Video surveillance method, device, equipment and storage medium

Abstract

Embodiments of the present application provide a video surveillance method, apparatus, device, and storage medium. The method includes: obtaining the number of access requests corresponding to each of a plurality of cameras, wherein the plurality of cameras are on the same network; determining a target camera from the plurality of cameras based on the number of access requests corresponding to each camera; and enabling the target camera for video surveillance. According to embodiments of the present application, a target camera can be selected from the plurality of cameras, and the number of enabled cameras can be flexibly adjusted to optimize network load.

Description

Technical Field

[0001] The present application relates to the field of monitoring technology, and in particular to a video monitoring method, apparatus, device and storage medium. Background Art

[0002] At present, video surveillance is widely used in production, security, transportation and other fields due to its intuitive, accurate and information-rich features.

[0003] However, traditional video surveillance solutions generate a large amount of video data during the monitoring process. When transmitting through the network, it takes up a lot of network resources, which can easily lead to excessive network load and affect the transmission of some data, resulting in a poor user experience. Summary of the Invention

[0004] The embodiments of the present application provide a video surveillance method, apparatus, device, and storage medium, which can optimize network load.

[0005] In a first aspect, an embodiment of the present application provides a video surveillance method, the method comprising:

[0006] Obtaining a number of access requests corresponding to each of a plurality of cameras, wherein the plurality of cameras are in the same network;

[0007] Determining a target shooting device from the plurality of shooting devices according to the number of access requests corresponding to each shooting device;

[0008] Enable target camera for video surveillance.

[0009] In some implementations of the first aspect, determining a target shooting device from a plurality of shooting devices according to the number of access requests corresponding to each shooting device includes:

[0010] Sort the number of access requests corresponding to each camera device by size;

[0011] The shooting devices corresponding to the first K access request numbers are determined as target shooting devices, where K is a positive integer.

[0012] In some implementations of the first aspect, determining a target shooting device from a plurality of shooting devices according to the number of access requests corresponding to each shooting device includes:

[0013] According to the number of access requests corresponding to each shooting device, a shooting device having a number of access requests greater than or equal to a preset number threshold is determined as a target shooting device.

[0014] In some implementations of the first aspect, before determining, based on the number of access requests corresponding to each capturing device, that a capturing device having a number of access requests greater than or equal to a preset threshold is a target capturing device, the method further includes:

[0015] Acquire network quality parameters of the network, wherein the network quality parameters include at least one of network bandwidth, network delay, and packet loss rate;

[0016] A preset quantity threshold is determined based on network quality parameters.

[0017] In some implementations of the first aspect, determining the preset quantity threshold according to the network quality parameter includes:

[0018] Determine a preset network quality level corresponding to the network quality parameter;

[0019] A preset quantity threshold is determined according to a preset network quality level.

[0020] In some implementations of the first aspect, determining the preset quantity threshold according to the network quality parameter includes:

[0021] The network quality parameter is input into a threshold determination model to obtain a preset quantity threshold, wherein the threshold determination model includes any one of a convolutional neural network, a recurrent neural network, and a recursive neural network.

[0022] In some implementations of the first aspect, enabling the target shooting device includes:

[0023] The activation instruction information is sent to the target shooting device, so that the target shooting device starts video monitoring in response to the activation instruction information.

[0024] In a second aspect, an embodiment of the present application provides a video surveillance device, the device comprising:

[0025] an acquisition module, configured to acquire a number of access requests corresponding to each of a plurality of shooting devices, wherein the plurality of shooting devices are in the same network;

[0026] a determination module, configured to determine a target shooting device from a plurality of shooting devices according to the number of access requests corresponding to each shooting device;

[0027] The enabling module is used to enable the target shooting device for video surveillance.

[0028] In some implementations of the second aspect, the determining module includes:

[0029] A sorting unit, configured to sort the number of access requests corresponding to each camera device according to the number;

[0030] The first determining unit is configured to determine that the photographing devices corresponding to the first K access requests are target photographing devices, where K is a positive integer.

[0031] In some implementations of the second aspect, the determining module includes:

[0032] The second determining unit is configured to determine, based on the number of access requests corresponding to each shooting device, a shooting device having a number of access requests greater than or equal to a preset number threshold as a target shooting device.

[0033] In some implementations of the second aspect, the acquisition module is further configured to, before determining, based on the number of access requests corresponding to each camera device, a camera device having a number of access requests greater than or equal to a preset threshold as a target camera device, acquire a network quality parameter of the network, where the network quality parameter includes at least one of network bandwidth, network latency, and packet loss rate;

[0034] The determination module is further configured to determine a preset quantity threshold according to network quality parameters.

[0035] In some implementations of the second aspect, the determining module includes:

[0036] A third determining unit, configured to determine a preset network quality level corresponding to the network quality parameter;

[0037] The third determining unit is further configured to determine a preset quantity threshold according to a preset network quality level.

[0038] In some implementations of the second aspect, the determining module includes:

[0039] The input unit is used to input the network quality parameter into the threshold determination model to obtain a preset quantity threshold, wherein the threshold determination model includes any one of a convolutional neural network, a recurrent neural network, and a recursive neural network.

[0040] In some implementations of the second aspect, the enabling module includes:

[0041] The sending unit is configured to send activation instruction information to the target shooting device, so that the target shooting device starts video monitoring in response to the activation instruction information.

[0042] In a third aspect, an embodiment of the present application provides a video surveillance device, the device comprising: a processor and a memory storing computer program instructions;

[0043] When the processor executes the computer program instructions, it implements the video surveillance method described in the first aspect or any of the implementable embodiments of the first aspect.

[0044] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium having computer program instructions stored thereon. When the computer program instructions are executed by a processor, the video surveillance method described in the first aspect or any implementable manner of the first aspect is implemented.

[0045] The embodiments of the present application provide a video surveillance method, apparatus, device, and storage medium. By obtaining the number of access requests corresponding to each of multiple shooting devices on the same network, a target shooting device is selected from the multiple shooting devices according to the number of access requests corresponding to the shooting device. The number of enabled devices in the network can be flexibly adjusted according to the number of access requests, i.e., the number of accessing users, thereby optimizing the network load and improving the user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0047] Figure 1 This is a schematic diagram of the architecture of a video surveillance system provided by an embodiment of the present application;

[0048] Figure 2 This is a schematic diagram of the architecture of another video surveillance system provided by an embodiment of the present application;

[0049] Figure 3 This is a fire alarm diagram provided by an embodiment of the present application;

[0050] Figure 4 This is a schematic diagram of the architecture of another video surveillance system provided by an embodiment of the present application;

[0051] Figure 5 This is a camera control schematic diagram provided by an embodiment of the present application;

[0052] Figure 6 This is a flow chart of a video surveillance method provided by an embodiment of the present application;

[0053] Figure 7 This is a schematic structural diagram of a video surveillance device provided in an embodiment of the present application;

[0054] Figure 8 It is a structural diagram of a video surveillance device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0055] The features and exemplary embodiments of various aspects of the present application will be described in detail below. In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings and Examples. It should be understood that the specific embodiments described herein only explain the present application, rather than limit the present application. For those skilled in the art, the present application can be implemented without the need for some of these specific details. The following description of the embodiments is merely to provide a better understanding of the present application by illustrating the examples of the present application.

[0056] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article, or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or device. In the absence of further limitations, the elements defined by the phrase "comprising..." do not exclude the presence of other identical elements in the process, method, article, or device comprising the elements.

[0057] Currently, traditional video surveillance solutions require deploying multiple cameras within a surveillance area for comprehensive monitoring. These cameras are typically deployed on the same network, such as a local area network (LAN). When multiple cameras operate simultaneously, they generate a large amount of video data, requiring significant network resources for data transmission and potentially causing network overload. Furthermore, other devices on the network can be negatively impacted.

[0058] Therefore, to address the problems of the prior art, embodiments of the present application provide a video surveillance method, apparatus, device, and storage medium. By obtaining the number of access requests corresponding to each of multiple cameras on the same network and selecting a target camera from the multiple cameras based on the number of access requests corresponding to the camera, the number of enabled devices in the network can be flexibly adjusted based on the number of access requests, i.e., the number of accessing users, thereby optimizing network load and improving user experience.

[0059] The potential video surveillance method, apparatus, device and storage medium provided by the embodiments of the present application are described in detail below with reference to the accompanying drawings through specific embodiments and their application scenarios.

[0060] Figure 1 This is a schematic diagram of the architecture of a video surveillance system provided by an embodiment of the present application. Figure 1As shown, the video surveillance system may include multiple electronic devices 110, a server 120, a monitoring device 130, and multiple camera devices 140. The electronic devices 110 may be mobile or non-mobile electronic devices. For example, the mobile electronic devices may be mobile phones, tablet computers, laptop computers, PDAs, ultra-mobile personal computers (UMPCs), etc., while the non-mobile electronic devices may be servers, network attached storage (NAS), personal computers (PCs), etc. The server 120 may be a high-performance electronic calculator for storing and processing data. The monitoring device 130 may exist as a standalone device or as a module in the server 120. The multiple camera devices 140 are located on the same network, such as the same local area network, and may be cameras, devices equipped with camera modules, etc. The electronic devices 110, server 120, monitoring device 130, and camera devices communicate with each other via a network, which may be a wired communication network or a wireless communication network.

[0061] The video surveillance system can be applied to places where surveillance is required, such as business halls, computer rooms, warehouses, archives, schools, factories, and stations. Specifically, multiple electronic devices 110 can send access requests to the server 120. The access request corresponds to the shooting device 140 and is used to request access to the shooting device 140 and obtain the content shot by the shooting device 140. The server 120 can then send the access request to the monitoring device 130. Based on the access request, the monitoring device 130 can count the number of access requests corresponding to each of the multiple shooting devices 140. Based on the number of access requests corresponding to each shooting device 140, the target shooting device is determined from the multiple shooting devices 140. The target shooting device is then enabled for video surveillance. For example, an enablement indication message can be sent to the shooting device 140 determined as the target shooting device. The shooting device 140 starts video surveillance in response to the enablement indication message.

[0062] Figure 2 This is a schematic diagram of the architecture of another video surveillance system provided by an embodiment of the present application. Figure 2 As shown, electronic device 110 may be a PC, server 120 may include a streaming server, a monitoring server, an identification server, an alarm server, and a front-end server, monitoring device 130 may be integrated into the front-end server as a module, and camera 140 may be a camera deployed in a monitoring area such as a computer room or warehouse. The network between devices may be an intranet or the Internet.

[0063] After the camera is enabled as a target shooting device, it can shoot the monitored area, that is, collect video stream data of the monitored area in real time and send the video stream data to the front-end server.

[0064] Based on the video stream data, the front-end server can identify alarms with higher real-time levels, such as fire and water leakage alarms, and obtain first identification information, and preliminarily identify alarms with lower real-time levels, such as abnormal entry and exit of personnel and abnormal behaviors (such as theft and destruction), obtain pre-processed alarm data, and send the first identification information to the monitoring server, send the pre-processed alarm data to the identification server, and send video stream data to the streaming media server.

[0065] The recognition algorithm for various abnormal scenarios running in the recognition server can identify the alarm category based on the pre-processed alarm data and obtain the second identification information, so that the video surveillance system can quickly and accurately identify the abnormality and alarm, and send the second identification information to the monitoring server. For example, it can be deployed in a cluster manner.

[0066] The monitoring server may be a monitoring platform, which may send alarm information to the alarm server according to the first identification information or the second identification information, and may also be used to control services such as flow acquisition.

[0067] The streaming media server can be used to distribute and replicate the video stream address of the video stream data, that is, to send the video stream data to the PC. It can also realize remote monitoring and provide input for subsequent recognition algorithms. For example, it can be deployed in a cluster manner.

[0068] The alarm server may be a short message server, ie, a short message platform, an email server, etc., which may send alarm information to a preset alarm device.

[0069] The PC, as the electronic device 140 , can simultaneously display monitoring images of multiple areas, view historical video recordings, receive or view alarm information, and so on.

[0070] The following is an example of how the video capture system is applied to a fire scene. Figure 3 As shown, the following steps may be included:

[0071] Step 1: The camera captures the monitored area and generates video stream data in real time.

[0072] Step 2: The camera sends video stream data to the front-end server.

[0073] Step 3: The front-end server identifies whether a fire has occurred based on the fire identification algorithm and the video stream data. If so, it generates fire identification information.

[0074] Step 4: The front-end server sends fire identification information to the monitoring server.

[0075] Step 5: The monitoring server generates fire alarm information based on the fire identification information.

[0076] Step 6: The monitoring server calls the interface of the alarm server and sends fire alarm information to the alarm server.

[0077] Step 7: The alarm server sends a fire alarm message to the designated electronic device, notifying relevant personnel. Relevant personnel can view the monitoring screen through the electronic device and organize rescue operations.

[0078] In this embodiment, unattended, uninterrupted operation is possible, automatically detecting abnormal smoke and fire signs within the monitored area and quickly alerting relevant personnel. Furthermore, the system is not restricted by environmental conditions such as height, thermal barriers, explosives, and toxic substances, and can provide effective monitoring and early warning in indoor and outdoor spaces, as well as in special locations where traditional detection methods are ineffective.

[0079] In some embodiments, the video surveillance system can monitor multiple areas, such as Figure 4 As shown in the figure, the video surveillance system monitors N areas, such as N business halls, and each area has multiple cameras. Figure 1 、 Figure 2 The systems shown are similar and are not described here for brevity.

[0080] See also Figure 4 In terms of module division by function, the video surveillance system can include user management module, authority management module, video management module, remote management module, video projection module, remote training module, streaming media module, and abnormal alarm module.

[0081] The user management module can be used to add and delete users, modify user information, change passwords, and perform user authentication. User verification can include at least one of camera authentication, data encryption authentication, and Real-Time Streaming Protocol (RTSP) authentication, ensuring that only authenticated users can access video content, improving the security of video surveillance.

[0082] The permission management module can be used to add groups, assign permissions, delete permissions, etc.

[0083] The video management module can be used for real-time video, video playback, video download, video patrol, video recording, screenshot capture, etc.

[0084] The remote management module can be used for attendance check-in, camera angle control, behavioral violation reminders, vacant post reminders, etc. Among them, attendance check-in is specifically implemented by recording the employee's clock-in and clock-out time and synchronizing the employee's clock-in and clock-out time to the database, thereby implementing attendance supervision of the personnel.

[0085] On the one hand, the camera angle control can be realized by setting the rotation movement of each camera at a fixed time, so that the remote inspection monitoring area can be carried out at a fixed time. Figure 5 As shown, the primary monitoring system controls the secondary monitoring system. The video monitoring system provided in the embodiment of the present application is the primary monitoring system, while the traditional video monitoring system is the secondary monitoring system. The primary monitoring system can transmit control commands via the network to the secondary monitoring system. After the secondary monitoring system parses the command, it sends the command parameters to the camera's pan / tilt control interface, thereby achieving remote control of the camera's rotation.

[0086] The video projection module can be used to project videos to a specified area.

[0087] The remote training module can be used to broadcast live training videos captured by cameras, which can be viewed by all authorized users.

[0088] The streaming media module can be used to broadcast the video stream data collected by the camera live.

[0089] The Abnormal Alarm Module generates and sends alarms to designated electronic devices, notifying designated users when there's a sudden increase in the number of people in the monitored area, when someone is absent from their post, or when a fire occurs. It also generates statistics on the number of alarms, alarm areas, and alarm types, and displays these statistics in charts.

[0090] The following describes the video monitoring method provided by the embodiment of the present application. The execution subject of the video monitoring method can be Figure 1 The monitoring device 130 in the video surveillance system shown, or a module in the monitoring device 130.

[0091] Figure 6 This is a flow chart of a video surveillance method provided by an embodiment of the present application, such as Figure 6 As shown, the video monitoring method may include the following steps:

[0092] S610: Obtain the number of access requests corresponding to each of the multiple shooting devices.

[0093] Wherein, multiple cameras are in the same network, for example, multiple cameras in a school are in the same campus local area network. For example, access requests corresponding to the cameras sent by multiple electronic devices can be obtained from the server and counted to determine the number of access requests corresponding to each camera.

[0094] S620: Determine a target shooting device from multiple shooting devices according to the number of access requests corresponding to each shooting device.

[0095] In some embodiments, the number of access requests corresponding to each shooting device can be sorted by size, and the shooting devices corresponding to the first K numbers of access requests are determined as target shooting devices, where K is a positive integer.

[0096] For example, there are cameras a, b, c, and d in the same network, where the number of access requests corresponding to cameras a, b, c, and d are 8, 7, 6, and 5, respectively. Sort the access requests by size, and take the shooting devices corresponding to the first three numbers of access requests as the target shooting devices. At this time, the target shooting devices are a, b, and c.

[0097] In other embodiments, based on the number of access requests corresponding to each camera, a camera having a number of access requests greater than or equal to a preset number threshold may be determined as a target camera. The preset number threshold may be set by relevant personnel based on experience.

[0098] S630, enable the target shooting device.

[0099] After the target shooting device is enabled, it can be used for video monitoring. In one example, an enabling instruction message can be sent to the target shooting device, so that the target shooting device starts video monitoring in response to the enabling instruction message, that is, is enabled.

[0100] In an embodiment of the present application, by obtaining the number of access requests corresponding to each shooting device in multiple shooting devices on the same network, and selecting a target shooting device from the multiple shooting devices according to the number of access requests corresponding to the shooting device, the number of enabled devices in the network can be flexibly adjusted according to the number of access requests, that is, the number of accessing users, thereby optimizing the network load and improving the user experience.

[0101] In some embodiments, before S620, the method may further include: obtaining network quality parameters of the network. The network quality parameters may include at least one of network bandwidth, network latency, and packet loss rate. Then, based on the network quality parameters, a preset quantity threshold is determined. Flexible determination of the preset quantity threshold based on network quality can further optimize network load.

[0102] As an example, a preset network quality level corresponding to the network quality parameter can be determined based on the network quality parameter. Then, a preset quantity threshold can be determined based on the preset network quality level. Specifically, the preset quantity threshold corresponding to the preset network quality level can be determined. For example, if network quality parameter a is a network bandwidth of 50M, a network delay of 100ms, and a packet loss rate of 3%, then the preset network quality level corresponding to network quality parameter a is 3, and the preset quantity threshold corresponding to the preset network quality level 3 is 5.

[0103] In addition, the network quality parameters can be input into a threshold determination model to obtain a preset quantity threshold. The threshold determination model is pre-trained based on training data and can include any one of a convolutional neural network, a recurrent neural network, and a recursive neural network.

[0104] Based on the video monitoring method provided in the embodiment of the present application, the embodiment of the present application also provides a video monitoring device, such as Figure 7 As shown, the video monitoring device 700 may include: an acquisition module 710 , a determination module 720 , and an activation module 730 .

[0105] The acquisition module 710 is configured to acquire the number of access requests corresponding to each of the plurality of shooting devices, wherein the plurality of shooting devices are in the same network.

[0106] The determination module 720 is configured to determine a target shooting device from a plurality of shooting devices according to the number of access requests corresponding to each shooting device.

[0107] The enabling module 730 is used to enable the target shooting device for video monitoring.

[0108] In some embodiments, the determination module 720 includes: a sorting unit, configured to sort the number of access requests corresponding to each photographing device according to the size of the number.

[0109] The first determining unit is configured to determine that the photographing devices corresponding to the first K access requests are target photographing devices, where K is a positive integer.

[0110] In some embodiments, the determination module 720 includes: a second determination unit, configured to determine, based on the number of access requests corresponding to each shooting device, a shooting device having a number of access requests greater than or equal to a preset number threshold as a target shooting device.

[0111] In some embodiments, the acquisition module 710 is further configured to acquire a network quality parameter before determining, based on the number of access requests corresponding to each camera device, a camera device having a number of access requests greater than or equal to a preset threshold as a target camera device. The network quality parameter includes at least one of network bandwidth, network latency, and packet loss rate.

[0112] The determination module 720 is further configured to determine a preset quantity threshold according to the network quality parameter.

[0113] In some embodiments, the determination module 720 includes: a third determination unit, configured to determine a preset network quality level corresponding to the network quality parameter.

[0114] The third determining unit is further configured to determine a preset quantity threshold according to a preset network quality level.

[0115] In some embodiments, the determination module 720 includes an input unit configured to input the network quality parameter into a threshold determination model to obtain a preset quantity threshold, wherein the threshold determination model includes any one of a convolutional neural network, a recurrent neural network, and a recursive neural network.

[0116] In some embodiments, the enabling module 730 includes: a sending unit, configured to send enabling instruction information to the target shooting device, so that the target shooting device starts video monitoring in response to the enabling instruction information.

[0117] It is understandable that Figure 7 Each module / unit in the video surveillance device 700 shown has the function of implementing each step in the video surveillance method provided in the embodiment of the present application and can achieve its corresponding technical effects. For the sake of brevity, they are not described here in detail.

[0118] Figure 8 It is a structural diagram of a video surveillance device provided in an embodiment of the present application.

[0119] like Figure 8 As shown, the video surveillance device 800 in this embodiment includes an input device 801, an input interface 802, a central processing unit 803, a memory 804, an output interface 805, and an output device 806. The input interface 802, the central processing unit 803, the memory 804, and the output interface 805 are interconnected via a bus 810. The input device 801 and the output device 806 are connected to the bus 810 via the input interface 802 and the output interface 805, respectively, and are further connected to other components of the video surveillance device 800.

[0120] Specifically, the input device 801 receives input information from the outside and transmits the input information to the central processing unit 803 through the input interface 802; the central processing unit 803 processes the input information based on the computer-executable instructions stored in the memory 804 to generate output information, temporarily or permanently stores the output information in the memory 804, and then transmits the output information to the output device 806 through the output interface 805; the output device 806 outputs the output information to the outside of the video surveillance device 800 for user use.

[0121] In some embodiments, Figure 8 The video surveillance device 800 shown includes: a memory 804 for storing programs; and a processor 803 for running the programs stored in the memory to implement the video surveillance method provided in the embodiment of the present application.

[0122] An embodiment of the present application further provides a computer-readable storage medium having computer program instructions stored thereon; when the computer program instructions are executed by a processor, the video surveillance method provided in the embodiment of the present application is implemented.

[0123] It should be understood that the various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other. For the sake of brevity, they will not be described in detail. The present application is not limited to the specific configurations and processes described above and shown in the figures. For the sake of simplicity, a detailed description of the known methods is omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of the present application is not limited to the specific steps described and shown, and those skilled in the art can make various changes, modifications and additions, or change the order between the steps after understanding the spirit of the present application.

[0124] The functional blocks shown in the above-described block diagram can be implemented as hardware, software, firmware or a combination thereof. When implemented in hardware, it can be, for example, an electronic circuit, an application specific integrated circuit (ASIC), appropriate firmware, a plug-in, a function card, etc. When implemented in software, the elements of the present application are programs or code segments that are used to perform the required tasks. The program or code segment can be stored in a machine-readable medium, or transmitted on a transmission medium or a communication link via a data signal carried in a carrier wave. "Machine-readable medium" can include any medium that can store or transmit information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, read-only memories (ROMs), flash memories, erasable ROMs (EROMs), floppy disks, CD-ROMs, optical disks, hard disks, optical fiber media, radio frequency (RF) links, etc. The code segments can be downloaded via computer networks such as the Internet, intranets, etc.

[0125] It should also be noted that the exemplary embodiments mentioned in this application describe some methods or systems based on a series of steps or devices. However, this application is not limited to the order of the above steps. In other words, the steps can be performed in the order mentioned in the embodiments, or in a different order, or several steps can be performed simultaneously.

[0126] Aspects of the present disclosure have been described above with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present disclosure. It should be understood that each box in the flowchart and / or block diagram and the combination of each box in the flowchart and / or block diagram can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer or other programmable data processing device to produce a machine so that these instructions executed by the processor of the computer or other programmable data processing device enable the implementation of the function / action specified in one or more boxes of the flowchart and / or block diagram. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor or a field programmable logic circuit. It is also understood that each box in the block diagram and / or flowchart and the combination of the boxes in the block diagram and / or flowchart can also be implemented by dedicated hardware that performs the specified function or action, or can be implemented by a combination of dedicated hardware and computer instructions.

[0127] The above description is only a specific embodiment of the present application. Those skilled in the art will clearly understand that for the convenience and brevity of description, the specific working processes of the systems, modules and units described above can refer to the corresponding processes in the aforementioned method embodiments, and will not be repeated here. It should be understood that the scope of protection of the present application is not limited thereto. Any person skilled in the art can easily think of various equivalent modifications or replacements within the technical scope disclosed in the present application, and these modifications or replacements should be included in the scope of protection of the present application.

Claims

1. A video monitoring method, characterized in that: The method comprises: Obtaining a number of access requests corresponding to each of a plurality of shooting devices, wherein the plurality of shooting devices are in the same network; determining a target shooting device from the plurality of shooting devices according to the number of access requests corresponding to each shooting device and a preset number threshold, wherein the preset number threshold is determined based on a network quality parameter; Activating the target camera for video surveillance; receiving video stream data sent by the target shooting device, identifying alarms with a higher real-time level to obtain first identification information, and preliminarily identifying alarms with a lower real-time level to obtain pre-processed alarm data; Sending the first identification information to the monitoring server and the pre-processed alarm data to the identification server, so that the identification server can identify the alarm category based on the pre-processed alarm data, obtain second identification information, and send the second identification information to the monitoring server; The monitoring server sends alarm information to the alarm server according to the first identification information or the second identification information.

2. The method according to claim 1, characterized in that The determining a target shooting device from the plurality of shooting devices according to the number of access requests corresponding to each shooting device and a preset number threshold comprises: Sort the number of access requests corresponding to each of the photographing devices by size; The shooting devices corresponding to the first K access request quantities are determined as the target shooting devices, where K is a positive integer.

3. The method according to claim 1, characterized in that The determining a target shooting device from the plurality of shooting devices according to the number of access requests corresponding to each shooting device and a preset number threshold comprises: According to the number of access requests corresponding to each shooting device, a shooting device having a number of access requests greater than or equal to the preset number threshold is determined as the target shooting device.

4. The method according to claim 3, characterized in that Before determining, based on the number of access requests corresponding to each of the photographing devices, that a photographing device having a number of access requests greater than or equal to the preset number threshold is the target photographing device, the method further includes: Acquire network quality parameters of the network, wherein the network quality parameters include at least one of network bandwidth, network delay, and packet loss rate; The preset quantity threshold is determined according to the network quality parameter.

5. The method according to claim 4, characterized in that The determining the preset quantity threshold according to the network quality parameter includes: Determining a preset network quality level corresponding to the network quality parameter; The preset quantity threshold is determined according to the preset network quality level.

6. The method according to claim 4, characterized in that The determining the preset quantity threshold according to the network quality parameter includes: The network quality parameter is input into a threshold determination model to obtain the preset quantity threshold, wherein the threshold determination model includes any one of a convolutional neural network, a recurrent neural network, and a recursive neural network.

7. The method according to claim 1, characterized in that The enabling of the target shooting device includes: An activation instruction message is sent to the target shooting device, so that the target shooting device starts video monitoring in response to the activation instruction message.

8. A video surveillance device, characterized in that: The device comprises: an acquisition module, configured to acquire a number of access requests corresponding to each of a plurality of shooting devices, wherein the plurality of shooting devices are in the same network; a determination module, configured to determine a target shooting device from the plurality of shooting devices according to the number of access requests corresponding to each shooting device and a preset number threshold, wherein the preset number threshold is determined based on a network quality parameter; An enabling module, configured to enable the target shooting device for video surveillance; an identification module configured to receive video stream data sent by the target shooting device, identify alarms with a higher real-time level, obtain first identification information, and preliminarily identify alarms with a lower real-time level, obtain pre-processed alarm data; a first sending module, configured to send first identification information to the monitoring server and send pre-processed alarm data to the recognition server, so that the recognition server can identify the alarm category based on the pre-processed alarm data, obtain second identification information, and send the second identification information to the monitoring server; The second sending module is used for the monitoring server to send alarm information to the alarm server according to the first identification information or the second identification information.

9. A video surveillance device, characterized in that: The device includes: a processor and a memory storing computer program instructions; when the processor executes the computer program instructions, the video surveillance method according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer program instructions, and when the computer program instructions are executed by a processor, the video surveillance method according to any one of claims 1 to 7 is implemented.

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