Camera equipment control method and device, electronic equipment and storage medium

Abstract

The embodiment of the invention provides a camera equipment control method and device, electronic equipment and a storage medium, the method is applied to a processor of a deployment and control system, the deployment and control system further comprises a plurality of first camera equipment and at least one second camera equipment, the first camera equipment is fixed camera equipment, and the second camera equipment is fixed camera equipment. The second camera device is a movable camera device. The method comprises the following steps: acquiring a plurality of first images obtained by respectively shooting a plurality of first areas by a plurality of first camera devices; if the first face image exists in the target first image in the plurality of first images, determining a second area according to the first face image and the target first image; and controlling second camera equipment to shoot the second area to obtain a second image. By implementing the method provided by the invention, the deployment cost of the camera equipment in the deployment and control system can be reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of power equipment, and in particular to a control method and device for a camera device, an electronic device and a storage medium. Background Art

[0002] In operations in power, construction, factories and other scenarios, the control system needs to deploy a large number of high-definition cameras in the site to collect target images of on-site personnel and verify the identities of the workers in the site. However, since the workers will not deliberately pose for photos due to the placement of the camera, the control system in the existing technology usually uses complex facial recognition algorithms in conjunction with a large number of high-resolution cameras for identity recognition, which leads to the problem of high deployment costs of camera equipment in the control system. Summary of the invention

[0003] In response to the above problems, the example of the present application provides a control method, device, electronic device and storage medium for a camera device, which is conducive to reducing the deployment cost of the camera device in the control system.

[0004] To achieve the above-mentioned objectives, in a first aspect, an embodiment of the present application provides a control method for a camera device, which is applied to a processor of a control system, wherein the control system also includes multiple first camera devices and at least one second camera device, wherein the first camera device is a fixed camera device, and the second camera device is a movable camera device, and the method includes: acquiring multiple first images obtained by respectively photographing multiple first areas by the multiple first camera devices; if a first facial image exists in a target first image among the multiple first images, determining a second area based on the first facial image and the target first image; and controlling the second camera device to photograph the second area to obtain a second image.

[0005] It can be seen that in the embodiment of the present application, multiple first images are obtained by shooting multiple first areas through multiple first camera devices. When there is a first facial image in the target first image among the multiple first images, the processor determines the second area according to the first facial image and the target first image, and then controls the second camera device to shoot the second area to obtain a clearer and more accurate second image, which can be used for subsequent identity recognition and other operations, so that the control system does not need to deploy a large number of high-cost second camera devices, reducing the deployment cost of the camera devices in the control system.

[0006] In combination with the first aspect, in a possible embodiment, determining the second area based on the first facial image and the target first image includes: determining first position data of the first facial image in the target first image; determining first three-dimensional coordinates of the first facial image in the controlled area based on the first position data, wherein the controlled area covers multiple first areas; determining the second area based on the first three-dimensional coordinates, the second area including the first three-dimensional coordinates.

[0007] In combination with the first aspect, in a possible embodiment, the method also includes: obtaining a third image of the first area corresponding to the first target camera device after a first preset time of obtaining the target first image, wherein the first target camera device is the first camera device corresponding to the target first image; if the third image includes the first facial image, determining the second position data of the first facial image in the third image; if the difference between the first position data and the second position data is greater than the preset difference, before determining the second area based on the first three-dimensional coordinates as the center, the method also includes: determining the moving direction and moving speed of the first facial image based on the first position data and the second position data; and correcting the first three-dimensional coordinates based on the moving direction and moving speed of the first facial image.

[0008] It can be seen that in the embodiment of the present application, the first three-dimensional coordinates are corrected according to the moving direction and the moving speed, which solves the problem that when the target person corresponding to the first facial image is in a moving state, the second image cannot be obtained in the second area determined according to the first three-dimensional coordinates.

[0009] In combination with the first aspect, in a possible embodiment, if the third image does not include the first facial image, the method further includes: obtaining a fourth image obtained by photographing the corresponding first area by a second target camera device, wherein the fourth image includes the first facial image, and the second target camera device is a first camera device adjacent to the first target camera device; determining third position data of the first facial image in the fourth image; if the difference between the first position data and the second position data is greater than a preset difference, before determining the second area based on the first three-dimensional coordinates as the center, the method further includes: determining a moving direction and a moving speed of the first facial image based on the first position data and the third position data; and correcting the first three-dimensional coordinates based on the moving direction and the moving speed of the first facial image.

[0010] It can be seen that in the embodiment of the present application, if the third image does not include the first facial image, the fourth image taken by the second target camera device adjacent to the first target camera device is directly acquired, so as to quickly acquire the specific position of the target person corresponding to the first facial image after the first preset time, and there is no need for the processor to re-acquire all the images taken by the first camera device, thereby improving the processing efficiency of the processor.

[0011] In combination with the first aspect, in a possible embodiment, the method also includes: acquiring at least one second facial image based on the second image; determining a target facial image from the at least one second facial image, the target facial image being the second facial image with the smallest offset from the standard facial image among the at least one second facial image; acquiring at least one preset facial image; respectively calculating the similarity between the target facial image and the at least one preset facial image; if the similarity between the target facial image and any one of the preset facial images is not less than a first preset threshold, determining that a first identity recognition result of the target facial image is normal; if the similarity between the target facial image and any one of the preset facial images is less than the first preset threshold, determining that the first identity recognition result of the target facial image is abnormal.

[0012] It can be seen that in the embodiment of the present application, by obtaining the second facial image with the smallest offset from the second image, and then performing identity recognition based on the target facial image and the preset facial image, the accuracy of the identity recognition result is improved.

[0013] In combination with the first aspect, in a possible embodiment, the control system also includes multiple third camera devices, which are movable camera devices, and respectively calculate the similarity between the target facial image and at least one preset facial image, including: obtaining multiple third facial images of the target person corresponding to the target facial image obtained by photographing the target facial image with multiple third camera devices, and the third facial image is obtained by photographing the target facial image simultaneously with the second camera device photographing the target facial image; determining the second three-dimensional coordinates of each of the multiple feature points of the target facial image according to the target facial image and the multiple third facial images; calculating at least one first distance according to the second three-dimensional coordinates of each of the multiple feature points of the target facial image, and the first distance is a Euclidean distance calculated according to the second three-dimensional coordinates of any two feature points; obtaining at least one second distance of each preset facial image, and the first distance corresponds to the second distance one by one; and respectively calculating the similarity between the target facial image and at least one preset facial image according to at least one second distance of each preset facial image and at least one first preset distance.

[0014] It can be seen that in the embodiment of the present application, the second three-dimensional coordinates of each of the multiple feature points of the target facial image are calculated by using multiple third facial images and the target facial image, and then the similarity between the target facial image and at least one preset facial image can be calculated on a three-dimensional level, thereby improving the accuracy of the identity recognition result determined based on the similarity between the target facial image and at least one preset facial image.

[0015] In combination with the first aspect, in a possible embodiment, if the similarity between the target facial image and any preset facial image is less than a first preset threshold, and the similarity between the target facial image and the target preset facial image is greater than a second preset threshold, and the second preset threshold is less than the first preset threshold, the method also includes: determining a first body feature value of the target person corresponding to the target facial image based on the first image; obtaining a second body feature value corresponding to the target preset facial image; generating a similarity compensation value based on the first body feature and the second body feature; and modifying the similarity between the target facial image and the target preset facial image based on the similarity compensation value.

[0016] It can be seen that in the embodiment of the present application, the similarity between the target facial image and the target preset facial image is modified by the similarity compensation value. When the identity recognition result of the target facial image is in doubt, the similarity between the target facial image and the target preset facial image is corrected by the first body feature and the second body feature, thereby improving the accuracy of the identity recognition result determined according to the similarity between the target facial image and at least one preset facial image.

[0017] In a second aspect, an embodiment of the present application provides a control device for a camera device, which is used to execute a control method for a camera device, and belongs to a control system. The control system also includes a plurality of first camera devices and at least one second camera device. The first camera device is a fixed camera device, and the second camera device is a movable camera device. The device includes:

[0018] An acquisition unit: used for acquiring a plurality of first images obtained by respectively photographing a plurality of first areas by a plurality of first camera devices;

[0019] A determining unit: configured to determine a second area according to the first facial image and the target first image if the first facial image exists in the target first image among the plurality of first images;

[0020] Control unit: used for controlling the second camera device to capture the second area to obtain a second image.

[0021] In a third aspect, an embodiment of the present application provides an electronic device comprising a processor, a memory, a communication interface, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor, and one or more instructions are suitable for being loaded by the processor and executing part or all of the method of the first aspect.

[0022] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium storing a computer program for electronic data exchange, wherein the computer program enables a computer to execute part or all of the method of the first aspect.

[0023] In a fifth aspect, the present application provides a computer program product. When a computer reads and executes the computer program product, the computer executes part or all of the method of the first aspect.

[0024] It can be understood that the beneficial effects of the embodiments described in the second to fifth aspects can refer to the beneficial effects of the method described in the first aspect, and will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] 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.

[0026] Figure 1 A schematic diagram of an application scenario of a control method for a camera device provided in an embodiment of the present application;

[0027] Figure 2 A schematic diagram of the structure of a control ball provided in an embodiment of the present application;

[0028] Figure 3 A flowchart of a control method for a camera device provided in an embodiment of the present application;

[0029] Figure 4 A schematic diagram of a process for determining a second area provided in an embodiment of the present application;

[0030] Figure 5 A flowchart of another method for controlling a camera device provided in an embodiment of the present application;

[0031] Figure 6 A schematic diagram of comparing a standard facial image and a second facial image provided in an embodiment of the present application;

[0032] Figure 7 A schematic diagram of a work ticket provided in an embodiment of the present application;

[0033] Figure 8 A flowchart of a control method for a camera device provided in an embodiment of the present application;

[0034] Fig. 9 A schematic diagram of the structure of a processor of a control system provided in an embodiment of the present application;

[0035] Fig.10 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0036] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings 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.

[0037] The terms "first", "second", etc. in the specification and claims of this application and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally includes steps or units that are not listed, or optionally includes other steps or units inherent to these processes, methods, products or devices.

[0038] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0039] The embodiments of the present application are described below in conjunction with the accompanying drawings.

[0040] See also Figure 1 , Figure 1 A schematic diagram of an application scenario of a control method for a camera device provided in an embodiment of the present application, wherein the application scenario 100 includes a control system 101, and the control system 101 includes a processor 1011, a plurality of first camera devices 1012, and a second camera device 1013. For ease of explanation, only three first camera devices 1012 are used as an example. In actual application scenarios, there may be more or fewer first camera devices 1012.

[0041] The control system here is specifically Figure 1The system shown includes a plurality of independent devices, wherein the processor 1011 is specifically a central processing unit in a local server or a microcontroller unit in a small device, and is used to control a first camera device 1012 and a second camera device 1013, and obtain images captured by the first camera device 1012 and the second camera device 1013. The first camera device 1012 is fixed at a designated position and captures a fixed area in the application scene 100, and the second camera device 1013 can change the capture area through technologies such as a pan / tilt head, and has better performance than the first camera device, but also requires more deployment costs.

[0042] In the embodiment of the present application, the processor 1011 obtains multiple first images obtained by capturing multiple first areas by multiple first camera devices 1012. The first camera devices 1012 are fixed at different positions to capture different first areas, and each first area may have partial overlap. The first image is specifically a single picture, multiple pictures, or a video.

[0043] If the first facial image exists in the target first image among the multiple first images, the processor 1011 determines the second area according to the first facial image and the target first image. The existence of the first facial image in the target first image here means that the processor 1011 recognizes the facial image of a person from a first image, and at this time, the processor 1011 determines the second area according to the first facial image in the target first image. The second area here is an area including the first facial image.

[0044] The processor 1011 controls the second camera to capture the second area to obtain a second image, thereby obtaining a clearer facial image of the target person corresponding to the first facial image to facilitate subsequent identity recognition.

[0045] Optionally, the control system 101 is specifically a control ball, see Figure 2 , Figure 2 The schematic diagram of the structure of a control ball provided in an embodiment of the present application, wherein a micro control unit 201 is built in the control ball 200, six fixed first camera devices 202 are arranged at the lower side of the control ball, and a pan head 203 is arranged at the upper side of the control ball, and the pan head 203 is used to move the second camera device 204, so that the second camera device 204 can change the shooting angle according to the instruction of the micro control unit 201. The micro control unit 201 is also used to control the first camera device 202.

[0046] It can be seen that in the embodiment of the present application, multiple first images are obtained by shooting multiple first areas through multiple first camera devices. When there is a first facial image in the target first image among the multiple first images, the processor determines the second area according to the first facial image and the target first image, and then controls the second camera device to shoot the second area to obtain a clearer and more accurate second image, which can be used for subsequent identity recognition and other operations, so that the control system does not need to deploy a large number of high-cost second camera devices, reducing the deployment cost of the camera devices in the control system.

[0047] See also Figure 3 , Figure 3 A flow chart of a control method for a camera device provided in an embodiment of the present application can be based on Figure 1 The application scenario shown is implemented as follows Figure 3 As shown, steps S301-S303 are included.

[0048] S301: The processor obtains a plurality of first images obtained by respectively photographing a plurality of first areas by a plurality of first camera devices.

[0049] Specifically, the first area here refers to multiple areas in the controlled area. The control system is used to observe the people in the controlled area and obtain their facial images, and then verify their identities based on their facial images to prevent unauthorized entry into the controlled area, thereby causing safety hazards and other problems.

[0050] The controlled areas here specifically include power operation areas, construction areas, residential areas, etc.

[0051] S302: If a first facial image exists in a target first image among the plurality of first images, the processor determines a second area according to the first facial image and the target first image.

[0052] Specifically, after acquiring the plurality of first images, the processor identifies the plurality of first images, and identifies whether the first facial image exists in the plurality of first images or whether the first facial image does not exist. The processor identifies the plurality of first images specifically through the Dlib algorithm, the OpenCV algorithm, or other deep learning models.

[0053] If there is a first facial image in any of the multiple first images, it can be known that the corresponding first camera device has captured the face of the target person corresponding to the first facial image. Since the first camera device is a fixed camera device with a low resolution, the processor can only determine that the target person exists in the first area based on the first image, and cannot identify the identity of the target person based on the first facial image. Therefore, the second area is determined based on the first facial image and the target first image. Then, a second camera device with a higher lens resolution is used to capture the target person to obtain a clearer second image.

[0054] In a possible embodiment, determining a second area based on a first facial image and a target first image includes: determining first position data of the first facial image in the target first image; determining first three-dimensional coordinates of the first facial image in a controlled area based on the first position data, wherein the controlled area covers a plurality of first areas; and determining a second area based on the first three-dimensional coordinates, wherein the second area includes the first three-dimensional coordinates.

[0055] Specifically, in the embodiment of the present application, the second area is determined in the controlled area according to the first position data of the first facial image in the target first image.

[0056] First, determine the first position data of the first facial image in the target first image, where the first position data includes the image size, height, horizontal position and other data of the first facial image in the target first image. Then, the processor can determine the first three-dimensional coordinates of the first facial image in the control area based on the image size, height, horizontal position and other data of the first facial image in the target first image based on a conversion algorithm or a preset correspondence between the position data and the first three-dimensional coordinates, i.e., the coordinates of the first facial image in the coordinate system established with the control area. Then determine the second area based on the first three-dimensional coordinates, where the first three-dimensional coordinates are included.

[0057] Furthermore, the image size data here is used to determine the y-axis coordinate in the first three-dimensional coordinate, the height data here is used to determine the z-axis coordinate in the first three-dimensional coordinate, and the horizontal position data here is used to determine the x-axis coordinate in the first three-dimensional coordinate.

[0058] For example, see Figure 4 , Figure 4 A schematic diagram of a process for determining a second region provided in an embodiment of the present application. It can be seen that the first three-dimensional coordinates here are determined based on the first position data, and the first three-dimensional coordinates are specifically the center point of the first facial image. The processor generates a second region based on the first three-dimensional coordinates. It can be seen that Figure 4 The second area shown in is generated with the first three-dimensional coordinates as the center.

[0059] In a possible embodiment, the method further includes: obtaining a third image of the first area corresponding to the target by shooting a first target camera device after a first preset time of obtaining the target first image, wherein the first target camera device is the first camera device corresponding to the target first image; if the third image includes the first facial image, determining the second position data of the first facial image in the third image; if the difference between the first position data and the second position data is greater than the preset difference, before determining the second area based on the first three-dimensional coordinates as the center, the method further includes: determining the moving direction and moving speed of the first facial image based on the first position data and the second position data; and correcting the first three-dimensional coordinates based on the moving direction and moving speed of the first facial image.

[0060] Specifically, if the first facial image may be taken while the corresponding target person is walking or working in the control area, after the processor determines the second area, the target person may not exist in the second area. This is because the processor needs to perform calculations for a period of time to determine the second area based on the first three-dimensional coordinates, and during this period of time, the target person needs to keep moving and working, which may cause the processor to move out of the second area after determining the second area. Therefore, in the embodiment of the present application, it is also necessary to determine that the first facial image may be taken while the corresponding target person is walking or working in the control area.

[0061] The processor first obtains a third image obtained by capturing the first area corresponding to the first target camera device after a first preset time after obtaining the first target image, and then determines the second position data of the first facial image in the third image, where the second position data specifically includes image size, height, horizontal position and other data corresponding to the first position data. The processor calculates the difference between the first position data and the second position data, where the difference is specifically obtained based on the difference of specific data such as image size difference, height difference, horizontal position difference and the like in the two position data.

[0062] If the difference between the first position data and the second position data is not greater than the preset difference, it proves that the target person has not moved or has moved very little within the first preset time, so the second area can be directly determined according to the first three-dimensional coordinates.

[0063] If the difference between the first position data and the second position data is greater than the preset difference, it proves that the target person has moved a large amount within the first preset time. At this time, the moving direction and moving speed of the first facial image are determined according to the first position data and the second position data; the first three-dimensional coordinates are corrected according to the moving direction and moving speed of the first facial image, so as to ensure that the target person exists in the second area finally determined. Here, correcting the first three-dimensional coordinates according to the moving direction and moving speed specifically includes determining the moving range of the target person on the three axes (x, y, z) within the second preset time range according to the moving direction and moving speed. Here, the sum of the first preset time and the second preset time is determined by the average calculation time required for the processor to determine the second area according to the first three-dimensional coordinates. The sum of the first preset time and the second preset time can be 500ms, 1000ms, etc.

[0064] It can be seen that in the embodiment of the present application, the first three-dimensional coordinates are corrected according to the moving direction and the moving speed, which solves the problem that when the target person corresponding to the first facial image is in a moving state, the second image cannot be obtained in the second area determined according to the first three-dimensional coordinates.

[0065] In a possible embodiment, if the third image does not include the first facial image, the method further includes: obtaining a fourth image obtained by capturing the corresponding first area with a second target camera device, wherein the fourth image includes the first facial image, and the second target camera device is a first camera device adjacent to the first target camera device; determining third position data of the first facial image in the fourth image; if the difference between the first position data and the second position data is greater than a preset difference, before determining the second area based on the first three-dimensional coordinates as the center, the method further includes: determining a moving direction and a moving speed of the first facial image based on the first position data and the third position data; and correcting the first three-dimensional coordinates based on the moving direction and the moving speed of the first facial image.

[0066] Specifically, in an embodiment of the present application, if the third image does not include the first facial image, it proves that the target person has walked out of the first area photographed by the first target camera device after the first preset time. At this time, the fourth image of the first area corresponding to the first area photographed by the second target camera device is obtained. The second target camera device is the first camera device adjacent to the first target camera device, and the first area photographed by the second target camera device is also adjacent to the first area photographed by the first target camera device.

[0067] That is to say, when the third image does not include the first facial image, the processor directly obtains the corresponding image from the first camera device adjacent to the first target camera device, and then searches for the fourth image including the facial image of the target person, and then performs the subsequent steps of determining whether the difference between the first position data and the second position data is greater than the preset difference, correcting the first three-dimensional coordinates, etc. For a detailed description of the steps of determining whether the difference between the first position data and the second position data is greater than the preset difference, correcting the first three-dimensional coordinates, etc., please refer to the aforementioned related description and will not be repeated here.

[0068] It can be seen that in the embodiment of the present application, if the third image does not include the first facial image, the fourth image taken by the second target camera device adjacent to the first target camera device is directly acquired, so as to quickly acquire the specific position of the target person corresponding to the first facial image after the first preset time, and there is no need for the processor to re-acquire all the images taken by the first camera device, thereby improving the processing efficiency of the processor.

[0069] S303: The processor controls the second camera device to photograph the second area to obtain a second image.

[0070] Specifically, after controlling the second camera device to shoot the second area, a second facial image that is clearer than the first facial image can be obtained from the second image. The processor can then perform operations such as identity recognition on the target person based on the second facial image.

[0071] The above-mentioned application embodiment provides a camera device control method, wherein the processor controls the second camera device to obtain a second image, and based on this, the second image is used to identify the corresponding target person. The embodiment of the present application also provides another camera device control method, see Figure 5 , Figure 5 A flowchart of another method for controlling a camera device provided in an embodiment of the present application includes steps S501-S504:

[0072] S501: The processor obtains a plurality of first images obtained by respectively photographing a plurality of first areas by a plurality of first camera devices.

[0073] S502: If a first facial image exists in a target first image among the plurality of first images, the processor determines a second area according to the first facial image and the target first image.

[0074] S503: The processor controls the second camera device to photograph the second area to obtain a second image.

[0075] For the detailed description of steps S501-S503, please refer to the relevant description of steps S301-S302, which will not be repeated here.

[0076] S504: The processor determines a first identity recognition result according to the second image.

[0077] The first identity recognition result here is normal or abnormal. If the first identity recognition result is normal, the target person is allowed to appear in the controlled area. If the first identity recognition result is abnormal, the target person is not allowed to appear in the controlled area. If the first identity recognition result is abnormal, a first alarm message is generated. The first alarm message is used to notify the management personnel that a person who is not allowed to appear has appeared in the controlled area.

[0078] In a possible embodiment, determining a first identity recognition result based on a second image includes: acquiring at least one second facial image based on the second image; determining a target facial image from the at least one second facial image, the target facial image being the second facial image with the smallest offset from the standard facial image among the at least one second facial image; acquiring at least one preset facial image; respectively calculating the similarity between the target facial image and the at least one preset facial image; determining that the first identity recognition result of the target facial image is normal if the similarity between the target facial image and any one of the preset facial images is not less than a first preset threshold; determining that the first identity recognition result of the target facial image is abnormal if the similarity between the target facial image and any one of the preset facial images is less than the first preset threshold.

[0079] Specifically, the second image here includes multiple pictures of the target person taken by the second camera device. The processor determines the target facial image from the second image, and the target facial image is the one with the smallest offset from the standard facial image among the multiple pictures included in the second image. The standard facial image here is an image obtained by the target person photographing the camera device.

[0080] For example, see Figure 6 , Figure 6 A schematic diagram of a comparison between a standard facial image and a second facial image provided in an embodiment of the present application, wherein the facial image on the left is the standard facial image, and the image on the right is a second facial image, and the offset between the second facial image and the standard facial image is calculated based on the first distance and the second distance shown in the figure, where the first distance and the second distance are specifically the distance from the facial center axis to the facial edge line in the standard facial image and the second facial image.

[0081] After determining the target facial image, at least one preset facial image is obtained, wherein the preset facial image is a facial image of a person who can enter the control area and is collected in advance.

[0082] For example, the preset facial image is stored in a work ticket, which is a document used to record and manage specific work tasks, usually used in industries such as industry, construction, and electricity. It lists in detail information such as work content, personnel, required equipment, safety measures, and working hours, aiming to ensure that the work is carried out safely and orderly. It is also used here to record the preset facial image of the personnel. For example, please refer to Figure 7 , Figure 7 A schematic diagram of a work ticket provided in an embodiment of the present application, which records working hours, work content, safety measures to be taken, and preset facial images of multiple staff members, and the processor can obtain the preset facial images of the corresponding staff members by querying the work list.

[0083] After obtaining at least one preset facial image, the processor calculates the similarity between the target facial image and at least one preset facial image respectively; if the similarity between the target facial image and any one of the preset facial images is not less than a first preset threshold, the first identity recognition result of the target facial image is determined to be normal; if the similarity between the target facial image and any one of the preset facial images is less than the first preset threshold, the first identity recognition result of the target facial image is determined to be abnormal.

[0084] It can be seen that in the embodiment of the present application, by obtaining the second facial image with the smallest offset from the second image, and then performing identity recognition based on the target facial image and the preset facial image, the accuracy of the identity recognition result is improved.

[0085] In a possible embodiment, the control system further includes a plurality of third camera devices, which are movable camera devices, and respectively calculate the similarity between the target facial image and at least one preset facial image, including: obtaining a plurality of third facial images of the target person corresponding to the target facial image captured by the plurality of third camera devices, the third facial image being captured simultaneously when the second camera device captures the target facial image; determining the second three-dimensional coordinates of each of the plurality of feature points of the target facial image according to the target facial image and the plurality of third facial images; calculating at least one first distance according to the coordinates of the plurality of feature points of the target facial image, the first distance being the Euclidean distance calculated according to the second three-dimensional coordinates of any two feature points; obtaining at least one second distance of each preset facial image, the first distance corresponding to the second distance one-to-one; respectively calculating the similarity between the target facial image and at least one preset facial image according to at least one second distance of each preset facial image and at least one first preset distance.

[0086] Specifically, in the embodiment of the present application, the control system further includes a plurality of third camera devices, where the third camera devices and the second camera devices are movable camera devices of the same type. The third camera device is used to photograph the target person from different angles when the second device photographs the target person to obtain images at different angles from the second image. For a specific description of the third camera device photographing the target person, please refer to the relevant description of the second image obtained by the second camera device photographing the second area, which will not be repeated here.

[0087] The multiple third facial images here are taken by the corresponding third camera device at the same time when the second camera device takes the target facial image, and then the processor can obtain the second three-dimensional coordinates of each feature point in the multiple feature points of the target facial image according to the multiple facial images of the target person at different angles at the same time. The feature points here specifically include eye feature points, nose feature points, mouth feature points, etc.

[0088] At least one first distance can be calculated based on the coordinates of the multiple feature points, and the processor can calculate the similarity between the target facial image and at least one preset facial image based on the at least one first distance of the target facial image and at least one second distance of each preset facial image. If the first distance of the target facial image is the distance from the eye feature point to the mouth feature point in the target facial image, the corresponding second distance is the distance from the eye feature point to the mouth feature point in any one of the preset facial images.

[0089] Exemplarily, the target facial image includes a first feature point and a second feature point, wherein the second three-dimensional coordinates of the first feature point are (x1, y1, z1), and the second three-dimensional coordinates of the second feature point are (x2, y2, z2). The first distance between the first feature point and the second feature point satisfies the following formula (1):

[0090]

[0091] Wherein D is a first distance between the first feature point and the second feature point.

[0092] It can be seen that in the embodiment of the present application, the second three-dimensional coordinates of each of the multiple feature points of the target facial image are calculated by using multiple third facial images and the target facial image, and then the similarity between the target facial image and at least one preset facial image can be calculated on a three-dimensional level, thereby improving the accuracy of the identity recognition result determined based on the similarity between the target facial image and at least one preset facial image.

[0093] In a possible embodiment, if the similarity between the target facial image and any preset facial image is less than a first preset threshold, and the similarity between the target facial image and the target preset facial image is greater than a second preset threshold, and the second preset threshold is less than the first preset threshold, the method also includes: determining a first body feature value of a target person corresponding to the target facial image based on the first image; obtaining a second body feature value corresponding to the target preset facial image; generating a similarity compensation value based on the first body feature and the second body feature; and modifying the similarity between the target facial image and the target preset facial image based on the similarity compensation value.

[0094] Specifically, if the similarity between the target facial image and any preset facial image is less than a first preset threshold, and the similarity between the target facial image and the target preset facial image is greater than a second preset threshold, it specifically means that the similarity between the target facial image and the target preset facial image is high, but it cannot be completely determined that the target person corresponding to the target facial image is the person corresponding to the target preset facial image.

[0095] At this time, the first body feature value of the target person corresponding to the target facial image is determined according to the target first image. Since the first image is taken by the first camera device, and the first camera device is used to shoot a first area of ​​a larger area, the body shape data, height data and other data of the target person can be determined according to the first image to calculate the first body feature value of the target person. Then, the second body feature value corresponding to the target preset facial image is obtained, and a similarity compensation value is generated according to the first body feature and the second body feature. The smaller the difference between the first body feature value and the second body feature value, the higher the similarity compensation value. Then, the similarity between the target facial image and the target preset facial image is corrected according to the similarity compensation value, thereby affecting the final first identity recognition result.

[0096] It can be seen that in the embodiment of the present application, the similarity between the target facial image and the target preset facial image is modified by the similarity compensation value. When the identity recognition result of the target facial image is in doubt, the similarity between the target facial image and the target preset facial image is corrected by the first body feature and the second body feature, thereby improving the accuracy of the identity recognition result determined according to the similarity between the target facial image and at least one preset facial image.

[0097] The above application embodiment describes a method for identifying a target person based on local computing. Based on this, the present application embodiment also provides another method for controlling a camera device including a server, where the server is connected to a control system. Figure 8 , Figure 8 Another method for controlling a camera device provided in an embodiment of the present application includes steps S801-S806:

[0098] S801: The processor obtains a plurality of first images obtained by respectively photographing a plurality of first areas by a plurality of first camera devices.

[0099] S802: If a first facial image exists in a target first image among the plurality of first images, the processor determines a second area according to the first facial image and the target first image.

[0100] S803: The processor controls the second camera device to photograph the second area to obtain a second image.

[0101] S804: The processor determines a first identity recognition result according to the second image.

[0102] For the detailed description of steps S801-S804, please refer to the relevant description of steps S501-S504, which will not be repeated here.

[0103] S805: The processor generates a third image according to the second image, and sends the third image to the server.

[0104] Specifically, the third image here is video data extracted from the second image, and the video data includes target image data. Since the server has a computing power advantage over the processor, the server can use a model and algorithm that requires more computing power when identifying the target person through the third image, so the server can obtain a more accurate identification result.

[0105] S806: The processor receives the second identity recognition result sent by the server, and generates a third identity recognition result according to the first identity recognition result and the second identity recognition result.

[0106] Specifically, if the first identity recognition result is the same as the second identity recognition result, the third identity recognition result, the first identity recognition result, and the second identity recognition result are all the same result. If the first identity recognition result and the second identity recognition result are different, a second alarm message is generated, and the second alarm message is used to notify the management personnel to determine the correct recognition result from the first identity recognition result and the second identity recognition result, so as to determine the correct recognition result as the third identity recognition result.

[0107] It can be seen that in the embodiment of the present application, the final third identity identification result is generated by the first identity identification result and the second identity identification result sent by the server, which further improves the accuracy of the identity identification result.

[0108] Optionally, determining the target facial image from the at least one second facial image includes: inputting the at least one second facial image into the first facial recognition model to obtain the target facial image output by the first facial recognition model; calculating the similarity between the target facial image and the at least one preset facial image includes: inputting the target facial image and the at least one preset facial image into the second facial recognition model to obtain the similarity between the at least one preset facial image output by the second facial recognition model. If the first identity recognition result and the second identity recognition result are different, and the second identity recognition result is a correct result, then obtaining the training data corresponding to the second identity recognition result; optimizing the first facial recognition model and the second facial recognition model in the control system according to the training data. Thereby improving the accuracy of identity recognition and demerit recording.

[0109] By implementing the method in the above application embodiment, it can be seen that the deployment cost is reduced by shooting images through multiple first camera devices and at least one second camera device. The problem that the second image cannot be obtained in the second area determined according to the first three-dimensional coordinates. The specific position of the target person corresponding to the first facial image after the first preset time is quickly obtained, thereby improving the processing efficiency of the processor. By improving the quality of the target facial image, calculating the second three-dimensional coordinates of each of the multiple feature points of the target facial image from multiple third facial images and the target facial image, and correcting the similarity between the target facial image and the target preset facial image by the first body feature and the second body feature, the accuracy of the identity recognition result is improved.

[0110] Based on the description of the above configuration method embodiment, the present application also provides a control device 900 of a camera device, which can be operated on Figure 1 A computer program (including program code) in the application scenario shown in FIG. Figure 1 The application scenario shown in the figure is executed Figure 3 , Figure 5 or Figure 8 See the method shown in Fig. 9 , Fig. 9 A schematic diagram of a control device for a camera device provided in an embodiment of the present application, the device comprising:

[0111] The acquisition unit 901 is used to acquire a plurality of first images obtained by respectively photographing a plurality of first areas by a plurality of first camera devices.

[0112] The determining unit 902 is configured to determine a second area according to the first facial image and the target first image if a first facial image exists in a target first image among the plurality of first images.

[0113] Control unit 903: used to control the second camera device to capture the second area to obtain a second image.

[0114] In a possible embodiment, in terms of determining the second area based on the first facial image and the target first image, the determination unit 902 is also specifically used to: determine the first position data of the first facial image in the target first image; determine the first three-dimensional coordinates of the first facial image in the controlled area based on the first position data, wherein the controlled area covers multiple first areas; determine the second area based on the first three-dimensional coordinates, and the second area includes the first three-dimensional coordinates.

[0115] In a possible embodiment, the acquisition unit 901 is further specifically used to: acquire a third image of the first area corresponding to the first target camera device after a first preset time of obtaining the target first image, wherein the first target camera device is the first camera device corresponding to the target first image; if the third image includes the first facial image, determine the second position data of the first facial image in the third image; if the difference between the first position data and the second position data is greater than the preset difference, before determining the second area based on the first three-dimensional coordinates as the center, the method also includes: determining the moving direction and moving speed of the first facial image based on the first position data and the second position data; and correcting the first three-dimensional coordinates based on the moving direction and moving speed of the first facial image.

[0116] In a possible embodiment, if the third image does not include the first facial image, the acquisition unit 901 is further specifically used to: acquire a fourth image obtained by photographing the corresponding first area with a second target camera device, wherein the fourth image includes the first facial image, and the second target camera device is a first camera device adjacent to the first target camera device; determine third position data of the first facial image in the fourth image; if the difference between the first position data and the second position data is greater than a preset difference, before determining the second area with the first three-dimensional coordinates as the center, the method also includes: determining a moving direction and a moving speed of the first facial image based on the first position data and the third position data; and correcting the first three-dimensional coordinates based on the moving direction and the moving speed of the first facial image.

[0117] In a possible embodiment, the acquisition unit 901 is further specifically used to: acquire at least one second facial image based on the second image; determine a target facial image from the at least one second facial image, the target facial image being the second facial image with the smallest offset from the standard facial image among the at least one second facial image; acquire at least one preset facial image; respectively calculate the similarity between the target facial image and the at least one preset facial image; if the similarity between the target facial image and any one of the preset facial images is not less than a first preset threshold, determine that the first identity recognition result of the target facial image is normal; if the similarity between the target facial image and any one of the preset facial images is less than the first preset threshold, determine that the first identity recognition result of the target facial image is abnormal.

[0118] In a possible embodiment, the control system further includes a plurality of third camera devices, which are movable camera devices. In terms of respectively calculating the similarity between the target facial image and at least one preset facial image, the acquisition unit 901 is further specifically used for: acquiring a plurality of third facial images of the target person corresponding to the target facial image captured by the plurality of third camera devices, wherein the third facial image is captured simultaneously when the second camera device captures the target facial image; determining the second three-dimensional coordinates of each of the plurality of feature points of the target facial image according to the target facial image and the plurality of third facial images; calculating at least one first distance according to the second three-dimensional coordinates of each of the plurality of feature points of the target facial image, wherein the first distance is a Euclidean distance calculated according to the second three-dimensional coordinates of any two feature points; acquiring at least one second distance of each preset facial image, wherein the first distance corresponds to the second distance one-to-one; and respectively calculating the similarity between the target facial image and at least one preset facial image according to at least one second distance of each preset facial image and at least one first preset distance.

[0119] In a possible embodiment, if the similarity between the target facial image and any preset facial image is less than a first preset threshold, and the similarity between the target facial image and the target preset facial image is greater than a second preset threshold, and the second preset threshold is less than the first preset threshold, the determination unit 902 is further specifically used to: determine the first body feature value of the target person corresponding to the target facial image according to the first image; obtain the second body feature value corresponding to the target preset facial image; generate a similarity compensation value according to the first body feature and the second body feature; and modify the similarity between the target facial image and the target preset facial image according to the similarity compensation value.

[0120] Based on the description of the above method embodiment and device embodiment, please refer to Fig.10 , Fig.10 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. Fig.10The electronic device 1000 shown (the electronic device 1000 may be a computer device, Figure 1 The control system 101 shown includes a memory 1001, a processor 1002, a communication interface 1003 and a bus 1004. The memory 1001, the processor 1002 and the communication interface 1003 are connected to each other through the bus 1004.

[0121] The memory 1001 may be a read-only memory (ROM), a static storage device, a dynamic storage device or a random access memory (RAM).

[0122] The memory 1001 can store programs. When the program stored in the memory 1001 is executed by the processor 1002, the processor 1002 and the communication interface 1003 are used to execute each step of the control method of the camera device of the embodiment of the present application.

[0123] The processor 1002 can adopt a general central processing unit (CPU), a microprocessor, an application specific integrated circuit (ASIC), a graphics processing unit (GPU) or one or more integrated circuits to execute relevant programs to implement the functions required to be performed by the units in the electronic device 1000 of the embodiment of the present application, or to execute the control method of the camera device of the method embodiment of the present application.

[0124] The processor 1002 may also be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the control method of the camera device of the present application may be completed by an integrated logic circuit of hardware or software instructions in the processor 1002. The above-mentioned processor 1002 may also be a general-purpose processor, a digital signal processor (Digital Signal Processing, DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (Field Programmable Gate Array, FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The methods, steps and logic block diagrams disclosed in the embodiments of the present application may be implemented or executed. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc. The steps of the method disclosed in the embodiments of the present application may be directly embodied as being executed by a hardware decoding processor, or may be executed by a combination of hardware and software modules in a decoding processor. The software module may be located in a mature storage medium in the art such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory or an electrically erasable programmable memory, a register, etc. The storage medium is located in the memory 1001, and the processor 1002 reads the information in the memory 1001, and combines its hardware to complete the functions required to be performed by the units included in the electronic device 1000 of the embodiment of the present application, or executes the control method of the camera device of the method embodiment of the present application.

[0125] The communication interface 1003 uses a transceiver device such as, but not limited to, a transceiver to implement communication between the electronic device 1000 and other devices or a communication network. For example, data can be acquired through the communication interface 1003 .

[0126] The bus 1004 may include a path for transmitting information between various components of the electronic device 1000 (eg, the memory 1001 , the processor 1002 , and the communication interface 1003 ).

[0127] It should be noted that although Fig.10 The electronic device 1000 shown only shows the memory 1001, the processor 1002, and the communication interface 1003. However, in the specific implementation process, those skilled in the art should understand that the electronic device 1000 also includes other devices necessary for normal operation. At the same time, according to specific needs, those skilled in the art should understand that the electronic device 1000 may also include hardware devices for implementing other additional functions. In addition, those skilled in the art should understand that the electronic device 1000 may also only include the devices necessary for implementing the embodiments of the present application, and does not necessarily include Fig.10 All devices shown in .

[0128] An embodiment of the present application further provides a chip, which includes a processor and a data interface. The processor reads instructions stored in a memory through the data interface to implement the control method of the camera device.

[0129] Optionally, as an implementation method, the chip may further include a memory, in which instructions are stored, and the processor is used to execute the instructions stored in the memory. When the instructions are executed, the processor is used to execute the control method of the camera device.

[0130] An embodiment of the present application also provides a computer-readable storage medium, which stores instructions. When the computer-readable storage medium is executed on a computer or a processor, the computer or the processor executes one or more steps in any of the above methods.

[0131] The embodiment of the present application further provides a computer program product including instructions. When the computer program product is executed on a computer or a processor, the computer or the processor executes one or more steps in any of the above methods.

[0132] Those skilled in the art will appreciate that the functions described in conjunction with the various illustrative logic blocks, modules, and algorithm steps disclosed herein can be implemented in hardware, software, firmware, or any combination thereof. If implemented in software, the functions described in the various illustrative logic blocks, modules, and steps can be stored or transmitted as one or more instructions or codes on a computer-readable medium and executed by a hardware-based processing unit. Computer-readable media may include computer-readable storage media, which corresponds to tangible media, such as data storage media, or includes any media (e.g., based on a communication protocol) that facilitates the transfer of a computer program from one place to another. In this manner, computer-readable media may generally correspond to (1) non-temporary tangible computer-readable storage media, or (2) communication media, such as signals or carrier waves. Data storage media may be any available media that can be accessed by one or more computers or one or more processors to retrieve instructions, codes, and / or data structures for implementing the techniques described in this application. A computer program product may include computer-readable media.

[0133] As an example and not limitation, such computer-readable storage media may include RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage, flash memory, or any other medium that can be used to store the desired program code in the form of instructions or data structures and can be accessed by a computer. Also, any connection is properly referred to as a computer-readable medium. For example, if instructions are transmitted from a website, server or other remote source using a coaxial cable, fiber optic cable, twisted pair, digital subscriber line (DSL), or wireless technologies such as infrared, radio and microwave, then the coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio and microwave are included in the definition of media. However, it should be understood that the computer-readable storage media and data storage media do not include connections, carrier waves, signals or other temporary media, but are actually directed to non-temporary tangible storage media. As used herein, disks and optical disks include compact disks (CDs), laser optical disks, optical optical disks, digital versatile disks (DVDs), and Blu-ray disks, where disks typically reproduce data magnetically, while optical disks reproduce data optically using lasers. Combinations of the above should also be included within the scope of computer-readable media.

[0134] Instructions may be executed by one or more processors, such as one or more digital signal processors (DSPs), general purpose microprocessors, application specific integrated circuits (ASICs), field programmable logic arrays (FPGAs), or other equivalent integrated or discrete logic circuits. Thus, the term "processor" as used herein may refer to any of the aforementioned structures or any other structures suitable for implementing the techniques described herein. Additionally, in some aspects, the functions described by the various illustrative logic blocks, modules, and steps described herein may be provided within dedicated hardware and / or software modules configured for encoding and decoding, or incorporated in a combined codec. Moreover, the techniques may be fully implemented in one or more circuits or logic elements.

[0135] The techniques of the present application may be implemented in a variety of devices or apparatuses, including a wireless handset, an integrated circuit (IC), or a set of ICs (e.g., a chipset). Various components, modules, or units are described in this application to emphasize functional aspects of devices for performing the disclosed techniques, but do not necessarily need to be implemented by different hardware units. In fact, as described above, the various units may be combined in an encoded hardware unit in conjunction with appropriate software and / or firmware, or provided by interoperating hardware units (including one or more processors as described above).

[0136] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the specific descriptions of the corresponding steps in the aforementioned method embodiments, and will not be repeated here.

[0137] It should be understood that in the description of the present application, unless otherwise specified, " / " indicates that the objects associated before and after are in an "or" relationship, for example, A / B can represent A or B; wherein A and B can be singular or plural. Also, in the description of the present application, unless otherwise specified, "multiple" refers to two or more than two. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b, or c can represent: a, b, c, ab, ac, bc, or abc, wherein a, b, c can be single or multiple. In addition, in order to facilitate the clear description of the technical solutions of the embodiments of the present application, in the embodiments of the present application, the words "first", "second", etc. are used to distinguish the same items or similar items with substantially the same functions and effects. Those skilled in the art can understand that the words "first", "second", etc. do not limit the quantity and execution order, and the words "first", "second", etc. do not limit them to be necessarily different. Meanwhile, in the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a concrete manner for ease of understanding.

[0138] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the division of the unit is only a logical function division, and there may be other division methods in actual implementation, for example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. The mutual coupling, direct coupling, or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0139] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0140] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function according to the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transmitted through the computer-readable storage medium. The computer instructions can be transmitted from a website site, computer, server or data center to another website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (digital subscriber line, DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that contains one or more available media integrations. The available medium may be a read-only memory (ROM), or a random access memory (RAM), or a magnetic medium, such as a floppy disk, a hard disk, a tape, a disk, or an optical medium, such as a digital versatile disc (DVD), or a semiconductor medium, such as a solid state disk (SSD), etc.

[0141] The above is only a specific implementation of the embodiment of the present application, but the protection scope of the embodiment of the present application is not limited thereto, and any changes or replacements within the technical scope disclosed in the embodiment of the present application should be included in the protection scope of the embodiment of the present application. Therefore, the protection scope of the embodiment of the present application should be based on the protection scope of the claims.

[0142] The device embodiments described above are merely illustrative, wherein the units and modules described as separate components may or may not be physically separated. In addition, some or all of the units and modules may be selected according to actual needs to achieve the purpose of the present embodiment. Those of ordinary skill in the art may understand and implement the present invention without creative effort.

[0143] The above is only a specific implementation of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A method for controlling a camera device, characterized in that: A processor applied to a control system, wherein the control system further comprises a plurality of first camera devices and at least one second camera device, wherein the first camera device is a fixed camera device and the second camera device is a movable camera device, and the method comprises: Acquire a plurality of first images obtained by respectively photographing a plurality of first areas using a plurality of first camera devices; If a first facial image exists in a target first image among the plurality of first images, determining a second area according to the first facial image and the target first image; The second camera device is controlled to photograph the second area to obtain a second image.

2. The method according to claim 1, characterized in that The determining the second area according to the first facial image and the target first image comprises: determining first position data of the first facial image in the target first image; Determine a first three-dimensional coordinate of the first facial image in a controlled area according to the first position data, wherein the controlled area covers the plurality of first areas; The second area is determined according to the first three-dimensional coordinates, and the second area includes the first three-dimensional coordinates.

3. The method according to claim 2, characterized in that The method further comprises: Acquire a third image of the first area corresponding to the first target camera device after a first preset time of acquiring the first target image, wherein the first target camera device is the first camera device corresponding to the first target image; If the third image includes the first facial image, determining second position data of the first facial image in the third image; If the difference between the first position data and the second position data is greater than a preset difference, before determining the second area based on the first three-dimensional coordinates as the center, the method further includes: determining a moving direction and a moving speed of the first facial image according to the first position data and the second position data; The first three-dimensional coordinates are corrected according to the moving direction and moving speed of the first facial image.

4. The method according to claim 3, characterized in that If the third image does not include the first facial image, the method further includes: Acquire a fourth image of the first area corresponding to the second target camera device, wherein the fourth image includes the first facial image, and the second target camera device is a first camera device adjacent to the first target camera device; determining third position data of the first facial image in the fourth image; If the difference between the first position data and the second position data is greater than a preset difference, before determining the second area based on the first three-dimensional coordinates as the center, the method further includes: determining a moving direction and a moving speed of the first facial image according to the first position data and the third position data; The first three-dimensional coordinates are corrected according to the moving direction and moving speed of the first facial image.

5. The method according to any one of claims 1 to 4, characterized in that: The method further comprises: acquiring the at least one second facial image based on the second image; Determine a target facial image from the at least one second facial image, the target facial image being a second facial image having the smallest offset from the standard facial image among the at least one second facial image; Acquire at least one preset facial image; respectively calculating the similarity between the target facial image and the at least one preset facial image; If the similarity between the target facial image and any one of the preset facial images is not less than a first preset threshold, determining that the first identity recognition result of the target facial image is normal; If the similarity between the target facial image and any of the preset facial images is less than a first preset threshold, it is determined that the first identity recognition result of the target facial image is abnormal.

6. The method according to claim 5, characterized in that The control system further includes a plurality of third camera devices, wherein the third camera devices are movable camera devices, and the respectively calculating the similarity between the target facial image and the at least one preset facial image includes: Acquire multiple third facial images of the target person corresponding to the target facial image by taking multiple third photographing devices, wherein the third facial images are taken simultaneously when the second photographing device takes the target facial image; determining a second three-dimensional coordinate of each feature point of a plurality of feature points of the target facial image according to the target facial image and the plurality of third facial images; Calculating at least one first distance according to the second three-dimensional coordinates of each feature point among the plurality of feature points of the target facial image, wherein the first distance is a Euclidean distance calculated according to the second three-dimensional coordinates of any two feature points; Acquire at least one second distance of each preset facial image, wherein the first distance corresponds to the second distance in a one-to-one manner; The similarity between the target facial image and the at least one preset facial image is calculated respectively according to the at least one second distance of each preset facial image and the at least one first preset distance.

7. The method according to claim 6, characterized in that If the similarity between the target facial image and any one of the preset facial images is less than a first preset threshold, and the similarity between the target facial image and the target preset facial image is greater than a second preset threshold, and the second preset threshold is less than the first preset threshold, the method further includes: Determine a first body feature value of a target person corresponding to the target facial image according to the first image; Obtaining a second body feature value corresponding to the target preset facial image; generating a similarity compensation value according to the first body feature and the second body feature; The similarity between the target facial image and the target preset facial image is modified according to the similarity compensation value.

8. A control device for a camera device, characterized in that: The device is used to execute a control method for a camera device. The device belongs to a control system. The control system further includes a plurality of first camera devices and at least one second camera device. The first camera device is a fixed camera device, and the second camera device is a movable camera device. The device includes: An acquisition unit: used for acquiring a plurality of first images obtained by respectively photographing a plurality of first areas by a plurality of first camera devices; A determining unit: configured to determine a second area according to the first facial image and the target first image if a first facial image exists in the target first image among the plurality of first images; Control unit: used for controlling the second camera device to capture the second area to obtain a second image.

9. An electronic device, characterized in that: The method comprises a processor, a memory, a communication interface, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor, and the programs include instructions for executing the steps in the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program for electronic data exchange, wherein the computer program enables a computer to execute the method according to any one of claims 1 to 7.

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