A security monitoring camera equipment monitoring system and monitoring method

Abstract

The present application discloses a security monitoring camera equipment monitoring system and a monitoring method, and relates to the field of camera equipment monitoring technology. The present application includes a camera data acquisition and analysis module, a visual analysis module, a mobile object data acquisition and analysis module, a monitoring target analysis module, a main control terminal, and a database. By analyzing the camera images of each camera device, it is determined whether each camera device is abnormal, thereby solving the limitation problems existing in the feasibility analysis process of the current security monitoring equipment monitoring development. At the same time, the mobile objects appearing in the camera device are analyzed to obtain the monitoring target, and the real-time position of the detection target is analyzed. The main control terminal issues an early warning prompt to the camera device with abnormality, and at the same time, the illuminator of the camera device corresponding to the monitoring area to which the monitoring target belongs is turned on, thereby ensuring that the security personnel can quickly lock the monitoring target position.

Description

Technical Field

[0001] The present application relates to the technical field of camera equipment monitoring, and in particular to a security monitoring camera equipment monitoring system and a monitoring method. Background Art

[0002] With the development of science and technology, security monitoring is widely used in all walks of life. In the monitoring of the same type of security monitoring camera equipment, doing a good job of abnormal detection of monitoring equipment and tracking of monitoring targets is the key and core of security monitoring.

[0003] At present, security monitoring mainly analyzes the data of moving objects appearing in the monitoring area of ​​the monitoring equipment. Obviously, this analysis method has the following problems:

[0004] Currently, there is a lack of analysis of the surveillance images of each camera device based on the clarity and occlusion area corresponding to each camera image. This cannot avoid losses caused by unclear camera images or camera occlusion, which reduces the security effect to a certain extent. In addition, there is no abnormal prompt, which may result in security personnel being unable to promptly detect abnormal camera devices among the various camera devices.

[0005] 2. Currently, there is a lack of analysis of relevant data on moving objects entering the monitoring screen, and the screen of the main camera equipment cannot be projected onto the largest screen of the display terminal in real time. It may not be possible to reduce the time for zooming in the monitoring screen in an emergency, which reduces the security effect of the monitoring camera equipment to a certain extent. The monitoring area where the monitoring target is located is not further locked, so that when the security personnel arrive at the scene at night, they cannot accurately find the location of the monitoring target, which reduces the work efficiency of the security personnel and cannot guarantee the security effect. Summary of the invention

[0006] In view of the above-mentioned technical deficiencies, the purpose of this application is to provide a security monitoring camera equipment monitoring system and monitoring method.

[0007] In order to solve the above-mentioned technical problems, the present application adopts the following technical solutions: In the first aspect, the present application provides a security monitoring camera equipment monitoring system, the method comprising the following modules: a camera data acquisition and analysis module, used to acquire each photographic image of each camera device, and transmit each camera image to a visual analysis module, and then output the clarity and occlusion area corresponding to each camera image of each camera device, and then analyze and obtain the camera picture evaluation coefficient of each camera device, and judge whether each camera device has an abnormality.

[0008] The mobile object data acquisition and analysis module is used to obtain the human shape similarity and temperature of the mobile object when a mobile object enters the monitoring area of ​​a certain camera device, and then analyze and obtain the target similarity evaluation coefficient of the mobile object, so as to determine whether the mobile object is a monitoring target.

[0009] The monitoring target analysis module is used to obtain the real-time position coordinates of the monitoring target when a moving object is the monitoring target, and obtain the center point coordinates of the monitoring area of ​​each camera device, and then analyze and obtain the distance evaluation coefficient of each camera device, so as to determine the main camera device of the monitoring target.

[0010] The main control terminal is used to give an abnormal prompt when a certain camera device has an abnormality; project the monitoring screen of the main camera device of the monitored target on the largest screen of the display terminal, and control the main camera device to turn on the lighting.

[0011] Preferably, the analysis obtains the clarity evaluation coefficient of each camera device, and the specific analysis process is as follows: the clarity and the occlusion area corresponding to each camera image of each camera device are respectively recorded as and ,in Indicates the number corresponding to each camera device. , It is expressed as the total number of camera devices, is a natural integer greater than or equal to 1; It represents the number corresponding to each camera image. , is the total number of camera images, is a natural integer greater than or equal to 1.

[0012] According to the calculation formula Get the first The clarity evaluation factor of the camera device , where e is a natural integer, It is represented as the reference value of the clarity of the camera image in the database. It is represented as the reference value of the occlusion area of ​​the camera image in the database, and It is represented by the weight factor corresponding to the clarity of the camera image in the database and the weight factor corresponding to the occlusion area.

[0013] Preferably, the specific judgment process of judging whether each camera device has an abnormality is as follows: comparing the clarity assessment coefficient of each camera device with the clarity assessment coefficient threshold in the database; when the clarity assessment coefficient of a certain camera device is greater than or equal to the clarity assessment coefficient threshold in the database, the camera device is judged to have an abnormality; otherwise, the camera device is judged to have no abnormality, thereby judging whether each camera device has an abnormality.

[0014] Preferably, the analysis obtains the target similarity evaluation coefficient of the moving object, and the specific analysis process is as follows: the human shape similarity and temperature of the moving object are respectively recorded as and , substitute into the calculation formula Obtain the target similarity evaluation coefficient of the moving object ,in Expressed as a natural integer, It is represented as the reference value of the humanoid similarity of the moving objects in the database. It is expressed as the influence value of the temperature of the moving object in the database, Represents the reference value of the temperature of the moving object in the database, The allowed floating value of the temperature of the moving object in the database is expressed as: and It is represented by the weight factor corresponding to the humanoid similarity of the moving object in the database and the weight factor corresponding to the temperature.

[0015] Preferably, the specific judgment process for judging whether the moving object is a monitoring target is as follows: comparing the target similarity assessment coefficient of the moving object with the target similarity assessment coefficient threshold in the database; when the target similarity assessment coefficient of the moving object is greater than or equal to the target similarity assessment coefficient threshold in the database, the moving object is judged not to be a monitoring target; otherwise, the moving object is judged to be a monitoring target.

[0016] Preferably, the analysis obtains the distance evaluation coefficient of each camera device, and the specific analysis process is as follows: the real-time position coordinates of the monitored target are marked as , and mark the center coordinates of the monitoring area of ​​each camera device as , substitute into the calculation formula Get the first Camera distance evaluation factor ,in Represents the reference value of the camera device distance in the database.

[0017] Preferably, the main camera device of the monitoring target is determined by the following specific determination process: the distance evaluation coefficients of the various camera devices are arranged from small to large, and the camera device corresponding to the smallest camera device distance evaluation coefficient is used as the main camera device of the monitoring target.

[0018] It also includes a database for storing reference values ​​of the clarity of the camera image, reference values ​​of the occlusion area, weight factors corresponding to the clarity and weight factors corresponding to the occlusion area, storing clarity evaluation coefficient thresholds, storing reference values ​​of the human figure similarity of moving objects, temperature influence values, reference values ​​of temperature, allowable floating values ​​of temperature, weight factors corresponding to the human figure similarity and weight factors corresponding to the temperature, storing target similarity evaluation coefficient thresholds, and storing reference values ​​of the camera device distance.

[0019] In a second aspect, the present application provides a method for monitoring security surveillance camera equipment, comprising the following steps: Step 1, camera data acquisition and analysis: acquire each photographic image of each camera device, and transmit each camera image to a visual analysis module, and then output the clarity and occlusion area corresponding to each camera image of each camera device, and then analyze and obtain the camera picture evaluation coefficient of each camera device, and determine whether each camera device has an abnormality.

[0020] Step 2: Mobile object data acquisition and analysis: When a mobile object enters the monitoring area of ​​a camera device, the human shape similarity and temperature of the mobile object are obtained, and then the target similarity evaluation coefficient of the mobile object is analyzed to determine whether the mobile object is a monitoring target.

[0021] Step 3: Analyze the monitoring target: When a moving object is the monitoring target, obtain the real-time position coordinates of the monitoring target and the center point coordinates of the monitoring area of ​​each camera device, and then analyze and obtain the distance evaluation coefficient of each camera device, so as to determine the main camera device of the monitoring target.

[0022] Main control terminal: When a camera device has an abnormality, an abnormal prompt will be given; the monitoring screen of the main camera device of the monitored target will be projected on the largest screen of the display terminal, and the main camera device will be controlled to turn on the lighting.

[0023] The beneficial effects of the present application are as follows: 1. A security monitoring camera equipment monitoring system and monitoring method provided by the present application analyzes the camera images of each camera device to determine whether each camera device has an abnormality, thereby solving the limitations existing in the feasibility analysis process of the current security monitoring equipment monitoring development. At the same time, the moving objects appearing in the camera device are analyzed to obtain the monitoring target, and the real-time position of the detection target is analyzed. The main control terminal issues an early warning prompt for the abnormal camera device, and at the same time turns on the illuminator of the camera device corresponding to the monitoring area to which the monitoring target belongs, thereby ensuring that the security personnel can quickly lock the monitoring target position.

[0024] 2. This application analyzes the surveillance images of the camera equipment to avoid losses caused by unclear camera images or camera obstructions. The obstruction of the surveillance equipment may also be caused by human factors. For example, a person attempting to invade may remotely spray an unknown liquid onto the camera equipment, thereby making the camera equipment unable to operate normally and allowing the intruder to take the opportunity to enter. Regularly monitoring the camera equipment for abnormalities can improve the security effect to a certain extent and provide abnormal prompts so that security personnel can detect abnormalities in the camera equipment in a timely manner.

[0025] 3. This application analyzes the relevant data of moving objects entering the monitoring screen to avoid false warnings, which saves time for security personnel to a certain extent. The volume and temperature of moving objects can be detected by infrared thermal imagers. Because the volume and temperature of the human body are different from those of other animals, combining these two data for analysis can accurately determine whether the moving object is a monitoring target.

[0026] 4. This application projects the image of the main camera device to the largest screen of the display terminal in real time, which is convenient for security personnel to observe and track the monitored target, reduces the time for manually choosing to enlarge the monitoring image in an emergency, and improves the security effect of the monitoring camera equipment to a certain extent. At the same time, the illuminator of the main camera device is turned on to further lock the position of the monitored target, so that security personnel can accurately find the position of the monitored target when they arrive at the scene at night, which increases the work efficiency of security personnel and ensures the security effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0028] Figure 1 This is a schematic diagram of the system structure connection for this application.

[0029] Figure 2 The figure is a flowchart of the implementation steps of the present application method. DETAILED DESCRIPTION

[0030] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0031] See also Figure 1 As shown, the present application provides a security monitoring camera equipment monitoring system in the first aspect, including the following modules: camera data acquisition and analysis module, visual analysis module, mobile object data acquisition and analysis module, monitoring target analysis module, main control terminal, and database.

[0032] The camera data acquisition and analysis module is used to acquire each photographic image of each camera device and transmit each camera image to the visual analysis module, and then output the clarity and occlusion area corresponding to each camera image of each camera device, and then analyze and obtain the camera picture evaluation coefficient of each camera device, and determine whether each camera device has any abnormality.

[0033] In a specific example, the analysis obtains the clarity evaluation coefficient of each camera device. The specific analysis process is as follows: the clarity and the occlusion area corresponding to each camera image of each camera device are respectively recorded as and ,in Indicates the number corresponding to each camera device. , It is expressed as the total number of camera devices, is a natural integer greater than or equal to 1; It represents the number corresponding to each camera image. , is the total number of camera images, is a natural integer greater than or equal to 1.

[0034] According to the calculation formula Get the first The clarity evaluation factor of the camera device , where e is a natural integer, It is represented as the reference value of the clarity of the camera image in the database. It is represented as the reference value of the occlusion area of ​​the camera image in the database, and It is represented by the weight factor corresponding to the clarity of the camera image in the database and the weight factor corresponding to the occlusion area.

[0035] It should be noted that the weight factors corresponding to the clarity of the camera image and the weight factors corresponding to the occlusion area are obtained by factor analysis. First, the information of clarity and dirty area is condensed, and then the variance explanation rate after rotation is obtained. The weight is obtained by dividing the cumulative variance explanation rate.

[0036] It should be noted that factor analysis is a well-known technology. It is a multivariate statistical analysis method that starts from studying the internal dependencies of variables and reduces some variables with intricate relationships to a few comprehensive factors; information concentration is expressed as calculating the median; the variance explanation rate is the amount of information extracted by the factor, and the variance explanation rate = characteristic root / total number of analysis items; the variance explanation rate after rotation is expressed as the variance explanation rate of the factor after maximum variance rotation.

[0037] It should be noted that the visual analysis algorithm is used in the visual analysis module.

[0038] In a specific example, the determination of whether each camera device has an abnormality is performed as follows: the clarity assessment coefficient of each camera device is compared with the clarity assessment coefficient threshold in the database; when the clarity assessment coefficient of a camera device is greater than or equal to the clarity assessment coefficient threshold in the database, the camera device is determined to have an abnormality; otherwise, the camera device is determined to have no abnormality, thereby determining whether each camera device has an abnormality.

[0039] The present application analyzes the surveillance images of the camera equipment to avoid losses caused by unclear camera images or camera obstructions. The obstruction of the surveillance equipment may also be man-made. For example, a person attempting to invade may remotely spray an unknown liquid onto the camera equipment, thereby rendering the camera equipment unable to operate normally and allowing the intruder to take the opportunity to enter. Regularly monitoring the camera equipment images for abnormalities can improve the security effect to a certain extent and provide abnormal prompts so that security personnel can detect abnormalities in the camera equipment in a timely manner.

[0040] The mobile object data acquisition and analysis module is used to obtain the human shape similarity and temperature of the mobile object when a mobile object enters the monitoring area of ​​a certain camera device, and then analyze and obtain the target similarity evaluation coefficient of the mobile object, so as to determine whether the mobile object is a monitoring target.

[0041] In a specific example, the analysis obtains the target similarity evaluation coefficient of the moving object. The specific analysis process is as follows: the human shape similarity and temperature of the moving object are respectively recorded as and , substitute into the calculation formula Obtain the target similarity evaluation coefficient of the moving object ,in Expressed as a natural integer, It is represented as the reference value of the humanoid similarity of the moving objects in the database. It is expressed as the influence value of the temperature of the moving object in the database, Represents the reference value of the temperature of the moving object in the database, It is expressed as the allowable floating value of the temperature of the moving object in the database. and It is represented by the weight factor corresponding to the humanoid similarity of the moving object in the database and the weight factor corresponding to the temperature.

[0042] It should be noted that the weight factors corresponding to the humanoid similarity and the temperature of the moving object are obtained by factor analysis. First, the information of humanoid similarity and temperature is condensed, and then the variance explanation rate after rotation is obtained. The weight is obtained by dividing the cumulative variance explanation rate.

[0043] In a specific example, the determination of whether a moving object is a monitoring target is carried out as follows: the target similarity evaluation coefficient of the moving object is compared with the target similarity evaluation coefficient threshold in the database. When the target similarity evaluation coefficient of the moving object is greater than or equal to the target similarity evaluation coefficient threshold in the database, the moving object is judged not to be a monitoring target, otherwise the moving object is judged to be a monitoring target.

[0044] It should be noted that an infrared thermal imager is used to obtain the volume and temperature of the moving object.

[0045] This application analyzes the relevant data of moving objects entering the monitoring screen to avoid false warnings, saving time for security personnel to a certain extent. The volume and temperature of the moving object can be detected by the infrared thermal imager. Because the volume and temperature of the human body are different from those of other animals, combining these two data for analysis can accurately determine whether the moving object is a monitoring target.

[0046] The monitoring target analysis module is used to obtain the real-time position coordinates of the monitoring target when a moving object is the monitoring target, and obtain the center point coordinates of the monitoring area of ​​each camera device, and then analyze and obtain the distance evaluation coefficient of each camera device, so as to determine the main camera device of the monitoring target.

[0047] In a specific example, the analysis obtains the distance evaluation coefficient of each camera device, and the specific analysis process is as follows: the real-time position coordinates of the monitored target are marked as , and mark the center coordinates of the monitoring area of ​​each camera device as , substitute into the calculation formula Get the first Camera distance evaluation factor ,in Represents the reference value of the camera device distance in the database.

[0048] In a specific example, the main camera device of the monitoring target is determined by the following specific determination process: the distance evaluation coefficients of the camera devices are arranged from small to large, and the camera device corresponding to the smallest camera device distance evaluation coefficient is used as the main camera device of the monitoring target.

[0049] The main control terminal is used to give an abnormal prompt when a certain camera device has an abnormality; project the monitoring screen of the main camera device of the monitored target on the largest screen of the display terminal, and control the main camera device to turn on the lighting.

[0050] It should be noted that the display terminal displays the monitoring images of all camera devices. When there is no monitoring target, the monitoring images are of the same size. When a monitoring target appears, the screen of the display terminal will automatically change into a largest screen and several small screens, among which the largest screen will display the monitoring image of the main camera device.

[0051] This application projects the image of the main camera device to the largest screen of the display terminal in real time, which is convenient for security personnel to observe and track the monitored target, reduces the time of manually choosing to enlarge the monitoring image in an emergency, and improves the security effect of the monitoring camera equipment to a certain extent. At the same time, the illuminator of the main camera device is turned on to further lock the position of the monitored target, so that security personnel can accurately find the position of the monitored target when they arrive at the scene at night, which increases the work efficiency of security personnel and ensures the security effect.

[0052] In a specific example, a database is also included for storing reference values ​​of clarity of camera images, reference values ​​of occlusion areas, weight factors corresponding to clarity and weight factors corresponding to occlusion areas, clarity evaluation coefficient thresholds, reference values ​​of human-shaped similarity of moving objects, temperature influence values, reference values ​​of temperature, allowable floating values ​​of temperature, weight factors corresponding to human-shaped similarity and weight factors corresponding to temperature, target similarity evaluation coefficient thresholds, and reference values ​​of camera device distances.

[0053] See also Figure 2 As shown, the present application provides a security surveillance camera equipment monitoring method in the second aspect, including the following steps: Step 1, camera data acquisition and analysis: acquire each photographic image of each camera device, and transmit each camera image to the visual analysis module, and then output the clarity and occlusion area corresponding to each camera image of each camera device, and then analyze and obtain the camera picture evaluation coefficient of each camera device, and determine whether each camera device has an abnormality.

[0054] Step 2: Mobile object data acquisition and analysis: When a mobile object enters the monitoring area of ​​a camera device, the human shape similarity and temperature of the mobile object are obtained, and then the target similarity evaluation coefficient of the mobile object is analyzed to determine whether the mobile object is a monitoring target.

[0055] Step 3: Analyze the monitoring target: When a moving object is the monitoring target, obtain the real-time position coordinates of the monitoring target and the center point coordinates of the monitoring area of ​​each camera device, and then analyze and obtain the distance evaluation coefficient of each camera device, so as to determine the main camera device of the monitoring target.

[0056] Main control terminal: When a camera device has an abnormality, an abnormal prompt will be given; the monitoring screen of the main camera device of the monitored target will be projected on the largest screen of the display terminal, and the main camera device will be controlled to turn on the lighting.

[0057] The present application provides a security monitoring camera equipment monitoring system and monitoring method, which analyzes the camera images of each camera device to determine whether each camera device has an abnormality, thereby solving the limitations existing in the current feasibility analysis process of security monitoring equipment monitoring development. At the same time, the moving objects appearing in the camera device are analyzed to obtain the monitoring target, and the real-time position of the detection target is analyzed. The main control terminal also issues an early warning prompt to the camera device with abnormalities, and at the same time turns on the illuminator of the camera device corresponding to the monitoring area to which the monitoring target belongs, thereby ensuring that security personnel can quickly lock the monitoring target position.

[0058] The above contents are merely examples and explanations of the concept of the present application. The technical personnel in the relevant technical field may make various modifications or additions to the described specific embodiments or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined in this specification, they should all fall within the scope of protection of the present application.

Claims

1. A security monitoring camera equipment monitoring system, characterized in that: include: The camera data acquisition and analysis module is used to acquire each photographic image of each camera device, and transmit each camera image to the visual analysis module, and then output the clarity and occlusion area corresponding to each camera image of each camera device, and then analyze and obtain the clarity evaluation coefficient of each camera device, and determine whether each camera device has an abnormality; The moving object data acquisition and analysis module is used to obtain the human shape similarity and temperature of the moving object when the moving object enters the monitoring area of ​​a certain camera device, and then analyze and obtain the target similarity evaluation coefficient of the moving object, so as to determine whether the moving object is a monitoring target; The monitoring target analysis module is used to obtain the real-time position coordinates of the monitoring target when the moving object is the monitoring target, and obtain the coordinates of the center point of the monitoring area of ​​each camera device, and then analyze and obtain the distance evaluation coefficient of each camera device, so as to determine the main camera device of the monitoring target; The main control terminal is used to give an abnormal prompt when a certain camera device has an abnormality; project the monitoring screen of the main camera device of the monitored target on the largest screen of the display terminal, and control the main camera device to turn on the lighting device; The analysis results in the clarity evaluation coefficient of each camera device. The specific analysis process is as follows: The clarity and occlusion area corresponding to each camera image of each camera device are respectively denoted as Q ij and Z ij , where i represents the number corresponding to each camera device, i=1,2,...,n, n represents the total number of camera devices, and n is a natural integer greater than or equal to 1; j represents the number corresponding to each camera image, j=1,2,...,m, m represents the total number of camera images, and m is a natural integer greater than or equal to 1; According to the calculation formula Get the clarity evaluation coefficient β of the i-th camera device i , where e is a natural integer, Q′ is a reference value of the definition of the camera image in the database, Z′ is a reference value of the occlusion area of ​​the camera image in the database, σ1 and σ2 are weight factors corresponding to the definition of the camera image in the database and the occlusion area; The analysis results in a target similarity assessment coefficient of a moving object, and the specific analysis process is as follows: The humanoid similarity and temperature of the moving object are recorded as R and T respectively, and substituted into the calculation formula The target similarity evaluation coefficient λ of the moving object is obtained, where e is represented by a natural integer, R′ is represented by a reference value of the humanoid similarity of the moving object in the database, a is represented by an influence value of the temperature of the moving object in the database, T′ is represented by a reference value of the temperature of the moving object in the database, ΔT is represented by an allowable floating value of the temperature of the moving object in the database, ω1 and ω2 are represented by weight factors corresponding to the humanoid similarity and the temperature of the moving object in the database.

2. A security monitoring camera equipment monitoring system according to claim 1, characterized in that: The specific process of judging whether each camera device is abnormal is as follows: The clarity assessment coefficient of each camera device is compared with the clarity assessment coefficient threshold in the database. When the clarity assessment coefficient of a camera device is greater than or equal to the clarity assessment coefficient threshold in the database, it is determined that the camera device has an abnormality. Otherwise, it is determined that the camera device has no abnormality. In this way, it is determined whether each camera device has an abnormality.

3. A security monitoring camera equipment monitoring system according to claim 1, characterized in that: The specific process of judging whether a moving object is a monitoring target is as follows: The target similarity evaluation coefficient of the moving object is compared with the target similarity evaluation coefficient threshold in the database. When the target similarity evaluation coefficient of the moving object is greater than or equal to the target similarity evaluation coefficient threshold in the database, the moving object is judged not to be a monitoring target, otherwise it is judged to be a monitoring target.

4. A security monitoring camera equipment monitoring system according to claim 1, characterized in that: The analysis results in the distance evaluation coefficient of each camera device. The specific analysis process is as follows: The real-time position coordinates of the monitored target are marked as (x′, y′), and the center coordinates of the monitoring area of ​​each camera device are marked as (x i ,y i ), substitute into the calculation formula Obtain the distance evaluation coefficient α of the i-th camera device i , where S represents the reference value of the camera device distance in the database.

5. A security monitoring camera equipment monitoring system according to claim 4, characterized in that: The main camera device of the monitoring target is determined, and the specific determination process is as follows: The distance evaluation coefficients of the camera devices are arranged from small to large, and the camera device corresponding to the smallest camera device distance evaluation coefficient is used as the main camera device of the monitoring target.

6. A security monitoring camera equipment monitoring system according to claim 1, characterized in that: It also includes a database for storing reference values ​​of the clarity of the camera image, reference values ​​of the occlusion area, weight factors corresponding to the clarity and weight factors corresponding to the occlusion area, storing clarity evaluation coefficient thresholds, storing reference values ​​of the human figure similarity of moving objects, temperature influence values, reference values ​​of temperature, allowable floating values ​​of temperature, weight factors corresponding to the human figure similarity and weight factors corresponding to the temperature, storing target similarity evaluation coefficient thresholds, and storing reference values ​​of the camera device distance.

7. A security monitoring camera device monitoring method applied to the security monitoring camera device monitoring system according to any one of claims 1 to 6, characterized in that: include: Step 1: Acquisition and analysis of camera data: Acquire each photographic image of each camera device, and transmit each camera image to the visual analysis module, and then output the clarity and occlusion area corresponding to each camera image of each camera device, and then analyze and obtain the clarity evaluation coefficient of each camera device, and determine whether each camera device has any abnormality; Step 2: Mobile object data acquisition and analysis: When a mobile object enters the monitoring area of ​​a camera device, the human shape similarity and temperature of the mobile object are acquired, and then the target similarity evaluation coefficient of the mobile object is analyzed to determine whether the mobile object is a monitoring target; Step 3: Monitoring target analysis: When a moving object is a monitoring target, obtain the real-time position coordinates of the monitoring target and the center point coordinates of the monitoring area of ​​each camera device, and then analyze and obtain the distance evaluation coefficient of each camera device, so as to determine the main camera device of the monitoring target; Main control terminal: When a camera device has an abnormality, an abnormal prompt will be given; the monitoring screen of the main camera device of the monitored target will be projected on the largest screen of the display terminal, and the main camera device will be controlled to turn on the lighting.

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