point can be effectively monitored and the grid area can be monitored.
S27, the distance d between the coordinates of monitors in the monitoring road is not smaller than 2r, namely d is not smaller than 2r. It can be understood by those skilled in the art that since the monitoring roads include the critical road segments, other road segments and the critical points and the monitoring roads are communicated with each other with the non-critical road segments, the monitors at both ends of the critical road segments and the non-critical road segments can be fully utilized to realize the effective monitoring of the monitoring roads on the premise that the number of monitors is as small as possible. The monitor design of a type of monitoring road can be laid out according to actual conditions, and will not be described here again.
And S28, if the distance between any two coordinates among the coordinates of the key points, the coordinates of the two end points of the non-key road section and the center coordinates of the grid is smaller than 2r, eliminating any one of the coordinates so that the distance between any two coordinates is not smaller than 2r.
Specifically, it is assumed that for a monitoring item, only monitors with total sum can be configured under the limit of cost, wherein sum is used by key points and non-key road sections c A plurality of monitors, n grids share a sum g Monitors, then control sum c +sum g And is less than or equal to sum. In this way, monitors that overlap in monitoring range due to critical points, non-critical road segment ends, and close proximity in the grid must be reduced. In the present embodiment, a scheme in which the number of monitors is minimized is obtained by ensuring that the distance between any two coordinates is not less than 2 r. Of course, if the monitor number sum is currently calculated c +sum g And if the total number of monitors is smaller than sum of purchased monitors, filling some points according to the characteristics of the monitored road aiming at redundant monitors.
In addition, considering that the non-critical road segments are generally intersected with a type of monitoring road, in the embodiment, the length l of the constraint grid is not smaller than the distance d between the coordinates of the monitors in the adjacent grids, namely l is not smaller than d, so that the monitoring video formed by the monitoring visual fields of the monitors in each grid can be ensured to have no blind area.
In this embodiment, by setting monitor deployments of key points and non-key road sections and setting monitor deployments of a class of monitoring roads through gridding, full coverage of the whole area to be monitored can be satisfied. In addition, in order to reduce the number of monitors to save cost while ensuring the monitoring effect, the embodiment limits the monitoring range of the monitors, eliminates monitors with overlapping monitoring ranges, and reduces unnecessary monitors while ensuring that monitors are arranged at key points to ensure the monitoring effect.
Computer programming may be employed to implement specific calculations of monitor layout during specific applications. The implementation manner of the computer programming may be formed according to the implementation function by a person skilled in the relevant art, and this embodiment is not described herein.
Further, in this embodiment, step S3, the method for determining whether sand theft occurs according to analysis of monitoring videos captured by all the monitors by the monitoring center platform includes:
s31, acquiring monitoring videos of all monitors, and extracting target objects from the monitoring videos.
Specifically, in this embodiment, first, all monitors are encoded according to the installation positions of the monitors, so as to obtain identification codes of the monitors; then, acquiring monitoring videos of all monitors, and carrying out framing treatment on each monitoring video to obtain a frame image corresponding to each monitor; and then processing the frame image by using a full-element AI label algorithm to extract a target object in the frame image.
In this embodiment, objects, scenes, faces, and the like in the video image can be identified and classified by the full-element AI label algorithm, for example, personnel, farm vehicles, tricycles, tractors, trucks, sand carriers, iron plates, iron rakes, sand pumps, and the like in the image can be identified.
The full-element AI label algorithm can be integrated at the monitor end, so that the full-element AI label algorithm of each monitor is utilized to process the monitoring video shot by the monitor; the full-element AI label algorithm may also be set in a monitoring center platform, where the monitoring center platform may store the monitoring video of each monitor in a classified manner according to the identification code of the monitor and perform the full-element AI label algorithm processing, and the embodiment is not limited herein.
It should be noted that, the AI algorithm function adopted in this embodiment is obtained by a person skilled in the art through the prior art, for example, in this embodiment, the nearest neighbor algorithm KNN is specifically adopted to realize the identification of the target object.
S32, judging whether the target objects extracted from the monitoring videos of different monitors are consistent, and if so, summarizing the monitoring videos to acquire the existence time of the target objects.
Specifically, in this embodiment, referring to fig. 3, first, related information of the target object in different monitoring videos is acquired, where the related information includes, but is not limited to, a video time point, a location where the target object exists, a type of the target object (such as a person, a vehicle, a ship, a tool, etc.), a license plate number/ship number, and other target features such as a color of the target object, an identification code corresponding to the monitor, etc.
And then judging whether the time intervals between video time points of different monitoring videos with the target object exceed (are larger than) an interval threshold value, and if the time intervals do not exceed the interval threshold value, extracting key feature points of the target object. The interval threshold may be adjusted according to practical situations, for example, based on experience, the interval threshold is set to be 12 hours, so that when the time of two monitoring videos exceeds 12 hours, the two monitoring videos are considered to be incomparable, and even if the targets identified in the two monitoring videos are consistent, the two monitoring videos may not have consistency because the intervals before and after the shooting of the monitoring videos are too long, so that erroneous judgment is avoided.
Then, calculating the feature vector of each key feature point and giving weight to each feature vector to obtain a feature vector set of each target object. In this embodiment, the weight of the feature vector is set based on the weight distribution method of the information entropy, including the steps of preparing a data set, calculating the information entropy of each feature vector, normalizing the information entropy, and finally obtaining the distributed weight, and the information entropy weight distribution method adopted in this embodiment is well known to those skilled in the art and will not be described here again. Of course, in other embodiments, the feature vectors may be weighted in other ways, such as based on monitoring experience.
And then, based on nearest neighbor matching, obtaining feature vectors with consistent feature points, and based on the number and the weight of the feature vectors with consistent feature points, obtaining the similarity of the target object. Specifically, based on nearest neighbor matching, finding a feature vector closest to a second image according to the feature vector in the first image (frame image); judging whether the feature points are consistent or not according to the matched feature vector pairing calculation angle and the distance difference; and obtaining the similarity degree of the target object according to the number and the weight of the feature points of the matching consistency. The nearest neighbor matching method adopted in this embodiment is well known to those skilled in the art, and will not be described here again.
And finally, if the similarity of the target objects is greater than a similarity threshold, judging that the target objects are consistent. The similarity threshold may be set according to the actual situation, and in this embodiment, based on the above-mentioned method for determining the consistency of the target object, a similarity determination result with higher accuracy may be obtained, so the similarity threshold is set to 90%. Of course, if other methods for judging the consistency of the target objects are adopted, or the similarity threshold value is set to a lower value, such as 75%, due to the influence of the definition resolution of the monitoring video. In addition, based on the above-mentioned method for judging the consistency of the target object, in this embodiment, the similarity is obtained by using a feature matching algorithm (generally, a SIFT algorithm), so that the automatic judgment of the similarity of the target object can be realized by using the self-judging function of the SIFT algorithm, and the intelligent degree of the system is improved.
In a specific application process, in order to reduce complexity of similarity calculation, feature recognition can be performed on a target object with obvious features, for example, when relevant information extracted from the target object contains a license plate number, whether the license plate number is consistent or not can be judged; if the vehicle license plate number cannot be judged, the vehicle license plate number can be judged by the characteristics of the vehicle body (such as the color of the vehicle, the vehicle-mounted object, the ornament, the brand mark, the wheels, the characteristics of the vehicle head part and the like); if there are no obvious features, the feature recognition method described above may be employed.
And S33, if the existence time of the target object exceeds a preset time threshold, judging that sand theft occurs.
Specifically, in this embodiment, the identification codes of the monitors may be classified and managed, for example, the monitor at the key point is identified as class I, the monitor in the high risk area where sand theft occurs is identified as class II, and the monitors in the other areas are identified as class III; therefore, the monitoring pictures shot by monitors of different categories can be processed with different priorities and different frequencies, so that the system operation load is reduced, and meanwhile, the monitoring loopholes are prevented.
In this embodiment, the identified objects are sorted according to the time sequence and the monitor identification codes, and if the lengths of the objects in the monitoring videos shot by all monitors exceed a preset time threshold, the sand theft behavior is determined. It will be appreciated that if a vehicle is within the capture range of the monitoring system for a long period of time, it is possible to perform sand theft operations. Empirically, the preset time threshold in this embodiment is set to half an hour. Of course, in other embodiments, the preset time threshold may be set reasonably according to factors such as the area of the monitoring range and the average passing duration of the road surface.
In addition, considering that a plurality of targets may appear in the same monitoring video, it is impossible to match all targets in a uniform and corresponding manner in different monitoring videos, and then the targets with similarity lower than the similarity threshold are used as pending events to be temporarily stored together with the data of the monitoring video and the like. If one of the objects in the same monitoring video is determined to have sand theft, and the other objects are consistent with the action track (the time and the position in the monitoring video) of the object and exceed (are greater than) the preset time threshold, the undetermined event and the object are determined to have sand theft together. Of course, considering practical situations, such as the situation that the vehicle is in front of, and the person gets off, the action track of other objects may be considered consistent, in terms of consistency determination of the action track of the other objects and the object, for example, the time difference between the objects is within 5 minutes. And if the pending event is not judged to have sand theft within a certain time, the pending event can be marked as other, for example, if the pending event is not judged to have sand theft within 12 hours, the pending event can be marked as other. The specific determination time can be set according to the actual situation.
Further, in this embodiment, step S4, if it is determined that sand theft occurs, the method for sending out alarm information by the supervision center platform includes:
if the sand stealing behavior is judged, the supervision center platform triggers an emergency response function, wherein the emergency response function comprises the following steps:
A. and notifying the operator on duty according to a preset emergency response rule. In the embodiment, the shift table can be listed in the emergency response rule in consideration of the fact that the shift staff is on duty according to the shift table and the shift staff on different days according to the shift table, so that the shift staff on the same day can be notified according to the occurrence date of sand stealing. The notification mode is not limited to automatically sending a short message to the attendant or automatically calling the attendant's phone, etc. In addition, the monitoring center platform can send out alarms to the monitor corresponding to sand stealing actions, such as changing color of an indicator lamp, sending out alarm buzzing, and displaying monitoring pictures of the monitor in an enlarged manner by a display screen.
B. And acquiring the final appearance position of the target object corresponding to the sand stealing behavior, and sending the position to an operator on duty. In this embodiment, the identification code of the monitor may be used to obtain the geographic location coordinate of the monitor, so as to automatically calculate the location of the target object according to the monitoring video. Of course, considering the mobility of the target object, the possible moving path of the target object can be calculated based on a model algorithm, and the possible arriving position and the corresponding time point of the target object can be predicted, so that the capture of the person on duty is facilitated.
C. And planning a blocking route according to the final appearance position of the target object corresponding to the sand stealing behavior, and sending the blocking route to an on-duty person. In this embodiment, the blocking route may be automatically planned by using a model algorithm according to the geographic location where the monitor is located, the moving direction of the target object, and the like.
The model algorithm for implementing the position prediction and the blocking route planning in this embodiment is well known to those skilled in the art, and will not be described herein. It should be noted that any position prediction and blocking route planning scheme without departing from the spirit of the present application shall fall within the scope of the present application.
The embodiment also provides a sand theft prevention system based on video monitoring and identification, as shown in fig. 4, the sand theft prevention system based on video monitoring and identification comprises: a plurality of monitors; the monitoring center platform is in communication connection with all monitors; the supervision center platform comprises a video acquisition module, an analysis processing module and a decision notification module; the video acquisition module is used for acquiring a monitoring video shot by each monitor; the analysis processing module is used for analyzing and processing the monitoring video to judge whether sand stealing occurs or not; the decision notification module is used for sending out alarm information when the analysis processing module judges that sand theft occurs.
According to the anti-sand theft system based on video monitoring identification, through layout design of the area to be monitored, the monitor is reasonably and efficiently arranged, and the effectiveness of monitoring is guaranteed on the basis of control cost; all monitoring videos are analyzed and judged through the monitoring center platform, so that the judgment accuracy is improved, further, the manpower waste caused after alarm information is sent out due to misjudgment can be avoided, and the problems of high cost and poor effect of the conventional illegal sand production monitoring scheme are solved.
Specifically, in this embodiment, the monitor is set at a specified position of the area to be monitored according to a preset layout manner, and is in communication connection with the video acquisition module of the supervision center platform. The video acquisition module is used for preprocessing the monitoring video after acquiring the monitoring video of the monitor, and the preprocessing comprises the step of making a corresponding relation between the monitoring video and the monitor (for example, an identification code for identifying the monitor on the monitoring video). The analysis processing module receives the monitoring video preprocessed by the video acquisition module, and carries out framing processing, object identification and extraction, object similarity judgment and the like on the monitoring video; and judging the stay area and time of the target object which is important to pay attention to, for example, a truck, a sand collecting ship or equipment which can be used for sand theft such as a sand pump, a tractor, a tricycle and the like, wherein the target object is listed as the target object which is important to pay attention to, and when the stay time of the target object in a key area (a key point and other areas which are easy to cause sand theft) exceeds a preset time threshold value, the sand theft is judged to occur. The decision notification module acquires related data of sand stealing behavior, including photographed monitors (including identification codes, position information and the like), judged original monitoring videos, time of the monitoring videos and the like, and then gives an alarm to an attendant according to the information, including notifying the attendant of the place where the sand stealing behavior occurs, the current state of the sand stealing behavior, a possible escape route, a blocking route and the like.
Preferably, in order to improve the capturing effectiveness, a plurality of blocking routes can be provided, and the blocking routes can be specifically set according to the number of operators on duty. In addition, the dispatching module can be arranged on the monitoring center platform, the current monitoring video of sand stealing behavior can be displayed on the monitoring center platform in real time through the dispatching module, and the on-duty personnel can communicate in real time in a communication mode conveniently, and the capturing scheme is adjusted. Even after judging that sand theft occurs, the supervision center platform automatically stores relevant information of relevant monitoring videos and targets so as to facilitate subsequent law enforcement departments to retrieve evidence.
Fig. 5 is a schematic diagram of a specific structure and a specific corresponding relation of a sand theft prevention system based on video monitoring identification. As can be seen from a specific example shown in fig. 5, the sand theft prevention system includes an acquisition management module, an image recognition module, a behavior analysis module, and an emergency response module. In this embodiment, since the monitor itself has an AI analysis function, the monitor has an acquisition management module for implementing functions such as capturing (data acquisition) of a monitoring video, data transmission and storage, data preprocessing, and identification of video data. The image recognition module, the behavior analysis module and the emergency response module are integrated on the monitoring center platform, wherein the image recognition module and the behavior analysis module are equivalent to the analysis processing module, and the emergency response module is equivalent to the decision notification module.
The acquisition management module is a module used for acquiring monitoring data in the system, and is mainly responsible for carrying out data communication with the monitor, receiving video data, AI identification result data and the like sent by the monitor, preprocessing the data, analyzing a data format, verifying the validity of the data and the like. The acquisition management module is also responsible for storing these data in a database (which may be built into the regulatory center platform) or sending them to other modules for further processing and analysis via a message queue.
If the monitor does not have the AI function, the acquisition management module acquires the video data of the monitor and then sends the video data to the image recognition module for carding. If the monitor has the AI function, the monitor can send video streams or pictures of the identified personnel, vehicles (agricultural vehicles, tricycles, tractors and the like) and tools (iron plates, iron rakes, sand pumps and the like) to the acquisition management module, and the acquisition management module pre-processes the data and then sends the data to the behavior analysis module directly.
The image recognition module is mainly used for recognizing and classifying objects, scenes, faces and the like in the video image through a series of AI models, for example, people, agricultural vehicles, tricycles, tractors, iron plates, iron rakes, sand pumps and the like in the image can be recognized. The method comprises the following specific steps: decomposing the video into a series of frame images; finding out a target object in the image of each frame through a full-element AI label algorithm; marking the position and the category of the target object found in the image, and extracting related information records of the target object, such as image time, vehicle license plate number, vehicle color, monitor codes for shooting the video, and the like; and sending the marked video image and the extracted related information thereof to a behavior analysis module for further processing and analysis.
The behavior analysis module is mainly used for detecting and identifying abnormal behaviors and improving the discovery probability of abnormal events. In a specific application scene, the sand stealing behavior is identified mainly after the transmitted video is comprehensively analyzed. The method comprises the following specific steps: the marked video image sent in real time enters a comparison area and needs to be compared with the video image marked in the first n hours (n can be adjusted according to actual conditions and is 12 hours by default) in the sample; if the object similarity is greater than a similarity threshold (where the similarity threshold is set to 90%), then the objects in the two images are considered to be identical; otherwise, marking the video of the new object and giving a sample number; sequencing video images with the same judgment target object and related information thereof into the same undetermined event according to time sequence; position judgment is carried out on monitor codes in undetermined events, if monitors in key monitoring areas appear, video information of the monitors is extracted, and if the last time displayed by the video information of the key monitoring areas is consistent with the latest time of undetermined events and the current time is different by more than m hours (m can be adjusted according to practice and is half an hour by default), the undetermined events are judged to be sand stealing behavior events together with high probability; if the undetermined event is not judged to be sand stealing behavior within s hours (s can be adjusted according to actual conditions and is 12 hours by default), the label is updated to be other.
Specifically, when the acquisition management module has identified video data, the behavior analysis module marks the videos as important concerns and analyzes the videos: if the stay time of the important attention vehicle entering the important attention area exceeds a set value, marking as an abnormal event, considering that sand stealing behavior occurs, and giving a suggested path capable of preventing the sand stealing behavior by combining with a video situation, sending a judging result and the suggested path to an emergency response module by a behavior analysis module, and sending the judging result and the suggested path to an operator on duty by the emergency response module according to a set notification rule so as to enable the operator on duty to make processing timely.
And when the acquisition management module does not recognize the video data, the image recognition module analyzes and judges the video data to determine whether heavy point targets such as agricultural vehicles, tricycles, tractors, sand pumps and the like appear, and if the targets are determined to appear, the behavior analysis module marks the videos as important attention and analyzes the videos: if the stay time of the important attention vehicle entering the important attention area exceeds a set value, marking as an abnormal event, considering that sand stealing behavior occurs, and giving a suggested path capable of preventing the sand stealing behavior by combining with a video situation, sending a judging result and the suggested path to an emergency response module by a behavior analysis module, and sending the judging result and the suggested path to an operator on duty by the emergency response module according to a set notification rule so as to enable the operator on duty to make processing timely.
Preferably, in this embodiment, a device management module may also be provided, which is mainly used for managing and monitoring the monitor connected to the supervision center platform. For example, the device management module may provide monitor registration, identification, authentication, maintenance, and configuration functions; the online state, the running condition and the like of the monitor can be checked; and, batch management of monitors can also be performed, such as packet management (mainly used for grouping monitors according to whether they are in critical monitoring areas, whether they are in non-critical monitoring areas, whether they are critical points, acquisition frequency, etc.), rights management (mainly used for giving monitors who can view, operate, modify, etc.), etc.
In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the difference from other embodiments, so that the same similar parts of each embodiment are referred to each other.
The method and system for preventing sand theft based on video monitoring identification provided by the embodiment comprise the following steps: acquiring a map of an area to be monitored, and sketching a monitored road on the map; according to the monitoring road layout monitoring equipment, the monitoring equipment comprises a supervision center platform and a plurality of monitors, and the supervision center platform is in communication connection with all the monitors; the monitoring center platform analyzes and judges whether sand stealing occurs according to the monitoring videos shot by all the monitors; and if the sand stealing behavior is judged, the supervision center platform sends out alarm information. The monitor is reasonably and efficiently arranged by carrying out layout design on the area to be monitored, so that the effectiveness of monitoring is ensured on the basis of control cost; all monitoring videos are analyzed and judged through the monitoring center platform, so that the judgment accuracy is improved, further, the manpower waste caused after alarm information is sent out due to misjudgment can be avoided, and the problems of high cost and poor effect of the conventional illegal sand production monitoring scheme are solved.
The above description is only illustrative of the preferred embodiments of the present invention and is not intended to limit the scope of the present invention, and any alterations and modifications made by those skilled in the art based on the above disclosure shall fall within the scope of the appended claims.
Claims (8)
1. The sand theft prevention method based on video monitoring and identification is characterized by comprising the following steps of:
acquiring a map of an area to be monitored, and sketching a monitored road on the map;
according to the monitoring road layout monitoring equipment, the monitoring equipment comprises a supervision center platform and a plurality of monitors, and the supervision center platform is in communication connection with all the monitors;
the monitoring center platform analyzes and judges whether sand stealing occurs according to the monitoring videos shot by all the monitors;
if the sand stealing behavior is judged to occur, the supervision center platform sends out alarm information;
the method for monitoring the road layout monitoring equipment comprises the following steps:
setting a non-key road section, a key road section, key points and other road sections on the monitoring road, wherein the two ends of the non-key road section are key points;
acquiring coordinates of the key points and coordinates of two end points of the non-key road section;
Summarizing the coordinates of the key points and the coordinates of the two end points of the non-key road section, and removing the repeated coordinates to obtain the number of coordinates and a coordinate set, wherein the number of coordinates is the number of monitors, and each coordinate in the coordinate set is the installation position of each monitor.
2. The method for preventing sand theft based on video monitoring identification according to claim 1, wherein the method for monitoring road layout monitoring equipment further comprises:
removing the non-key road sections from the monitoring road to obtain a type of monitoring road;
and carrying out gridding processing on the class of monitoring roads according to the shooting range of the monitors, wherein each grid is provided with one monitor.
3. The method for preventing sand theft based on video monitoring and identification according to claim 2, wherein the method for gridding the class of monitoring roads according to the shooting range of the monitor, wherein each grid is provided with one monitor comprises the following steps:
let the shooting range of monitor be conical, and the conical bottom radius is r, then:
wherein R is the mounting height of the monitor, and θ is the viewing angle of the monitor;
Gridding the monitoring roads so that the side length of each grid is not smaller than 2r;
and acquiring the central coordinate of each grid, wherein the central coordinate is the position of the monitor installed in each grid.
4. The method for preventing sand theft based on video monitoring identification according to claim 3, wherein the method for monitoring road layout monitoring equipment further comprises:
and if the grid comprises key points, the coordinates of the key points are the installation positions of the monitors.
5. The method for preventing sand theft based on video monitoring and identification according to claim 1, wherein the method for judging whether sand theft occurs or not by the monitoring center platform according to the monitoring video analysis shot by all the monitors comprises the following steps:
acquiring monitoring videos of all monitors, and extracting a target object from the monitoring videos;
judging whether the target objects extracted from the monitoring videos of different monitors are consistent, if so, summarizing the monitoring videos to obtain the existence time of the target objects;
if the existence time of the target object exceeds the preset time threshold, judging that sand theft occurs.
6. The method for preventing sand theft based on video monitoring and identification according to claim 5, wherein the method for acquiring the monitoring videos of all monitors and extracting the target object from the monitoring videos comprises the following steps:
Coding all monitors according to the installation positions of the monitors to obtain identification codes of the monitors;
acquiring monitoring videos of all monitors, and carrying out framing treatment on each monitoring video to obtain a frame image corresponding to each monitor;
and processing the frame image by using a full-element AI label algorithm to extract a target object in the frame image.
7. The method for preventing sand theft based on video monitoring and identification according to claim 5, wherein the method for judging whether the objects extracted from the monitoring videos of different monitors are consistent comprises:
acquiring related information of targets in different monitoring videos, wherein the related information comprises video time points;
judging whether the time intervals between video time points of different monitoring videos with targets exceed an interval threshold, and if the time intervals do not exceed the interval threshold, extracting key feature points of the targets;
calculating the feature vector of each key feature point, and giving weight to each feature vector to obtain a feature vector set of each target object;
obtaining feature vectors with consistent feature points based on nearest neighbor matching, and obtaining the similarity of the target object based on the number and the weight of the feature vectors with consistent feature points;
And if the similarity of the target objects is greater than the similarity threshold, judging that the target objects are consistent.
8. The method for preventing sand theft based on video monitoring and identification according to claim 5, wherein the method for sending out alarm information by the supervision center platform if the sand theft is judged to occur comprises the following steps:
if the sand stealing behavior is judged, the supervision center platform triggers an emergency response function, wherein the emergency response function comprises the following steps:
notifying an operator on duty according to a preset emergency response rule;
acquiring a final appearance position of a target object corresponding to sand stealing behavior, and sending the position to an attendant; and/or planning a blocking route according to the final appearance position of the target object corresponding to the sand stealing behavior, and sending the blocking route to an operator on duty.
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