Scenic spot missing person searching method and device, electronic equipment and medium

Abstract

This application discloses a method, device, electronic device, and storage medium for finding people in scenic areas, including: acquiring the facial features of a target object and initial capture information within the scenic area; the initial capture information includes images captured by various monitoring points within the scenic area, along with corresponding capture points and capture times; combining the scenic area's geographic information database, determining the target object's movement trajectory and attraction stop information within the scenic area during a first time period based on the facial features and initial capture information; the movement trajectory and attraction stop information are obtained based on video data collected from various monitoring points within the scenic area and the scenic area's geographic information; combining real-time visitor density data within the scenic area, determining the target object's search area and search priority for each area during a second time period based on the movement trajectory and attraction stop information.

Description

Technical Field

[0001] This application relates to the field of data processing technology, specifically to a method, device, electronic device, and storage medium for finding people in scenic areas. Background Technology

[0002] In various scenic areas, especially large 5A-level scenic areas, mountain scenic areas, and theme park scenic areas, the vast geographical area, scattered attractions, complex geographical environment, and crisscrossing trail networks, coupled with dense crowds during holidays, make it extremely easy for elderly people, children, and people with mobility impairments to get separated from their companions. Current search technologies often rely on communication devices carried by missing persons or on extensive, indiscriminate manual searches by scenic area staff. The former requires the active cooperation of the missing person and is completely ineffective for those who do not carry communication devices, do not know how to use them, or are unable to make contact. The latter, due to the large area of ​​the scenic area and the lack of clear search areas and priorities, results in extremely low search efficiency, often failing to find missing persons in a timely manner and potentially causing safety hazards due to delayed searches. Furthermore, the uneven distribution of visitor density, varying visitor routes, and numerous surrounding transportation hubs in scenic areas further increase the difficulty of traditional search methods, making it difficult to meet the actual needs of efficient and accurate search for missing persons in scenic areas. Summary of the Invention

[0003] This application provides a method, electronic device, apparatus, and storage medium for finding missing persons in scenic areas. It can combine scenic area geographic information and real-time visitor density data to accurately determine the search area and search priority for missing persons, greatly improving the efficiency of finding missing persons in scenic areas and solving the technical problems of traditional methods that rely on cooperation and blind searching.

[0004] Firstly, embodiments of this application provide a method for finding people in scenic areas, including: Acquire the facial features of the target object and its initial capture information within the scenic area; the initial capture information includes images captured by each monitoring point within the scenic area, along with the corresponding capture point and capture time; By combining the scenic area's geographic information database, and based on the facial features and initial capture information of the target object, the movement trajectory and attraction stop information of the target object within the scenic area during the first time period are determined; the movement trajectory and attraction stop information are obtained based on video data collected from various monitoring points within the scenic area and the scenic area's geographic information; Based on real-time visitor density data of the scenic area, and according to the movement trajectory and attraction stay information, the scenic area search area and search priority of each area for the target object are determined in the second time period.

[0005] Optionally, in some embodiments of this application, the start time of the second time period is not earlier than the start time of the first time period, and the end time of the second time period is later than the end time of the first time period. The second time period includes the scenic area search period after the target object loses contact.

[0006] Optionally, in some embodiments of this application, obtaining the facial features of the target object and the initial capture information within the scenic area includes: Obtain the facial image of the target object and extract facial features; The facial features of the target object are matched with the captured images in the scenic area's image database based on feature similarity. The scenic area's image database includes multiple images taken by various monitoring points within the scenic area, along with their corresponding shooting locations and shooting times. The captured images and corresponding information in the scenic area's image database that match the facial features of the target object are determined as the initial capture information for the target object.

[0007] Optionally, in some embodiments of this application, obtaining the facial features of the target object and the initial capture information within the scenic area includes: Obtain the facial image of the target object and extract facial features; The facial features of the target object are matched with the captured images in the scenic area image database to determine the feature similarity and at least one captured image that meets the similarity condition, along with the corresponding shooting location and shooting time. The scenic area image database includes multiple images taken by various monitoring points within the scenic area and their corresponding information. In response to a specified operation that selects a set of information from the at least one captured image and corresponding information, the specified captured image and corresponding shooting point and shooting time are determined as the initial capture information of the target object.

[0008] Optionally, in some embodiments of this application, obtaining the face image of the target object and extracting facial features includes: Receive the facial image of the target object provided by the user seeking people and extract facial features; Alternatively, based on the object identifier of the target object, obtain the face image corresponding to the object identifier from the scenic area's tourist face database and extract the face features; the scenic area's tourist face database pre-stores at least one face image collected when tourists enter the park or purchase tickets.

[0009] Optionally, in some embodiments of this application, the step of combining the scenic area geographic information database and determining the movement trajectory and attraction stay information of the target object within the scenic area during the first time period based on the facial features and initial capture information of the target object includes: Based on the facial features and initial capture information of the target object, the movement trajectory and attraction stay information corresponding to the target object are obtained from the scenic area trajectory feature database; the scenic area trajectory feature database includes the movement trajectory, attraction stay information and association information with monitoring points of each active object in the scenic area.

[0010] Optionally, in some embodiments of this application, before obtaining the movement trajectory and attraction stay information corresponding to the target object from the scenic area trajectory feature database, the method further includes: Acquire video data collected from each monitoring point within the scenic area and geographic information from the scenic area's geographic information database; Based on the collected video data and scenic area geographic information, the movement trajectory and attraction stay information of at least one active object in the scenic area are determined and stored in the scenic area trajectory feature database after being associated with the corresponding monitoring point information; the at least one active object includes the target object.

[0011] Optionally, in some embodiments of this application, the step of combining the scenic area geographic information database and determining the movement trajectory and attraction stay information of the target object within the scenic area during the first time period based on the facial features and initial capture information of the target object includes: Acquire video data collected from each monitoring point within the scenic area and geographic information from the scenic area's geographic information database; Based on the collected video data and scenic area geographic information, and according to the facial features and initial capture information of the target object, the movement trajectory and attraction stay information of the target object within the scenic area during the first time period are determined.

[0012] Optionally, in some embodiments of this application, the step of combining real-time visitor density data of the scenic area and determining the scenic area search area and search priority of each area for the target object in the second time period based on the movement trajectory and attraction stay information includes: Determine at least a portion of the complete movement trajectory and attraction stay information of the target object within the scenic area, wherein the at least a portion of the information includes the location of the target object at the end time of the first time period and the last attraction stay information; By combining real-time visitor density data and trail network information of the scenic area, and based on at least some of the information, the scenic area search area for the target object and the search priority of each area are determined in the second time period.

[0013] Optionally, in some embodiments of this application, the step of combining real-time visitor density data of the scenic area and determining the scenic area search area and search priority of each area for the target object in the second time period based on the movement trajectory and attraction stay information includes: Obtain the historical visit data of the target scenic area; By combining real-time visitor density data of the scenic area, and based on the historical visit data of the scenic area and the movement trajectory and attraction stay information of the target object in the first time period, the search area of ​​the target object in the scenic area and the search priority of each area are determined.

[0014] Secondly, embodiments of this application provide a scenic area missing person locator, comprising: The acquisition module is used to acquire the facial features of the target object and the initial capture information within the scenic area; the initial capture information includes images captured by each monitoring point within the scenic area and the corresponding shooting point and shooting time. The first determining module is used to combine the scenic area's geographic information database and, based on the facial features and initial capture information of the target object, determine the target object's movement trajectory and attraction stop information within the scenic area during a first time period; the movement trajectory and attraction stop information are obtained based on video data collected from various monitoring points within the scenic area and the scenic area's geographic information; The second determining module is used to combine real-time visitor density data of the scenic area with the movement trajectory and the information on the place of stay at the attractions to determine the scenic area search area and the search priority of each area for the target object in the second time period.

[0015] Accordingly, this application also provides an electronic device, including a memory, a processor, and a processor program stored in the memory and executable on the processor, wherein the processor executes the program as described in any of the methods above.

[0016] This application also provides a storage medium storing a processor program that, when executed by a processor, implements any of the methods described above.

[0017] This application provides a method, device, electronic device, and storage medium for finding missing persons in scenic areas. It can acquire facial features and initial snapshot information of missing persons within the scenic area, combine this with a scenic area geographic information database to determine the missing person's movement trajectory and location information at various attractions, and further combine this with real-time visitor density data to determine the search area and priority after the person goes missing. Scenic area staff can conduct targeted searches based on the determined search area and priority, significantly improving search efficiency and accuracy. This method does not rely on the active cooperation of the missing person or their communication devices. It achieves accurate searching solely through video data collected by monitoring equipment within the scenic area, combined with unique data such as scenic area geographic information and real-time visitor flow data. This allows for timely retrieval of missing persons and reduces safety risks during the search process. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a flowchart illustrating the method for finding missing persons in scenic areas provided in this application embodiment; Figure 2 This is a schematic diagram of the structure of the scenic area missing person search device provided in the embodiments of this application; Figure 3 This is a schematic diagram of the structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0020] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0021] In the description of this application, it should be understood that the terms "center," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," and "outer," etc., indicating orientation or positional relationships based on the orientation or positional relationships shown in the accompanying drawings, are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of this application. Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined with "first" or "second" may explicitly or implicitly include one or more of the stated features. In the description of this application, "a plurality of" means two or more, unless otherwise explicitly specified.

[0022] In this application, the term "exemplary" is used to mean "serving as an example, illustration, or description." Any embodiment described as "exemplary" in this application is not necessarily to be construed as being more preferred or advantageous than other embodiments. The following description is provided to enable any person skilled in the art to make and use this application. Details are set forth in the following description for purposes of explanation. It should be understood that those skilled in the art will recognize that this application can be made without using these specific details. In other instances, well-known structures and processes are not described in detail to avoid obscuring the description of this application with unnecessary detail. Therefore, this application is not intended to be limited to the embodiments shown, but is consistent with the broadest scope of the principles and features disclosed in this application.

[0023] This application provides a method, device, server, and computer-readable storage medium for finding people in scenic areas, which will be described in detail below.

[0024] In this embodiment of the scenic area search method, a scenic area search device is used as the execution subject. For simplicity and ease of description, this execution subject will be omitted in subsequent method embodiments. The scenic area search device is applied to a server. The method includes: acquiring the facial features of the target object and initial capture information within the scenic area; combining the scenic area geographic information database, determining the movement trajectory and attraction stay information of the target object within the scenic area during a first time period based on the facial features and initial capture information of the target object; combining the real-time visitor density data of the scenic area, determining the scenic area search area of ​​the target object and the search priority of each area during a second time period based on the movement trajectory and attraction stay information.

[0025] This application provides a method for finding missing persons in scenic areas, which can be executed by an electronic device or a server. This application example illustrates a method for finding missing persons in scenic areas executed by an electronic device. The electronic device includes a touchscreen display and a processor. The touchscreen display is used to present a graphical user interface (GUI) and receive operation commands generated by the user interacting with the GUI. When the user operates the GUI through the touchscreen display, the GUI can control the content locally on the electronic device in response to the received operation commands, or it can control the content on the server side in response to the received operation commands.

[0026] The scenic area missing person search solution provided in this application can acquire facial features and initial snapshot information of missing persons within the scenic area. Combined with the scenic area's geographic information database, it determines the missing person's movement trajectory and location information before disappearance. Furthermore, it uses real-time visitor density data to determine the search area and priority after the person goes missing. Scenic area staff can then conduct targeted searches based on the determined search areas and priorities, significantly improving search efficiency and accuracy. This method does not rely on the active cooperation of the missing person or their communication devices. It achieves accurate missing person search solely through video data collected by monitoring equipment within the scenic area, combined with unique data such as scenic area geographic information and real-time visitor flow data. This allows for timely retrieval of missing persons and reduces safety risks during the search process.

[0027] The following sections provide detailed descriptions of each example. It should be noted that the order in which the embodiments are described is not intended to limit the priority of the embodiments.

[0028] A method for finding people in a scenic area includes: acquiring the facial features of the target person and initial snapshot information within the scenic area; combining the scenic area's geographic information database, determining the target person's movement trajectory and attraction stop information within the scenic area during a first time period based on the facial features and initial snapshot information; and combining real-time visitor density data of the scenic area, determining the target person's search area and search priority for each area during a second time period based on the movement trajectory and attraction stop information.

[0029] In various scenic areas, especially mountainous, lakeside, and large-scale theme parks, the large area, wide distribution of attractions, and crisscrossing trails, coupled with the large number of tourists and rapid population movement during holidays, frequently lead to situations where people get lost and require search and rescue within the scenic area. For example, in national forest parks, large cultural and tourism scenic areas, and seaside resorts, elderly people and children frequently get lost because they cannot keep up with their companions or are attracted by the attractions and stray from the group, making it imperative for scenic areas to provide efficient missing person search services.

[0030] In related technologies, there are two main methods for finding missing persons in scenic areas: one is to contact the missing person using their mobile phone, smartwatch, or other communication devices to arrange a meeting point; the other is for scenic area staff to conduct manual patrols and searches within the scenic area based on the description provided by the person searching. The first method requires the cooperation of the missing person, and it is completely ineffective for children, the elderly, or those who are too nervous or lost to use communication devices. The second method is problematic because scenic areas are large and lack clearly defined search areas, forcing staff to conduct a general, indiscriminate search, which is not only extremely inefficient but also consumes a lot of manpower. If the missing person enters secluded trails or forested areas within the scenic area, there is a risk of accidents such as falling off cliffs or into water due to delayed searches.

[0031] Therefore, there is a need for a method for finding missing persons in scenic areas that does not rely on the active cooperation of the missing persons and can accurately determine the search area and priority based on the characteristics of the scenic area itself, so as to find the missing persons more efficiently and accurately.

[0032] Due to the needs of scenic area security monitoring, visitor flow statistics, and tour management, a large number of monitoring devices are typically deployed in various scenic areas. These monitoring points cover major attractions, trail intersections, rest areas, entrances and exits, and other areas, collecting video and image data in real time. Simultaneously, scenic areas usually possess comprehensive geographic information data and can obtain real-time visitor density data for each area through visitor flow statistics equipment. Based on this, this application provides a method for finding missing persons in scenic areas. By acquiring the facial features and initial snapshot information of the target object, and combining this with the scenic area's geographic information database, the method determines the target object's movement trajectory and visitor information within a first time period. Then, by combining this with the scenic area's real-time visitor density data, the method determines the search area and search priority within a second time period. Scenic area staff can then conduct targeted searches based on these results to find the missing target object more quickly.

[0033] To make the methods for finding missing persons in scenic areas provided in this disclosure clearer, the implementation process of the solution provided in this disclosure will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0034] Referring to Figure 1, Figure 1 is a flowchart illustrating a method for finding missing persons in a scenic area, as provided in this disclosure. This method can be applied to intelligent management systems in scenic areas, such as operational command systems and smart tourism platforms. As shown in Figure 1, the process includes: Step S101: Obtain the facial features of the target object and the initial capture information within the scenic area; the initial capture information includes images captured by each monitoring point within the scenic area and the corresponding shooting location and shooting time.

[0035] The scenic areas in this disclosure are various tourist places available for tourists to visit and relax, including natural scenic areas (such as mountain scenic areas, forest scenic areas, river and lake scenic areas), cultural scenic areas (such as ancient town scenic areas, cultural relic scenic areas), theme scenic areas (such as amusement scenic areas, health care scenic areas), etc. Such scenic areas usually have the characteristics of a wide geographical scope, complex geographical environment, and scattered scenic spots.

[0036] The target object is a missing person who needs to be found after getting lost in the scenic area, including the elderly, children, disabled people, tourists, etc., and is the core object of the missing person search service in this disclosure; the missing person search user is a person who actively seeks the missing person search service in the scenic area, usually a peer relative, friend, etc. of the missing person.

[0037] The monitoring devices in the scenic area are deployed at each key position according to preset rules, including the core area of the scenic spot, the intersection of the footpaths, the rest area, the entrance and exit of the scenic area, the parking lot, etc., to achieve video monitoring coverage of the main areas of the scenic area. The monitoring devices can capture the tourists moving in the scenic area in real time, obtain the captured images, and after associating the captured images with the shooting points and shooting times, store them in the scenic area captured image library. The shooting rules can be set according to the needs of the scenic area. For example, the monitoring device automatically shoots when detecting a frontal face, or shoots the images of the monitoring area at fixed time intervals (such as 5 seconds, 10 seconds). This disclosure does not limit this.

[0038] The face feature is the unique feature of the target object's face, obtained by extracting the features of the face image, and can be used to accurately match the relevant images in the scenic area captured image library; the initial capture information is the basic information of the target object captured by the monitoring device in the scenic area, including the captured image, the shooting point (such as the monitoring at the east entrance of XX scenic spot, the 3rd monitoring of XX footpath), and the shooting time, which is the basis for determining the activity track of the target object later.

[0039] This step needs to locate the relevant capture information of the target object in the scenic area captured image library, and the core is achieved through the similarity matching of face features. Specifically, it can be divided into two methods: automatic matching and manual designation, both of which can be completed by the scenic area intelligent management system. The missing person search user only needs to provide the basic face image or object identifier.

[0040] Exemplarily, for the parent looking for a lost child, they can provide the child's life photo to the scenic area staff. After the scenic area intelligent management system extracts the face features of the life photo, it performs feature matching with all the captured images in the scenic area captured image library, and automatically obtains the captured images that match successfully and the corresponding shooting points and shooting times as the initial capture information; if multiple captured images with relatively high similarity are obtained, the system can display these multiple images to the parent, and the parent can specify the captured image of the child from them to determine the final initial capture information.

[0041] Step S102: Combining the scenic area geographic information database, based on the facial features of the target object and the initial capture information, determine the movement trajectory and attraction stay information of the target object within the scenic area during the first time period; the movement trajectory and attraction stay information are obtained based on video data collected from various monitoring points within the scenic area and the scenic area geographic information.

[0042] The scenic area geographic information database is a pre-constructed collection of scenic area geographic information, including the location coordinates of all attractions within the scenic area, the direction and distance of the trail network, the distribution of rest areas, the deployment location of monitoring points, the coordinates of the scenic area entrances and exits, as well as geographic information such as transportation hubs and parking lots around the scenic area. It is the geographic basis for reconstructing the actual movement trajectory of the target object.

[0043] The movement trajectory is the actual route taken by the target within the scenic area during the first time period. It is reconstructed by combining the information captured by multiple monitoring points with the geographical information of the scenic area. For example, the movement route is "Children's Park → Flower Sea Trail → Viewing Platform → Pine Forest Rest Area". The trajectory includes the arrival time and departure time of each point. The attraction stay information is the information related to the target's stay at various attractions and rest areas in the scenic area, including the name of the attraction, the duration of the stay, and the time period of the stay. For example, "stayed for 25 minutes on the Flower Sea Trail and 10 minutes on the Viewing Platform".

[0044] The first time period is the period during which the target person was active in the scenic area before losing contact with the user being searched. The end time is the time when the target person lost contact. The start time can be flexibly set according to the shooting time of the initial snapshot information. For example, if the shooting time of the initial snapshot information is 9:00 AM and the time of loss of contact is 10:00 AM, then the first time period can be from 9:00 AM to 10:00 AM. If the target person's activity time in the scenic area is relatively long, the first time period can also be set to 1 hour or 2 hours before losing contact. This disclosure does not limit the length of the first time period.

[0045] In this embodiment, based on video data collected by monitoring equipment in the scenic area, and using basic AI capabilities such as face / body recognition, face / body tracking, and attribute recognition, combined with ReID (Person re-identification) technology, and then matching the geographic information in the scenic area's geographic information database, the actual movement trajectory of the target object in the scenic area during the first time period can be restored, and its stay information at each attraction can be statistically analyzed to obtain complete movement trajectory and attraction stay information.

[0046] In this step, the determination of movement trajectory and attraction stay information can be divided into two methods: one is to directly retrieve it from the pre-built scenic area trajectory feature database. This database stores the trajectory and stay information of all tourists in the scenic area in real time and associates it with the capture information of the target object. After determining the initial capture information, it can be retrieved quickly; the other is to retrieve the surveillance video data in a targeted manner after receiving the missing person request, and calculate the trajectory and stay information of the target object by combining it with geographic information. This method can save the storage resources of the scenic area system and adapt to the usage needs of small and medium-sized scenic areas.

[0047] Step S103: Combining real-time visitor density data of the scenic area, and based on the movement trajectory and attraction stay information, determine the scenic area search area and search priority of each area for the target object in the second time period.

[0048] Real-time visitor density data for scenic areas includes real-time visitor numbers, crowding levels, and visitor trends in various areas. This data is collected in real-time by visitor counting equipment (such as infrared visitor counting instruments and camera visitor counting modules) and uploaded to the scenic area's smart management system. For example, data such as "low visitor density in the viewing platform area (5 people / 100㎡), high visitor density in the popular flower sea area (50 people / 100㎡), and extremely low visitor density on the back mountain trail (1 person / 100㎡)" can be used to describe the visitor density.

[0049] The start time of the second time period is no earlier than the start time of the first time period, and the end time is later than the end time of the first time period. It also includes the period during which the target person went missing. For example, if the first time period is from 9:00 AM to 10:00 AM (the time when the target person went missing), then the second time period can be from 9:00 AM to 10:30 AM or from 10:00 AM to 11:00 AM. The end time of the second time period can be flexibly adjusted according to the search progress in the scenic area to achieve dynamic updates of the search area.

[0050] The search area within the scenic area refers to the areas where the target person may have been active after going missing. This includes attractions, trails, rest areas, entrances and exits within the scenic area, as well as transportation hubs, parking lots, and surrounding businesses. This disclosure includes the areas surrounding the scenic area in the search scope to avoid omissions due to limited search area. Search priority is a level of search based on the likelihood of the target person's activity in each area. For example, the first priority is the area most likely to appear, which should be searched first by scenic area staff; the second priority is the area less likely to appear, which can be searched by staff later; and the third priority is the area with the lowest probability, which can be investigated after the first and second priority areas have been searched without success.

[0051] This step is the core of the scenic area's missing person search method. By combining the target's movement trajectory, information on places visited, and real-time visitor density data, it achieves precise localization of the search area and reasonable prioritization of search areas. Specifically, this can be achieved in two ways: one is to use the target's last location and last place visited before going missing as the core, combined with the direction and distance of the scenic area's trail network and real-time visitor density, to predict the target's possible travel range and prioritize searches accordingly; the other is to further optimize the search area and prioritize searches by combining the target's historical visit data (such as past attraction preferences and travel habits), thereby improving the accuracy of predictions.

[0052] For example, if the target is a child, and the child's last stop in the first time period was the children's playground in the scenic area, the time of disappearance was 10:00 AM, and the last location was the west gate of the children's playground, based on the real-time visitor density data of the scenic area, it can be seen that the visitor density of the parent-child trail around the children's playground is moderate, the visitor density of the suburban trail on the west side is extremely low, and the visitor density of the parking lot at the east gate of the scenic area is moderate. The system can designate the parent-child trail within 500 meters of the west gate of the children's playground as the first-priority search area, the suburban trail as the second-priority search area, and the parking lot at the east gate as the third-priority search area. Scenic area staff can conduct targeted searches according to this priority, greatly improving the efficiency of finding the child.

[0053] Optionally, in some embodiments of this application, obtaining the facial features of the target object and the initial capture information within the scenic area may include the following steps: Step S201: Obtain the face image of the target object and extract its facial features.

[0054] The target object's facial image is an image containing a clear face of the target object, such as a casual photo, ID photo, or a photo taken when entering the park. The facial feature extraction is completed by the scenic area's intelligent management system through a professional facial feature extraction algorithm. The extracted features are unique and can be used for accurate image matching.

[0055] In this step, facial images are obtained in two ways: one is to receive facial images provided by users searching for missing persons, such as parents uploading photos of their children through the scenic area's missing persons terminal or staff members' mobile phones; the other is to retrieve them from the scenic area's visitor facial recognition database based on the target object's identifier. The identifier includes the target object's ID number for ticket purchase, mobile phone number, and facial recognition records for entering the park. The scenic area's visitor facial recognition database pre-stores facial images collected when visitors enter the park or purchase tickets, such as facial images collected simultaneously when visitors purchase tickets with their ID cards or images taken when entering the park by facial recognition.

[0056] Step S202: Perform feature similarity matching between the facial features of the target object and each captured image in the scenic area's image capture library; the scenic area's image capture library includes multiple images taken by various monitoring points within the scenic area, along with their corresponding shooting locations and shooting times.

[0057] The scenic area's image database is the foundational database of the scenic area's intelligent management system. It stores images captured at various monitoring points in real time and associates each image with the capturing location and time, enabling traceability of image information. In this step, the system uses a facial feature similarity matching algorithm to match the facial features of the target object with all images in the image database one by one, calculates the feature similarity value, and filters out images whose similarity value meets a preset threshold.

[0058] Step S203: The captured images and corresponding information in the scenic area image database that match the facial features of the target object are determined as the initial capture information of the target object.

[0059] This step is an automatic matching method. The system directly determines the captured images with similarity values ​​that meet the preset threshold, along with the corresponding shooting location and shooting time, as the initial capture information. No manual intervention is required, which can quickly complete the acquisition of initial information, improve the response speed of the missing person service, and adapt to the scenario of emergency missing person search in scenic areas.

[0060] Optionally, in some embodiments of this application, obtaining the facial features of the target object and the initial capture information within the scenic area may include the following steps: Step S301: Obtain the face image of the target object and extract its facial features.

[0061] The implementation method of this step is exactly the same as that of step S201, and will not be repeated here.

[0062] Step S302: Perform feature similarity matching between the facial features of the target object and each captured image in the scenic area image database, and determine at least one captured image that meets the similarity condition, along with the corresponding shooting location and shooting time; the scenic area image database includes multiple images taken by various monitoring points within the scenic area and their corresponding information.

[0063] In this step, the system first presets similarity conditions, such as feature similarity value ≥80%, and then selects one or more images that meet the requirements from the scenic area image database based on these conditions. At the same time, it retrieves the shooting location and shooting time corresponding to the image to form multiple sets of candidate initial capture information.

[0064] Step S303: In response to the specified operation of specifying a set of information from the at least one captured image and corresponding information, the specified captured image and corresponding shooting point and shooting time are determined as the initial capture information of the target object.

[0065] This step involves manual selection. The system displays multiple sets of candidate initial capture information to the user, who then selects the target image by clicking or choosing. The system then uses the user-selected set of information as the final initial capture information. This method can resolve matching errors caused by similar facial features (such as twins or children with similar appearances), further improving the accuracy of the initial capture information.

[0066] Optionally, in some embodiments of this application, step S102, in conjunction with the scenic area geographic information database, determines the movement trajectory and attraction stay information of the target object within the scenic area during the first time period based on the facial features and initial capture information of the target object. This may include: obtaining the movement trajectory and attraction stay information corresponding to the target object from the scenic area trajectory feature database based on the facial features and initial capture information of the target object; the scenic area trajectory feature database includes the movement trajectory, attraction stay information, and association information with monitoring points of each active object in the scenic area.

[0067] The scenic area trajectory feature database is a dynamic database pre-built by the scenic area's intelligent management system. The system retrieves video data from various monitoring points in real time, combines it with the scenic area's geographic information database to reconstruct the movement trajectories and visitor information for all tourists within the scenic area, and stores this information in the database after associating it with the tourists' captured images and facial features. After determining the initial capture information of the target object, the system can quickly match relevant information in the database using facial features or captured images, directly retrieving the target object's movement trajectory and visitor information without real-time calculation, thus improving the efficiency of trajectory determination.

[0068] Optionally, in some embodiments of this application, before obtaining the movement trajectory and attraction stay information corresponding to the target object from the scenic area trajectory feature database, the method further includes: obtaining video data collected from each monitoring point in the scenic area and geographical information from the scenic area geographic information database; determining the movement trajectory and attraction stay information of at least one active object in the scenic area based on the collected video data and scenic area geographic information, and storing it in the scenic area trajectory feature database after associating it with the corresponding monitoring point information; the at least one active object includes the target object.

[0069] This step involves building and updating the scenic area's trajectory feature database. The system uses AI technology to analyze surveillance video data, combines geographic information to reconstruct tourists' movement trajectories, collect statistics on their stays, and associates the trajectories, stay information, and monitoring point information to achieve real-time database updates, ensuring the accuracy and timeliness of the retrieved trajectory information.

[0070] Optionally, in some embodiments of this application, the step of combining the scenic area geographic information database and determining the target object's movement trajectory and attraction stay information within the scenic area during a first time period based on the target object's facial features and initial capture information includes: acquiring video data collected from each monitoring point within the scenic area and geographic information from the scenic area geographic information database; and determining the target object's movement trajectory and attraction stay information within the scenic area during a first time period based on the acquired video data and scenic area geographic information, according to the target object's facial features and initial capture information.

[0071] This method employs targeted calculation. The system does not pre-store the trajectory information of all tourists within the scenic area. Only upon receiving a missing person request, it retrieves relevant surveillance video data based on the target's facial features and initial snapshot information, combining this data with the scenic area's geographical information to calculate the target's movement trajectory and visitor information separately. This method eliminates the need for extensive storage resources to build a scenic area trajectory feature database, effectively saving storage and computational costs for the scenic area system. It is suitable for small to medium-sized scenic areas and those with a limited number of monitoring points.

[0072] Optionally, in some embodiments of this application, the step of determining the search area and search priority of each area for the target object in the second time period by combining real-time visitor density data of the scenic area and the movement trajectory and attraction stay information includes: determining at least a portion of the target object's complete movement trajectory and attraction stay information in the scenic area, wherein the at least a portion of the information includes the target object's location at the end time of the first time period and the last attraction information; and determining the search area and search priority of each area for the target object in the second time period by combining real-time visitor density data of the scenic area and scenic area trail network information, based on the at least a portion of the information.

[0073] Complete movement trajectory and attraction stop information encompasses the target's entire activity trajectory and stops from entering the scenic area until the moment they went missing. In this step, it's not necessary to use the complete information; only the core information—the location at the moment of disappearance and the last attraction visited—is extracted to pre-determine the search area. Using this core information as the center, the system combines the orientation of the scenic area's trail network and the distance between each trail to define the area the target could have reached after going missing. Then, by combining this with the real-time visitor density of each area, the system determines the target's possible activity areas. For example, children typically avoid crowded areas with high visitor density and tend to enter trails and attractions with moderate or low visitor density; the system can prioritize searches based on this pattern.

[0074] Optionally, in some embodiments of this application, the step of determining the scenic area search area and search priority of each area for the target object in the second time period by combining real-time visitor density data of the scenic area and based on the movement trajectory and attraction stay information includes: obtaining the target object's historical visit data of the scenic area; and determining the scenic area search area and search priority of each area for the target object by combining real-time visitor density data of the scenic area and based on the historical visit data of the scenic area and the movement trajectory and attraction stay information of the target object in the first time period.

[0075] Historical visitor data for scenic areas refers to relevant data from the target individual's past visits to the area, including attraction preferences (such as a fondness for children's playgrounds and flower fields), travel routes (such as a preference for lakeside trails and mountain trails), and dwell habits (such as a preference for spending extended periods in rest areas). This data can be obtained from the scenic area's visitor records and user data from the smart tourism platform. Combining historical visitor data with actual visitor data allows for further prediction of the target individual's direction of travel after they go missing. For example, if the target individual has visited the scenic area multiple times and consistently visits the petting zoo, and their initial movement trajectory shows them heading towards the petting zoo, the system can designate the petting zoo as a first-priority search area. After optimization using real-time visitor density data, the final search area and priority are determined.

[0076] In this embodiment, the scenic area search method does not rely on the active cooperation of the target person or their communication devices. It relies solely on video data collected by surveillance equipment installed within the scenic area, combined with unique data such as the scenic area's geographic information database and real-time visitor density data, to accurately determine the search area and priority for the target person. Scenic area staff can then conduct targeted and prioritized searches based on these results, significantly improving search efficiency and accuracy. This enables the timely retrieval of lost individuals, reduces safety risks during the search process, and conserves the scenic area's manpower resources.

[0077] To facilitate better implementation of the scenic area search method of this application embodiment, this application embodiment also provides a scenic area search device, wherein the meanings of the terms are the same as those in the scenic area search method described above, and specific implementation details can be found in the description of the system embodiment.

[0078] Please see Figure 2 , Figure 2 The diagram below illustrates the structure of a scenic area missing person search device provided in this embodiment. Specifically, the device may include an acquisition module 201, a first determination module 202, and a second determination module 203, as follows: The acquisition module 201 is used to acquire the facial features of the target object and the initial capture information in the scenic area; the initial capture information includes images captured by each monitoring point in the scenic area and the corresponding shooting point and shooting time. The first determining module 202 is used to combine the scenic area geographic information database and determine the movement trajectory and attraction stay information of the target object within the scenic area during the first time period based on the facial features and initial capture information of the target object; the movement trajectory and attraction stay information are obtained based on video data collected from each monitoring point in the scenic area and the scenic area geographic information. The second determining module 203 is used to combine real-time visitor density data of the scenic area with the movement trajectory and the information on the place of stay at the scenic spot to determine the scenic area search area and the search priority of each area for the target object in the second time period.

[0079] This application provides a device for finding missing persons in scenic areas. It can acquire facial features and initial snapshot information of lost individuals within the scenic area, combine this with a geographic information database of the scenic area to determine the individual's movement trajectory and stops at various attractions before disappearing, and then combine this with real-time visitor density data to determine the search area and priority after the disappearance. Scenic area staff can conduct targeted searches based on the determined search area and priority, significantly improving search efficiency and accuracy. This method of finding missing persons in scenic areas does not rely on the active cooperation of the individual or on their communication devices. It achieves accurate searching solely through video data collected by monitoring equipment within the scenic area, combined with unique data such as geographic information and real-time visitor flow data. This allows for timely retrieval of lost individuals and reduces safety risks during the search process. Furthermore, embodiments of this application also provide an electronic device, such as... Figure 3 As shown, it illustrates a structural schematic diagram of the electronic device involved in the embodiments of this application, specifically: The electronic device may include components such as a processor 301 with one or more processing cores, a memory 302 with one or more processor-readable storage media, a power supply 303, and an input unit 304. Those skilled in the art will understand that... Figure 3The electronic device structure shown does not constitute a limitation on the electronic device and may include more or fewer components than shown, or combine certain components, or have different component arrangements. Wherein: Processor 301 is the control center of the electronic device. It connects various parts of the electronic device via various interfaces and lines. By running or executing software programs and / or modules stored in memory 302, and by calling data stored in memory 302, it performs various functions and processes data, thereby providing overall monitoring of the electronic device. Optionally, processor 301 may include one or more processing cores; preferably, processor 301 may integrate an application processor and a modem processor, wherein the application processor mainly handles the operating system, user interface, and applications, and the modem processor mainly handles wireless location services for scenic spots. It is understood that the modem processor may not be integrated into processor 301.

[0080] The memory 302 can be used to store software programs and modules. The processor 301 executes various functional applications and methods for finding missing persons in scenic areas by running the software programs and modules stored in the memory 302. The memory 302 may mainly include a program storage area and a data storage area. The program storage area may store the operating system, application programs required for at least one function (such as sound playback function, image playback function, etc.), etc.; the data storage area may store data created based on the use of the electronic device, etc. In addition, the memory 302 may include high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other volatile solid-state storage device. Accordingly, the memory 302 may also include a memory controller to provide the processor 301 with access to the memory 302.

[0081] The electronic device also includes a power supply 303 that supplies power to various components. Preferably, the power supply 303 can be logically connected to the processor 301 through a power management system, thereby enabling functions such as charging, discharging, and power consumption management through the power management system. The power supply 303 may also include one or more DC or AC power supplies, recharging systems, power fault detection circuits, power converters or inverters, power status indicators, and other arbitrary components.

[0082] The electronic device may also include an input unit 304, which can be used to receive input digital or character information and generate keyboard, mouse, joystick, optical or trackball signal inputs related to user settings and function control.

[0083] Although not shown, the electronic device may also include a display unit, etc., which will not be described in detail here. Specifically, in the embodiments of this application, the processing 301 in the electronic device loads the executable files corresponding to the processes of one or more applications into the memory 302 according to the following instructions, and the processing 301 runs the applications stored in the memory 302 to realize various functions, as follows: Acquire the facial features of the target object and its initial capture information within the scenic area; combine the scenic area's geographic information database, and based on the facial features and initial capture information of the target object, determine the target object's movement trajectory and attraction stay information within the scenic area during the first time period; combine the scenic area's real-time visitor density data, and based on the movement trajectory and attraction stay information, determine the target object's search area within the scenic area and the search priority of each area during the second time period.

[0084] For details on the implementation of each of the above operations, please refer to the previous examples, which will not be repeated here.

[0085] This application embodiment can acquire facial features and initial snapshot information of a missing person within a scenic area. Combined with the scenic area's geographic information database, it determines the target's movement trajectory and stops at various attractions before disappearing. Furthermore, it uses real-time visitor density data to determine the search area and priority after the person goes missing. Scenic area staff can then conduct targeted searches based on the determined search areas and priorities, significantly improving search efficiency and accuracy. This method of finding missing persons within scenic areas does not rely on the target's active cooperation or their communication devices. It achieves precise location tracking solely through video data collected by monitoring equipment within the scenic area, combined with unique data such as scenic area geographic information and real-time visitor flow data. This allows for timely retrieval of missing persons and reduces safety risks during the search process.

[0086] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be performed by instructions, or by instructions controlling related hardware. These instructions can be stored in a processor-readable storage medium and loaded and executed by a processor.

[0087] Therefore, embodiments of this application provide a storage medium storing multiple instructions that can be loaded by a processor to execute steps in any of the scenic area search methods provided in this application. For example, the instructions can execute the following steps: Acquire the facial features of the target object and its initial capture information within the scenic area; combine the scenic area's geographic information database, and based on the facial features and initial capture information of the target object, determine the target object's movement trajectory and attraction stay information within the scenic area during the first time period; combine the scenic area's real-time visitor density data, and based on the movement trajectory and attraction stay information, determine the target object's search area within the scenic area and the search priority of each area during the second time period.

[0088] For details on the implementation of each of the above operations, please refer to the previous examples, which will not be repeated here.

[0089] The storage medium may include: read-only memory (ROM), random access memory (RAM), disk or optical disk, etc.

[0090] Since the instructions stored in the storage medium can execute the steps in any of the scenic area search methods provided in the embodiments of this application, the beneficial effects that any of the scenic area search methods provided in the embodiments of this application can achieve can be realized. For details, please refer to the previous embodiments, which will not be repeated here.

[0091] The foregoing has provided a detailed description of a method, apparatus, electronic device, and storage medium for finding people in scenic areas, as provided in the embodiments of this application. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the embodiments above are only for the purpose of helping to understand the method and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A method for finding missing persons in scenic areas, characterized in that, include: Obtain the facial features of the target object and the initial capture information within the scenic area; The initial capture information includes images captured by each monitoring point within the scenic area, along with the corresponding capture point and capture time. By combining the scenic area's geographic information database, and based on the facial features and initial capture information of the target object, the movement trajectory and attraction stop information of the target object within the scenic area during the first time period are determined; the movement trajectory and attraction stop information are obtained based on video data collected from various monitoring points within the scenic area and the scenic area's geographic information; Based on real-time visitor density data of the scenic area, and according to the movement trajectory and the information on the time spent at the attractions, the search area of ​​the target person in the scenic area and the search priority of each area are determined in the second time period.

2. The method according to claim 1, characterized in that, The start time of the second time period is no earlier than the start time of the first time period, and the end time of the second time period is later than the end time of the first time period. The second time period includes the search period in the scenic area after the target object loses contact.

3. The method according to claim 1, characterized in that, The acquisition of the facial features of the target object and the initial capture information within the scenic area includes: Obtain the facial image of the target object and extract facial features; The facial features of the target object are matched with the captured images in the scenic area's image database based on feature similarity. The scenic area's image database includes multiple images taken by various monitoring points within the scenic area, along with their corresponding shooting locations and shooting times. The captured images and corresponding information in the scenic area's image database that match the facial features of the target object are determined as the initial capture information of the target object.

4. The method according to claim 1, characterized in that, The acquisition of the facial features of the target object and the initial capture information within the scenic area includes: Obtain the facial image of the target object and extract facial features; The facial features of the target object are matched with the captured images in the scenic area image database to determine the feature similarity and at least one captured image that meets the similarity condition, along with the corresponding shooting location and shooting time. The scenic area image database includes multiple images taken by various monitoring points within the scenic area and their corresponding information. In response to a specified operation that selects a set of information from the at least one captured image and corresponding information, the specified captured image and corresponding shooting point and shooting time are determined as the initial capture information of the target object.

5. The method according to claim 4, characterized in that, The step of acquiring the facial image of the target object and extracting facial features includes: Receive the facial image of the target object provided by the user seeking people and extract facial features; Alternatively, based on the object identifier of the target object, obtain the face image corresponding to the object identifier from the scenic area's tourist face database and extract the face features; the scenic area's tourist face database pre-stores at least one face image collected when tourists enter the park or purchase tickets.

6. The method according to claim 1, characterized in that, The method of combining the scenic area's geographic information database, based on the facial features and initial capture information of the target object, determines the target object's movement trajectory and visit information within the scenic area during the first time period, including: Based on the facial features and initial capture information of the target object, the movement trajectory and attraction stay information corresponding to the target object are obtained from the scenic area trajectory feature database; the scenic area trajectory feature database includes the movement trajectory, attraction stay information and association information with monitoring points of each active object in the scenic area.

7. The method according to claim 6, characterized in that, Before obtaining the movement trajectory and attraction stay information corresponding to the target object from the scenic area trajectory feature database, the method further includes: Acquire video data collected from each monitoring point within the scenic area and geographic information from the scenic area's geographic information database; Based on the collected video data and scenic area geographic information, the movement trajectory and attraction stay information of at least one active object in the scenic area are determined and stored in the scenic area trajectory feature database after being associated with the corresponding monitoring point information; the at least one active object includes the target object.

8. The method according to claim 1, characterized in that, The method of combining the scenic area's geographic information database, based on the facial features and initial capture information of the target object, determines the target object's movement trajectory and visit information within the scenic area during the first time period, including: Acquire video data collected from each monitoring point within the scenic area and geographic information from the scenic area's geographic information database; Based on the collected video data and scenic area geographic information, and according to the facial features and initial capture information of the target object, the movement trajectory and attraction stay information of the target object within the scenic area during the first time period are determined.

9. The method according to any one of claims 1 to 8, characterized in that, The method, by combining real-time visitor density data of the scenic area and based on the movement trajectory and attraction stay information, determines the scenic area search area and search priority of each area for the target object within the second time period, including: Determine at least a portion of the complete movement trajectory and attraction stay information of the target object within the scenic area, wherein the at least a portion of the information includes the location of the target object at the end time of the first time period and the last attraction stay information; By combining real-time visitor density data and trail network information of the scenic area, and based on at least some of the information, the scenic area search area for the target object and the search priority of each area are determined in the second time period.

10. The method according to any one of claims 1 to 8, characterized in that, The method, by combining real-time visitor density data of the scenic area and based on the movement trajectory and attraction stay information, determines the scenic area search area and search priority of each area for the target object within the second time period, including: Obtain the historical visit data of the target scenic area; By combining real-time visitor density data of the scenic area, and based on the historical visit data of the scenic area and the movement trajectory and attraction stay information of the target object in the first time period, the search area of ​​the target object in the scenic area and the search priority of each area are determined.

11. A device for finding missing persons in scenic areas, characterized in that, include: The acquisition module is used to acquire the facial features of the target object and the initial capture information within the scenic area; The initial capture information includes images captured by each monitoring point within the scenic area, along with the corresponding capture point and capture time. The first determining module is used to combine the scenic area's geographic information database and, based on the facial features and initial capture information of the target object, determine the target object's movement trajectory and attraction stop information within the scenic area during a first time period; the movement trajectory and attraction stop information are obtained based on video data collected from various monitoring points within the scenic area and the scenic area's geographic information; The second determining module is used to combine real-time visitor density data of the scenic area with the movement trajectory and the information on the place of stay at the attractions to determine the scenic area search area and the search priority of each area for the target object in the second time period.

12. An electronic device, characterized in that, include: A memory, a processor, and a processor program stored in the memory and executable on the processor, wherein the processor executes the program as the steps of the scenic area search method as described in any one of claims 1 to 10.

13. A storage medium, characterized in that, The system contains a computer processing program that can be loaded by a processor and executed as described in any one of claims 1 to 10 for finding missing persons in a scenic area.

Images