Video monitoring method, video monitoring system and electronic equipment

Abstract

The invention relates to a video monitoring method, a video monitoring system and electronic equipment, and the method comprises the steps: obtaining a face image collected from a target place through an early warning service module; querying archive information matched with the face image in an image archive library; if archive information matched with the face image is inquired in the image archive library, whether the current object belongs to a suspicious target or not is judged according to the archive information; if it is judged that the current object belongs to a suspicious target according to the archive information, an early warning process is triggered, and the early warning process comprises the steps that early warning information is sent to a user terminal to prompt the user terminal that the suspicious target exists in the target place, and identity information of the suspicious target needs to be reported to a management platform; and in response to identity record information corresponding to the suspicious target returned by the management platform, updating the state of the early warning process according to the identity record information, the state of the early warning process including rejection or passage of the suspicious target. According to the invention, the access pressure of the management platform can be reduced, and the management timeliness can be improved.

Description

Technical Field

[0001] This application relates to the field of video surveillance, and in particular to a video surveillance method, a video surveillance system, and an electronic device. Background Technology

[0002] Currently, certain business establishments (such as hotels, bars, and KTVs) typically install surveillance equipment at their entrances to prevent suspicious targets (such as minors) from entering. The captured images are then transmitted to a control center for facial recognition. Once a suspicious target is identified, the management department will intervene and implement management measures.

[0003] The management department has set up a management platform; however, the current video surveillance system relies excessively on the platform's capabilities, resulting in significant access pressure on the platform. Furthermore, once the management platform identifies a suspicious target, it struggles to manage the scene immediately, leading to management delays. Summary of the Invention

[0004] Therefore, it is necessary to provide a video surveillance method, video surveillance system, and electronic device that can reduce the access pressure on the management platform and improve the timeliness of management, in order to address the above-mentioned technical problems.

[0005] In a first aspect, this application provides a video surveillance method applied to an early warning service module, the method comprising:

[0006] Acquire facial images from the target location;

[0007] Search the image archive for file information that matches the face image;

[0008] If file information matching the face image is found in the image archive, it is determined whether the current object is a suspicious target based on the file information.

[0009] If the current object is determined to be a suspicious target based on the file information, an early warning process is triggered, which includes:

[0010] Send a warning message to the user terminal to remind the user terminal that there is a suspicious target in the target location and that the identity information of the suspicious target needs to be reported to the management platform;

[0011] In response to the identity registration information corresponding to the suspicious target returned by the management platform, the status of the early warning process is updated according to the identity registration information. The status of the early warning process includes rejecting or allowing the suspicious target to pass.

[0012] In one embodiment, after sending the warning information to the user terminal, the method further includes:

[0013] In response to the first access request initiated by the user terminal, trajectory information corresponding to the suspicious target is sent to the user terminal.

[0014] In one embodiment, in response to a first access request initiated by the user terminal, trajectory information corresponding to the suspicious target is sent to the user terminal, including:

[0015] Based on the first access request, a second access request is initiated to the image archive to query the trajectory information of the suspicious target;

[0016] In response to the trajectory information of the suspicious target returned by the image archive, the trajectory information of the suspicious target is sent to the user terminal.

[0017] In one embodiment, before sending the warning information to the user terminal, the method further includes:

[0018] Acquire video frame images corresponding to the suspicious target, collected at different times by multiple monitoring devices in the target location;

[0019] Based on video frame images collected at different times by multiple monitoring devices in the target location, trajectory information corresponding to the suspicious target is generated;

[0020] The trajectory information is stored in the image archive.

[0021] In one embodiment, determining whether the current object is a suspicious target based on the file information includes:

[0022] Determine whether the file information carries a target attribute identifier;

[0023] If the file information is determined to carry the target attribute identifier, then the current object is determined to be a suspicious target.

[0024] In one embodiment, the method further includes:

[0025] If it is determined that the file information does not carry an attribute identifier, a third access request is initiated to the management platform to query the attribute identifier of the current object and update the attribute identifier of the current object in the image archive.

[0026] In one embodiment, the method further includes:

[0027] If no matching profile information is found in the image database, profile information for the current object is created in the image database, and the attributes of the current object are analyzed based on the face image.

[0028] Based on the attributes of the current object obtained from the analysis, determine whether the current object belongs to a suspicious target.

[0029] Secondly, this application also provides a video surveillance method applied to a user terminal, wherein the user terminal is connected to an early warning service module, and when the early warning service module triggers an early warning process according to the method described in the first aspect above, the method includes:

[0030] The user terminal pop-up warning information is used to indicate that there is a suspicious target in the target location, and the identity information of the suspicious target needs to be reported to the management platform;

[0031] Initiate a first access request to the early warning service module to query the trajectory information corresponding to the suspicious target;

[0032] The system receives the trajectory information of the suspicious target returned by the early warning service module, determines the current location of the suspicious target based on the trajectory information, and prompts the user to urge the suspicious target to report its identity information to the management platform by scanning a QR code.

[0033] After the management platform returns the identity registration information corresponding to the suspicious target to the early warning service module, and the early warning service module updates the status of the early warning process based on the identity registration information, the user terminal displays the current status of the early warning process. The status of the early warning process includes rejecting or allowing the suspicious target to pass.

[0034] Thirdly, this application also provides a video surveillance system, including: a monitoring device, a view library, an image archive library, an image analysis service module, and an early warning service module, wherein the monitoring device is connected to the view library, and the view library, the image archive library, and the image analysis service module are respectively connected to the early warning service module, wherein:

[0035] The monitoring equipment is used to collect image data and upload the image data to the view library;

[0036] The view library is used to store the image data and upload the image data to the early warning service module;

[0037] The image archive is used to store the archive information of objects;

[0038] The image analysis service module is used to analyze the image data and extract image feature vectors and attributes corresponding to the current object;

[0039] The early warning service module implements the video surveillance method described in the first aspect by calling the view library, the image archive library, and the image analysis service module.

[0040] Fourthly, this application also provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the method described in the first or second aspect above.

[0041] The aforementioned video surveillance methods, systems, and electronic devices, specifically designed for target locations, particularly in scenarios requiring large-scale deployment of surveillance equipment for early warning systems, utilize an early warning service module in conjunction with an image database to identify suspicious targets. This avoids direct queries to the management platform, reducing its access load. Furthermore, upon identifying a suspicious target, the early warning service module triggers an early warning process, linking user terminals and the management platform to control the suspicious target, thus improving the timeliness of management. Attached Figure Description

[0042] Figure 1 This is a topology diagram of a video surveillance system in one embodiment;

[0043] Figure 2 This is a schematic diagram of the application environment of a video surveillance system in one embodiment;

[0044] Figure 3 This is a flowchart illustrating a video surveillance method in one embodiment;

[0045] Figure 4 This is a flowchart illustrating a video surveillance method in another embodiment;

[0046] Figure 5-1 This is a schematic diagram of the operation flow of a video surveillance system in one embodiment. Figure 1 ;

[0047] Figure 5-2 This is a schematic diagram of the operation flow of a video surveillance system in one embodiment. Figure 2 ;

[0048] Figure 6 This is a diagram of the internal structure of an electronic device in one embodiment. Detailed Implementation

[0049] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0050] Unless otherwise defined, the technical or scientific terms used in this application shall have the general meaning understood by one of ordinary skill in the art to which this application pertains. Words such as “a,” “an,” “an,” “the,” “the,” and “these” used in this application do not indicate quantitative limitation and may be singular or plural. The terms “comprising,” “including,” “having,” and any variations thereof used in this application are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or device that comprises a series of steps or modules (units) is not limited to the listed steps or modules (units) but may include steps or modules (units) not listed, or may include other steps or modules (units) inherent to these processes, methods, products, or devices. Words such as “connected,” “linked,” and “coupled” used in this application are not limited to physical or mechanical connections but may include electrical connections, whether direct or indirect. “Multiple” used in this application refers to two or more. “And / or” describes the relationship between related objects, indicating that three relationships may exist; for example, “A and / or B” can represent: A alone, A and B simultaneously, and B alone. Normally, the character " / " indicates that the objects before and after it are in an "or" relationship. The terms "first," "second," "third," etc., used in this application are merely to distinguish similar objects and do not represent a specific order of objects.

[0051] In one embodiment, Figure 1 A video surveillance system is provided, such as Figure 1 As shown, the system includes: monitoring equipment 1, a view library 2, an image archive library 3, an image analysis service module 4, and an early warning service module 5. The view library 2, image archive library 3, and image analysis service module 4 are all connected to the early warning service module 5. Among them:

[0052] Monitoring device 1 is used to acquire image data and upload the image data to the view library 2. Specifically, monitoring device 1 can be a GB / T 1400 camera.

[0053] View Library 2 is used to store image data and upload it to the early warning service module 5. Specifically, View Library 2 is a video image information resource library, which can be a video image information resource library conforming to the GB / T 1400 protocol. GB / T 1400, short for "Technical Requirements for Information Transmission, Exchange and Control of Public Security Video Surveillance Network System," is a standard that standardizes the interconnection of video surveillance systems in a specific region's public security field. It is used to unify the data format, transmission protocol, and interface standards of the view library, enabling the integration and sharing of video resources between different manufacturers' equipment and platforms, thereby improving social security prevention and emergency response capabilities.

[0054] Image archive 3 is used to store the archive information of objects. Specifically, image archive 3 stores the image feature vectors and archive information of objects. Objects refer to people, and archive information includes the person's identity information and attribute identifiers. Attribute identifiers can be age ranges, such as minors, adults, and the elderly.

[0055] Image feature vectors are numerical representations extracted from face images using algorithms (such as SIFT and CNN). Essentially, they are a set of multi-dimensional numerical sequences describing key image features (such as contours, textures, and object structures). Image Archive 3 supports image retrieval (such as face comparison), classification and recognition (such as distinguishing between plants and animals), cluster analysis (such as categorizing similar products), and data compression (dimensionality reduction for optimized storage). By calculating the similarity between image feature vectors (such as cosine distance), the degree of similarity between individuals in two face images can be determined, thereby enabling the retrieval of archive information.

[0056] Image analysis service module 4 is used to analyze image data and extract image feature vectors and the attributes of the corresponding current object.

[0057] The early warning service module 5 implements video surveillance by calling the view library 2, image archive library 3, and image analysis service module 4.

[0058] The aforementioned view library 2 and image archive library 3 can be integrated into a single data storage server or distributed across multiple data storage servers. Each of the aforementioned service modules can be implemented using a separate server or a server cluster composed of multiple servers. For example, image analysis service module 4 and early warning service module 5 can be integrated into a single server, or they can be deployed on separate servers respectively; this embodiment does not impose any limitations on either.

[0059] In some embodiments, Figure 2 A schematic diagram of the application environment of the video surveillance system is provided, such as... Figure 2 As shown, the early warning service module 5 is connected to both the user terminal 6 and the management platform 7. The monitoring device 1 is deployed at the entrances and exits of the target location. The user terminal 6 is the terminal device held by a user at the target location, such as the person in charge of the target location. The management platform 7 is a service platform held by the management department; specifically, this service platform can be a digital platform that integrates resources from multiple parties to participate in regional security governance through information technology.

[0060] View Library 2, Image Archive Library 3, Image Analysis Service Module 4, and Early Warning Service Module 5 are connected via the VideoLink private network. The VideoLink private network is a network architecture based on video communication and IoT technologies, enabling real-time transmission, intelligent analysis, and collaborative applications of high-definition video data. It integrates monitoring equipment, video conferencing, emergency command, and other terminal devices through a private network or the internet, supporting low-latency transmission of large-scale video streams; and combines AI technology to achieve intelligent processing such as facial recognition, behavior analysis, and abnormal event early warning.

[0061] In this embodiment, when a person passes through the monitoring area of ​​monitoring device 1, the monitoring device captures a facial image of the person passing by. Monitoring device 1 analyzes the facial image, generates capture information, and transmits the capture information to view library 2 via the video conferencing network. View library 2 then transmits the capture information to early warning service module 5. Early warning service module 5 calls image analysis service module 4 to analyze the capture information, obtain the facial image, and extract the image feature vector and attributes of the current object.

[0062] After obtaining the image feature vector and attributes of the current object, the early warning service module 5 searches for similarity-matching file information in the image database 3 and issues an early warning based on the file information. If a file information matching the face image is found in the image database 3, the module determines whether the current object is a suspicious target based on the file information. If no file information matching the face image is found in the image database 3, the module creates a file information for the current object in the image database 3 and analyzes the attributes of the current object based on the face image; based on the analyzed attributes of the current object, the module determines whether the current object is a suspicious target.

[0063] If the early warning service module 5 determines that the current object is a suspicious target, the early warning service module 5 triggers the early warning process: sending an early warning message to the user terminal 6 to remind the user terminal 6 that there is a suspicious target in the target location and the identity information of the suspicious target needs to be reported to the management platform 7.

[0064] User terminal 6 pops up a warning message. The warning message is used to indicate that there is a suspicious target in the target location. The identity information of the suspicious target needs to be reported to the management platform 7.

[0065] User terminal 6 initiates a first access request to the early warning service module 5 to query the trajectory information corresponding to the suspicious target. User terminal 6 receives the trajectory information of the suspicious target returned by the early warning service module 5, determines the current location of the suspicious target based on the trajectory information, and prompts the user to urge the suspicious target to report its identity information to the management platform 7 by scanning a QR code.

[0066] The early warning service module 5 responds to the identity registration information corresponding to the suspicious target returned by the management platform 7, and updates the status of the early warning process based on the identity registration information. The status of the early warning process includes rejecting or allowing the suspicious target to pass.

[0067] In one embodiment, Figure 3 A flowchart of a video surveillance method is provided, illustrating how this method can be applied to... Figure 1 or Figure 2 Taking the early warning service module 5 shown as an example, it includes the following steps:

[0068] Step S101: Obtain a face image collected from the target location.

[0069] When a person passes through the monitoring area of ​​monitoring device 1, monitoring device 1 captures a facial image of the person passing by. Monitoring device 1 analyzes the facial image, generates capture information, and transmits the capture information to the view library 2 via the video link private network. The view library 2 then transmits the capture information to the early warning service module 5.

[0070] Step S102: Query the image archive 3 for archive information that matches the face image.

[0071] The early warning service module 5 calls the image analysis service module 4 to parse the captured information, obtain the face image, and extract the image feature vector and attributes of the current object. After obtaining the image feature vector and attributes of the current object, the early warning service module 5 searches for file information that matches the similarity score through the image archive 3. Specifically, the image analysis service module 4 extracts the first image feature vector from the face image; compares the first image feature vector with the second image feature vector stored in the image archive 3 to determine the second image feature vector with the highest similarity; obtains the file information corresponding to the second image feature vector with the highest similarity, and uses this file information as the file information that matches the face image.

[0072] Step S103: If file information matching the face image is found in the image file database 3, then determine whether the current object belongs to a suspicious target based on the file information.

[0073] The early warning service module 5 determines whether the file information carries a target attribute identifier; if it determines that the file information carries a target attribute identifier, then the current object is determined to be a suspicious target. The target attribute identifier can be a minor identifier.

[0074] Step S104: If the current object is determined to be a suspicious target based on the file information, an early warning process is triggered. The early warning process includes the following steps S105 and S106:

[0075] Step S105: Send a warning message to user terminal 6 to remind user terminal 6 that there is a suspicious target in the target location and the identity information of the suspicious target needs to be reported to the management platform 7.

[0076] Step S106: In response to the identity registration information corresponding to the suspicious target returned by the management platform 7, update the status of the early warning process according to the identity registration information. The status of the early warning process includes rejecting or allowing the suspicious target to pass.

[0077] Specifically, when reporting the identity information of a suspicious target to the management platform 7, the user terminal 6 can scan a QR code and fill in the identity information of the suspicious target, or the terminal device held by the suspicious target can scan the QR code to achieve identity authentication. This embodiment does not impose any restrictions. The QR code refers to a dedicated graphic code provided by the management department for personal scanning for identity authentication and registration.

[0078] In this embodiment, for target locations, especially scenarios requiring large-scale deployment of monitoring equipment for early warning systems, the early warning service module 5, in conjunction with the image archive 3, performs suspicious target identification, avoiding direct queries to the management platform 7 and reducing the access pressure on the management platform 7. Furthermore, after identifying a suspicious target, the early warning service module 5 triggers an early warning process, linking the user terminal 6 and the management platform 7 to control the suspicious target, improving the timeliness of management.

[0079] In some embodiments, before sending warning information to the user terminal 6, the warning service module 5 acquires video frame images corresponding to the suspicious target collected by multiple monitoring devices 1 at different times in the target location; generates trajectory information corresponding to the suspicious target based on the video frame images collected by multiple monitoring devices 1 at different times in the target location; and stores the trajectory information in the image archive 3. This configuration facilitates locating the suspicious target after it has been identified.

[0080] After the early warning service module 5 sends the early warning information to the user terminal 6, in response to the first access request initiated by the user terminal 6, the early warning service module 5 sends the trajectory information corresponding to the suspicious target to the user terminal 6. Specifically, based on the first access request, the early warning service module 5 initiates a second access request to the image archive 3 to query the trajectory information of the suspicious target. In response to the trajectory information of the suspicious target returned by the image archive 3, the early warning service module 5 sends the trajectory information of the suspicious target to the user terminal 6.

[0081] In some embodiments, in step S103 above, if it is determined that the file information does not carry an attribute identifier, the early warning service module 5 initiates a third access request to the management platform 7 to query the attribute identifier of the current object. Upon receiving the attribute identifier of the current object returned by the management platform 7, the early warning service module 5 updates the attribute identifier of the current object in the image archive 3. With this configuration, after a preliminary file is created for an object in the image archive 3, only a few asynchronous queries to the management platform 7 are needed to complete the file information of that object, thus improving the accuracy of the file information.

[0082] In some embodiments, in step S102 above, if no matching profile information is found in the image archive 3, the early warning service module 5 creates profile information for the current object in the image archive 3 and analyzes the attributes of the current object based on the face image; based on the analyzed attributes of the current object, it determines whether the current object is a suspicious target. Further, the early warning service module 5 initiates a third access request to the management platform 7 to query the attribute identifier of the current object. Upon receiving the attribute identifier of the current object returned by the management platform 7, the early warning service module 5 updates the attribute identifier of the current object in the image archive 3.

[0083] In one embodiment, Figure 4 A flowchart illustrating another video surveillance method is provided, applicable to... Figure 2 The user terminal 6 shown is connected to the early warning service module 5. When the early warning service module 5 triggers the early warning process according to any of the above embodiments, the method includes:

[0084] Step S201: User terminal 6 pops up a warning message. The warning message is used to indicate that there is a suspicious target in the target location and the identity information of the suspicious target needs to be reported to the management platform 7.

[0085] Step S202: Initiate a first access request to the early warning service module 5 to query the trajectory information corresponding to the suspicious target;

[0086] Step S203: Receive trajectory information of suspicious targets returned by the early warning service module 5, determine the current location of the suspicious targets based on the trajectory information of the suspicious targets, and prompt the user to urge the suspicious targets to report their identity information to the management platform 7 by scanning the QR code;

[0087] In step S204, the management platform 7 returns the identity registration information corresponding to the suspicious target to the early warning service module 5. After the early warning service module 5 updates the status of the early warning process based on the identity registration information, the user terminal 6 displays the current status of the early warning process, which includes rejecting or allowing the suspicious target to pass.

[0088] In this embodiment, for target locations, especially scenarios requiring large-scale deployment of monitoring equipment for early warning systems, the early warning service module 5, in conjunction with the image archive 3, performs suspicious target identification, avoiding direct queries to the management platform 7 and reducing the access pressure on the management platform 7. Furthermore, after identifying a suspicious target, the early warning service module 5 triggers an early warning process, linking the user terminal 6 and the management platform 7 to control the suspicious target, improving the timeliness of management.

[0089] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0090] In one embodiment, Figure 5-1 and Figure 5-2 Together, they provide a schematic diagram of the operation process of a video surveillance system, combined with... Figure 5-1 and Figure 5-2 Running in this method Figure 2 Taking the video surveillance system shown as an example, the steps are as follows:

[0091] Step 1: When a person passes through the monitoring area of ​​monitoring device 1, the monitoring device captures a facial image of the person passing by. Monitoring device 1 analyzes the facial image, generates capture information, and transmits the capture information to the view library 2 via the video link private network. The view library 2 then transmits the capture information to the early warning service module 5.

[0092] Step 2: The early warning service module 5 calls the image analysis service module 4 to parse the captured information, obtain the face image, and extract the image feature vector and attributes of the current object. The attributes can be the age range.

[0093] Step 3: After obtaining the image feature vector and attributes of the current object, the early warning service module 5 searches for archive information that matches the similarity score through the image archive library 3.

[0094] Step 4: Image archive 3 queries for archive information that matches the similarity score. If no matching archive information is found, a new archive is created and the currently received face image is saved. If matching archive information is found, the currently received face image is saved and the archive information is returned.

[0095] Step 5: The early warning service module 5 determines whether the current object is a suspicious target based on the file information. Specifically, the early warning service module 5 determines whether the file information carries an attribute identifier. If so, it further determines whether the attribute identifier is a target attribute identifier (e.g., a minor identifier). If so, the early warning process is triggered; otherwise, the process ends. If the early warning service module 5 determines that the file information does not carry an attribute identifier, it initiates a third access request to the management platform 7 to query the attribute identifier of the current object. After the management platform 7 asynchronously returns the attribute identifier of the current object, it updates the attribute identifier of the current object in the image file library 3. Further, the early warning service module 5 determines whether the attributes obtained from the image analysis service module 4 meet the target attributes. If so, the early warning process is triggered; otherwise, the process ends.

[0096] Step 6: Trigger the alert process. Specifically, create a work order for the alert process and send the alert information to the user terminal 6.

[0097] Step 7: A pop-up window on user terminal 6 displays a warning message for the person in charge of the target location to view. The person in charge of the target location operates user terminal 6 to initiate a first access request to the warning service module 5 to obtain the trajectory information of the suspicious target.

[0098] Step 8: The early warning service module 5 initiates a second access request to the image archive 3 to query the file details of the suspicious target.

[0099] Step 9: Image archive 3 returns the file details of suspicious targets to the early warning service module 5.

[0100] Step 10: The early warning service module 5 returns the trajectory information of the suspicious target to the user terminal 6 based on the file details of the suspicious target.

[0101] Step 11: User terminal 6 displays the trajectory information of the suspicious target. The person in charge of the target location locates the suspicious target based on this trajectory information and urges them to scan the code for authentication.

[0102] Step 12: Suspicious targets scan the QR code for authentication in order to register on the management platform 7.

[0103] Step 13: After the management platform 7 completes the filing, it returns the filing status to the early warning service module 5.

[0104] Step 14: The early warning service module 5 updates the work order status based on the filing status returned by the management platform 7: rejected or allowed.

[0105] Step 15: The person in charge of the target site checks the work order status and determines whether to remove the suspicious target.

[0106] In this embodiment, for target locations, especially scenarios requiring large-scale deployment of monitoring equipment for early warning systems, the early warning service module 5, in conjunction with the image archive 3, performs suspicious target identification, avoiding direct queries to the management platform 7 and reducing the access pressure on the management platform 7. Furthermore, after identifying a suspicious target, the early warning service module 5 triggers an early warning process, linking the user terminal 6 and the management platform 7 to control the suspicious target, improving the timeliness of management.

[0107] In one embodiment, an electronic device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 6 As shown, the electronic device includes a processor, memory, communication interface, display screen, and input device connected via a system bus. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage medium. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, NFC (Near Field Communication), or other technologies. When the computer program is executed by the processor, it implements a video surveillance method. The display screen can be an LCD screen or an e-ink screen. The input device can be a touch layer covering the display screen, buttons, a trackball, or a touchpad mounted on the device's casing, or an external keyboard, touchpad, or mouse.

[0108] Those skilled in the art will understand that Figure 6 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the electronic device to which the present application is applied. The specific electronic device may include more or fewer components than shown in the figure, or combine certain components, or have different component arrangements.

[0109] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0110] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0111] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0112] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A video surveillance method, characterized in that, Applied to the early warning service module, the method includes: Acquire facial images from the target location; Search the image archive for file information that matches the face image; If file information matching the face image is found in the image archive, it is determined whether the current object is a suspicious target based on the file information. If the current object is determined to be a suspicious target based on the file information, an early warning process is triggered, which includes: Send a warning message to the user terminal to remind the user terminal that there is a suspicious target in the target location and that the identity information of the suspicious target needs to be reported to the management platform; In response to the identity registration information corresponding to the suspicious target returned by the management platform, the status of the early warning process is updated according to the identity registration information. The status of the early warning process includes rejecting or allowing the suspicious target to pass.

2. The video surveillance method according to claim 1, characterized in that, After sending the warning information to the user terminal, the method further includes: In response to the first access request initiated by the user terminal, trajectory information corresponding to the suspicious target is sent to the user terminal.

3. The video surveillance method according to claim 2, characterized in that, In response to a first access request initiated by the user terminal, trajectory information corresponding to the suspicious target is sent to the user terminal, including: Based on the first access request, a second access request is initiated to the image archive to query the trajectory information of the suspicious target; In response to the trajectory information of the suspicious target returned by the image archive, the trajectory information of the suspicious target is sent to the user terminal.

4. The video surveillance method according to claim 2, characterized in that, Before sending the warning information to the user terminal, the method further includes: Acquire video frame images corresponding to the suspicious target, collected at different times by multiple monitoring devices in the target location; Based on video frame images collected at different times by multiple monitoring devices in the target location, trajectory information corresponding to the suspicious target is generated; The trajectory information is stored in the image archive.

5. The video surveillance method according to claim 1, characterized in that, Determining whether the current object is a suspicious target based on the aforementioned file information includes: Determine whether the file information carries a target attribute identifier; If the file information is determined to carry the target attribute identifier, then the current object is determined to be a suspicious target.

6. The video surveillance method according to claim 5, characterized in that, The method further includes: If it is determined that the file information does not carry an attribute identifier, a third access request is initiated to the management platform to query the attribute identifier of the current object and update the attribute identifier of the current object in the image archive.

7. The video surveillance method according to claim 1, characterized in that, The method further includes: If no matching profile information is found in the image database, profile information for the current object is created in the image database, and the attributes of the current object are analyzed based on the face image. Based on the attributes of the current object obtained from the analysis, determine whether the current object belongs to a suspicious target.

8. A video surveillance method, characterized in that, It is applied to a user terminal, which is connected to an early warning service module. When the method according to any one of claims 1 to 7 triggers the early warning process, the method includes: The user terminal pop-up warning information is used to indicate that there is a suspicious target in the target location, and the identity information of the suspicious target needs to be reported to the management platform; Initiate a first access request to the early warning service module to query the trajectory information corresponding to the suspicious target; The system receives the trajectory information of the suspicious target returned by the early warning service module, determines the current location of the suspicious target based on the trajectory information, and prompts the user to urge the suspicious target to report its identity information to the management platform by scanning a QR code. After the management platform returns the identity registration information corresponding to the suspicious target to the early warning service module, and the early warning service module updates the status of the early warning process based on the identity registration information, the user terminal displays the current status of the early warning process. The status of the early warning process includes rejecting or allowing the suspicious target to pass.

9. A video surveillance system, characterized in that, include: The system includes monitoring equipment, a view library, an image archive library, an image analysis service module, and an early warning service module. The monitoring equipment is connected to the view library, and the view library, the image archive library, and the image analysis service module are each connected to the early warning service module. The monitoring equipment is used to collect image data and upload the image data to the view library; The view library is used to store the image data and upload the image data to the early warning service module; The image archive is used to store the archive information of objects; The image analysis service module is used to analyze the image data and extract image feature vectors and attributes corresponding to the current object; The early warning service module implements the video surveillance method according to any one of claims 1 to 7 by calling the view library, the image archive library, and the image analysis service module.

10. An electronic device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 8.

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