Target identification method and device, and storage medium

Abstract

The invention discloses a target recognition method and device and a storage medium, target recognition is applied to a door lock, the door lock comprises a camera device and a Bluetooth module, the method comprises the steps that preliminary positioning of a target is conducted through the Bluetooth module, and a first positioning position of the target is obtained; controlling the camera device to rotate towards the first positioning position; performing secondary positioning of the target based on a first image acquired by the rotated camera device to obtain a second positioning position of the target; adjusting the rotation position of the camera device based on the second positioning position of the target; and identifying the target by using a second image collected by the adjusted camera device. In this way, the positioning precision and the target recognition efficiency can be improved.

Description

Technical Field

[0001] The present application relates to the field of smart home, and specifically to a target recognition method, device and storage medium. Background Art

[0002] With the rapid development of the Internet of Things and artificial intelligence technologies, smart home devices have become increasingly popular, greatly improving people's quality of life and convenience. As an important part of smart homes, smart door locks have attracted much attention for their security, convenience, and intelligence.

[0003] However, existing smart door locks have deficiencies in user location perception and camera angle adjustment, resulting in a poor user experience. Summary of the Invention

[0004] In order to solve the above technical problems, the technical solution adopted in this application is: to provide a target recognition method, device and storage medium, so as to at least solve the problem that the existing smart door locks in the relevant technology have deficiencies in user position perception and camera angle adjustment, resulting in poor user experience.

[0005] According to one embodiment of the present invention, a target recognition method is provided. The target recognition method is applied to a door lock. The door lock includes a camera device and a Bluetooth module. The method includes:

[0006] Performing preliminary positioning of the target through the Bluetooth module to obtain a first positioning position of the target;

[0007] controlling the camera device to rotate toward the first positioning position;

[0008] Performing secondary positioning of the target based on the first image captured by the rotated camera device to obtain a second positioning position of the target;

[0009] adjusting a rotational position of the camera device based on a second positioning position of the target;

[0010] The target is identified using the second image captured by the adjusted camera device.

[0011] To solve the above technical problems, a technical solution adopted in this application is to provide a target recognition system, including:

[0012] A Bluetooth module, wherein the Bluetooth module is used to perform preliminary positioning of the target and obtain a first positioning position of the target;

[0013] an acquisition module, the acquisition module being configured to control the camera to acquire the first image to perform secondary positioning of the target and obtain a second positioning position of the target; and to control the camera to acquire the second image to identify the target;

[0014] A control module is configured to control the camera device to rotate toward the first positioning position, and to adjust the rotation position of the camera device based on the second positioning position of the target.

[0015] To solve the above technical problems, a technical solution adopted in this application is: to provide an electronic device, including a memory and a processor, wherein the memory is used to store a computer program, and when the computer program is executed by the processor, it is used to implement the target recognition method in the above technical solution.

[0016] In order to solve the above technical problems, a technical solution adopted in this application is: providing a computer-readable storage medium, which is used to store a computer program. When the computer program is executed by a processor, it is used to implement the target recognition method in the above technical solution.

[0017] Through the above scheme, the target recognition method provided by the present application performs preliminary positioning of the target through the Bluetooth module to obtain the first positioning position of the target, controls the camera device to rotate toward the first positioning position, performs secondary positioning of the target based on the first image captured by the rotated camera device to obtain the second positioning position of the target, adjusts the rotation position of the camera device based on the second positioning position of the target, and uses the second image captured by the adjusted camera device to identify the target; in this way, the preliminary positioning of the target is quickly provided through the Bluetooth module, and further more accurate secondary positioning is performed based on the captured image, thereby improving the positioning accuracy of the target, and then quickly capturing an image containing the target, and performing target recognition based on the image, thereby also improving the recognition efficiency of target recognition. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without inventive efforts. Among them:

[0019] Figure 1 This is a schematic diagram of the structure of a target recognition system provided by this application;

[0020] Figure 2 This is a flow chart of an embodiment of a target recognition method provided by the present application;

[0021] Figure 3 This is a flow chart of another embodiment of the target recognition method provided by the present application;

[0022] Figure 4 This is a structural diagram of an embodiment of an electronic device provided by the present application;

[0023] Figure 5 It is a structural diagram of an embodiment of a computer-readable storage medium provided by this application. DETAILED DESCRIPTION

[0024] The present application will be further described in detail below in conjunction with the accompanying drawings and examples. It is particularly noted that the following examples are only intended to illustrate the present application and are not intended to limit the scope of the present application. Similarly, the following examples are only some examples of the present application and not all examples. All other examples obtained by those of ordinary skill in the art without creative work are intended to fall within the scope of protection of this application.

[0025] References to "embodiments" in this application mean that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute an independent or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0026] It should be noted that the terms "first", "second", etc. in this application are only used for descriptive purposes and cannot be understood as indicating or suggesting relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first", "second", etc. may explicitly or implicitly include at least one of the features. In the description of this application, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally also includes steps or units that are not listed, or optionally also includes other steps or units inherent to these processes, methods, products or devices.

[0027] The target recognition of the present application is applied to a door lock, and the door lock is provided with a target recognition system for implementing the target recognition method provided by the present application. In one example, see Figure 1 , Figure 1 This is a schematic diagram of the structure of a target recognition system provided by this application, including:

[0028] (1) Bluetooth module: It is the communication bridge between the smart door lock and the target device. The target can connect the door lock to the target device through the Bluetooth module to perform authentication and control operations, such as unlocking the door lock and setting user permissions. In addition, it can also combine signal strength detection and antenna arrival angle detection to perform preliminary positioning of the target.

[0029] (2) Microcontroller (MCU): It is mainly responsible for processing data and signals from various components such as Bluetooth modules, cameras, sensors, etc., performing corresponding logic control and operations, controlling the opening and closing actions of the door lock according to the target operation instructions and system status, and calculating and judging the target position.

[0030] (3) Capture module: This module includes a camera device for capturing image information outside the door, or combined with target recognition technology for identity verification, and performs integrity comparison on the target image captured by the camera device to determine whether the image meets the requirements. If the image is incomplete or has deviations, the module can instruct the control device to adjust the position of the camera device to obtain a more accurate target image for target recognition.

[0031] (4) Control device: This device is used to control the movement of the camera according to the instructions of the MCU, such as adjusting the angle and focal length of the camera to ensure the quality and accuracy of the captured image. In addition, it can also have functions such as controlling other mechanical components of the door lock.

[0032] (5) Power supply system: used to provide stable power support for the door lock. Preferably, it is powered by a lithium battery to ensure that the door lock can operate normally in normal use and standby mode.

[0033] See also Figure 2 , Figure 2 It is a flow chart of an embodiment of the target recognition method provided by this application. It should be noted that if there are substantially the same results, this embodiment does not Figure 2 The process sequence shown is limited. Figure 2 As shown, this embodiment includes:

[0034] S110: Perform preliminary positioning of the target through the Bluetooth module to obtain a first positioning position of the target.

[0035] The Bluetooth module periodically scans for broadcast signals from devices within a certain range. Using the signals received by the Bluetooth module from the target device carried by the target, the module calculates the target's distance and azimuth. Based on these distance and azimuth, the target's first position is determined. The target is a user or other object currently located or detected by the Bluetooth module. The target device carried by the target is a mobile phone, smartwatch, or other wearable device carried by the target that can assist in positioning or data transmission. The first position is within the acquisition range of the rotating camera device.

[0036] In one embodiment, the Bluetooth module performs signal strength detection on a signal sent by a target device to obtain signal strength data, and calculates the distance between the target and the door lock based on the signal strength data and a signal attenuation model.

[0037] For example, the Bluetooth module actively scans the broadcast signals emitted by surrounding devices at preset time intervals and records the signal strength (RSSI) value of each device in order to obtain the signal strength information between the target device and the door lock, providing a data basis for subsequent distance calculation and positioning. Since the RSSI value may be affected by factors such as environmental noise and interference, resulting in noise and outliers in the data, the RSSI value collected by the Bluetooth module can also be filtered to remove the noise and outliers to obtain stable and reliable signal strength data. For example, the RSSI value can be processed by sliding average filtering, median filtering, etc. Furthermore, the distance between the user device and the door lock is calculated based on the filtered RSSI value and the known signal propagation characteristics through the signal attenuation model.

[0038] Furthermore, in practical applications such as doorways, while multipath effects are relatively minor, some degree of reflection and refraction may still occur, leading to complex signal paths and affecting positioning accuracy. The least squares method can compensate for multipath effects, reduce positioning errors, and improve the reliability of Bluetooth positioning. Therefore, in this embodiment, the Bluetooth module can obtain the signal strengths of several signals within a preset range from the door lock. These signal strengths are then fitted using the least squares method to obtain the path signal emitted by the target device. This path signal is then used to calculate the target's distance and / or azimuth.

[0039] Exemplarily, the multiple received signal paths are treated as multiple measurement values, and an error equation is constructed. By minimizing the squared error between the actual measurement value and the theoretical value, the optimal parameter estimate is solved, thereby fitting the most likely direct path signal. For example, in a two-dimensional positioning scenario, assuming there are multiple measurement points, the RSSI value of each measurement point corresponds to a distance estimate. The least squares method can be used to solve the optimal location coordinates of the user device, so that the sum of the squared errors between the theoretical distance from the location to each measurement point and the actual measured distance is minimized.

[0040] In one embodiment, the Bluetooth module can be configured with multiple antennas to form an antenna array, and the multiple antennas work together to receive signals from the target device. The number and layout of the antennas can be determined according to specific design requirements and are not limited here. The time difference of arrival (TDoA) of the signal emitted by the target device at each antenna is calculated. Based on the signal arrival time difference and the antenna spacing between the multiple antennas, the signal incidence angle is calculated to serve as the azimuth of the target.

[0041] For example, each antenna receives a signal from the target device, records the time it takes for the signal to arrive at the antenna, and calculates the time difference of arrival (TDoA) by comparing the arrival times of the signals received by different antennas. Furthermore, based on the measured TDoA and the known antenna spacing, the geometric relationship is used to calculate the incident angle of the signal, that is, the angle of arrival (AoA), as the azimuth of the target device. Taking two antennas as an example, assuming that the antenna spacing is d, the signal propagation speed is c, and the measured time difference of arrival is Δt, the incident angle θ can be calculated using the following formula (1). For multi-antenna arrays, other algorithms can also be used to further improve the accuracy of angle estimation.

[0042]

[0043] In the smart door lock system provided in this embodiment, angle of arrival (AoA) detection can accurately determine the position and direction of the user device relative to the door lock, thereby achieving more accurate user location judgment and authentication operations.

[0044] In one embodiment, before performing preliminary positioning of a target using a Bluetooth module and obtaining the target's first position, a connection may be established between the target device carried by the target and the Bluetooth module to authenticate and register the target. In one implementation, the Bluetooth module is controlled to establish a connection with the target device carried by the target, and device information and permission information of the target device are obtained through the Bluetooth module. The device information and permission information of the target device are then sent to a cloud server for verification. In response to successful verification, preliminary positioning of the target using the Bluetooth module is performed to obtain the target's first position, and subsequent steps are performed.

[0045] S120: Control the camera device to rotate toward the first positioning position.

[0046] The target is preliminarily positioned through the Bluetooth module. After obtaining a first positioning position of the target, the camera device of the door lock is controlled to rotate toward the first positioning position, wherein the first positioning position includes the distance and azimuth of the target.

[0047] In one embodiment, the horizontal adjustment angle of the camera device is calculated using the azimuth angle, and the vertical adjustment angle of the camera device is calculated using the distance and the azimuth angle. The camera device is controlled to rotate horizontally according to the horizontal adjustment angle and vertically according to the vertical adjustment angle.

[0048] In one embodiment, the azimuth of the target is calculated and used as the horizontal adjustment angle of the camera device. The vertical adjustment angle of the camera device is related to factors such as the distance between the target and the door lock and the azimuth. The height difference between the height of a first key point on the target's face and the height of the camera device, as well as the product of the distance and the cosine of the azimuth, are calculated. The inverse tangent of a first ratio between the height difference and the product is calculated to obtain the vertical adjustment angle of the camera device. Preferably, the first key point is an eye.

[0049] For example, the vertical adjustment angle Δα of the camera device is calculated using the following formula (2): y , where h is the height of the first key point of the target's face, h0 is the height of the camera device, l is the distance between the target and the door lock, and θ is the azimuth angle of the target.

[0050]

[0051] S130: Perform secondary positioning of the target based on the first image captured by the rotated camera device to obtain a second positioning position of the target.

[0052] After the camera device is rotated to the first positioning position based on the horizontal adjustment angle and the vertical adjustment angle, the target is secondary positioned based on the first image captured by the rotated camera device to obtain the second positioning position of the target.

[0053] In one embodiment, a camera device captures a first image at a first positioning position, performs feature point detection on the first image, and obtains the image position of a second key point in the first image, wherein the second key point is a feature point located on the face, and preferably, the second key point is the eye of the target. According to the calibration parameters of the camera device and the image position of the second key point, the actual position of the second key point is calculated to obtain the second positioning position. The calibration parameters of the camera device are obtained through a calibration process of the camera device, including but not limited to internal parameters (such as focal length, principal point coordinates, lens distortion coefficient, etc.) and external parameters (such as rotation matrix, translation vector, etc.); the image position of the second key point may include the pixel height of the second key point in the first image; and the actual position of the second key point may include the actual height of the second key point.

[0054] In one embodiment, a second ratio is obtained by calculating the ratio between the pixel height of the second key point in the first image and the actual size of each pixel in the first image, and the second ratio is multiplied by the focal length of the camera device to obtain the actual height of the second key point, and then the second positioning position of the target is obtained.

[0055] S140: Adjusting the rotation position of the camera device based on the second positioning position of the target.

[0056] After calculating the second positioning position of the target based on the first image captured at the first positioning position, in order to obtain more accurate positioning of the target and improve the speed of image capture and target recognition of the target's face, the first positioning position is fused with the second positioning position to obtain a fused positioning position, and the rotation position of the camera device is adjusted according to the fused positioning position.

[0057] In one embodiment, the fusion position of the first positioning position and the second positioning position is calculated based on the Kalman filter algorithm or the data fusion algorithm to obtain the fusion positioning position, the correction angle corresponding to the camera device from the first positioning position to the fusion positioning position is obtained, and the camera device is controlled to rotate toward the fusion positioning position according to the correction angle.

[0058] S150: Identify the target using the second image captured by the adjusted camera device.

[0059] After adjusting the position of the camera device to the fusion positioning position, the camera device is controlled to capture images to obtain a second image, and the target is identified using the second image captured by the adjusted camera device.

[0060] In one embodiment, a second image captured by the camera at the fusion positioning position is obtained and pre-processed. For example, grayscale processing can be performed to convert the color image into a grayscale image to reduce data volume and computational complexity. Noise removal can be further performed using a filtering algorithm (such as Gaussian filtering or median filtering) to remove noise interference in the image. Image enhancement, such as contrast adjustment and histogram equalization, can also be performed to improve the visual effect and feature clarity of the image.

[0061] The preprocessed second image is used to identify the target and determine its identity. For example, a deep learning-based target recognition algorithm, such as a convolutional neural network (CNN), can be used. The preprocessed image is input into a trained model, which automatically extracts features from the image, compares them with known target features, and outputs a recognition result. Alternatively, traditional target recognition methods, such as a cascade classifier based on Haar features, can be used to detect and identify the target.

[0062] Finally, the target recognition results are processed and the corresponding actions are performed based on the recognition results. For example, if the target recognition is successful, that is, the target is identified as a known legitimate user, the door can be unlocked, allowing the user to enter. At the same time, the recognition results can be fed back to the user device and cloud server for recording and updating. If the target recognition fails, that is, the target identity cannot be determined or the target is not identified as a legitimate user, the door lock remains closed and an alarm mechanism can be triggered to alert the user and relevant security systems.

[0063] This embodiment uses the Bluetooth module for rapid positioning and image-based precision positioning, improving target positioning accuracy. This allows for rapid acquisition of images containing the target and target recognition based on these images, thereby improving target recognition efficiency. Furthermore, because only preliminary positioning is performed using the Bluetooth module, image acquisition is initiated only during target recognition. This prevents invalid target recognition, reduces battery power consumption, and improves the efficiency and stability of target recognition within the door lock system.

[0064] See also Figure 3 , Figure 3 It is a flow chart of another embodiment of the target recognition method provided by this application. It should be noted that if there is substantially the same result, this embodiment does not Figure 3 The process sequence shown is limited. Figure 3 As shown, this embodiment takes the scenario where a door lock performs target recognition to control door unlocking as an example, and includes:

[0065] S201: The user controls the door lock through the application software to enter the face collection.

[0066] When using the system for the first time or when a new user logs in, the user establishes a connection with the door lock's Bluetooth module via a smartphone or other smart device. The door lock obtains the user's device information and identity information through the Bluetooth module and sends the user's device information and identity permission information to the cloud server for verification. After the cloud server verifies the user, it returns a successful authentication message, allowing the door lock to enter the user's face.

[0067] S202: Obtain the current distance and azimuth between the user and the door lock through the Bluetooth module.

[0068] The Bluetooth module scans the broadcast signals emitted by surrounding devices to obtain the signal strength value of the target device bound by the user to the door lock, uses the least squares method to compensate for the multipath effect, reduces the positioning error, and obtains the path signal emitted by the target device. The path signal is used to calculate the distance and / or azimuth of the target.

[0069] Substitute the signal strength value of the path signal into the following formula (3) to calculate the distance l between the user and the door lock, where P t is the transmit power, P r is the signal strength value of the path signal, A is the signal strength at the reference distance, and n is the path loss exponent.

[0070]

[0071] The Bluetooth module is equipped with multiple antennas, forming an antenna array. Each antenna receives the signal from the target device and records the time it takes for the signal to reach each antenna. By comparing the arrival times of the signals received by different antennas, the time difference of arrival (TDoA) is calculated. Furthermore, based on the time difference of arrival (TDoA) and the antenna spacing, the aforementioned formula (1) is used to calculate the angle of incidence of the signal, thereby obtaining the user's current azimuth.

[0072] Combined with the distance and azimuth between the user and the door lock obtained by the Bluetooth module, the target's position can be preliminarily located.

[0073] S203: Adjust the angle of the camera device and capture or recognize the user's face.

[0074] The microcontroller (MCU) calculates the optimal angle of the camera device based on the target position obtained by preliminary positioning, and controls the camera device to adjust the angle of the camera device to ensure the integrity and accuracy of the user's face acquisition.

[0075] The azimuth angle calculated in step S202 is used as the horizontal adjustment angle of the camera device, and the camera device is controlled to rotate horizontally at the horizontal adjustment angle. At the same time, the vertical adjustment angle is calculated based on the distance between the user and the door lock and the azimuth angle, and the camera device is controlled to rotate vertically at the vertical adjustment angle. The calculation of the vertical adjustment angle can be referred to formula (2) in step S120 and will not be repeated here.

[0076] After adjusting the camera's angle based on the horizontal and vertical adjustment angles, the camera is controlled to capture an image of the user at the door. If the camera's current position is sufficient to capture a complete and clear image of the user, the system will directly capture the user's facial image, assuming it is a first-time user or a new user has been registered. If the user requires target recognition to open the door, the door lock is controlled to unlock when target recognition is successful, allowing the user to enter the target location.

[0077] If the current position of the camera device is still insufficient to capture a complete and clear image of the user, step S204 is executed to obtain a more accurate positioning position of the user, thereby enabling image capture or target recognition of the user.

[0078] S204: The preliminary positioning position measured by the Bluetooth module and the secondary positioning position obtained by the image algorithm are integrated to obtain the final position of the user.

[0079] The camera is controlled to capture images at the initial positioning position. Image processing techniques are used to detect key points on the user's face, particularly the position of the eyes. The actual height and position of the user's eyes are then calculated based on the camera's calibration parameters and the position of the eyes in the image.

[0080] For example, h is defined as the height of the user's eyes, f is the focal length of the camera, H is the pixel height of the user's eyes in the image, and p is the actual size of each pixel in the image. The actual height of the current user's eyes is calculated using the following formula (4).

[0081]

[0082] The target is relocated by calculating the actual height of the current user's eyes to obtain the precise position of the target's secondary positioning. Furthermore, the preliminary positioning position measured by the Bluetooth module and the secondary positioning position of the image algorithm are fused using Kalman filtering to obtain the user's final position.

[0083] S205: Correct the position of the camera device, capture images, enter user corresponding information or open the door.

[0084] The camera's position is precisely corrected based on the calculated user's final position. If this is a first-time user or a new user is logging into the system, the camera is controlled to capture images and record the user's information. If the user needs to open the door, target recognition is performed. If target recognition is successful, the door unlocks, allowing the user entry. Otherwise, the door remains locked, and an alarm may be triggered to alert the user and related security systems.

[0085] In one embodiment, a target recognition system is provided, comprising at least: (1) a Bluetooth module, the Bluetooth module being used to perform preliminary positioning of a target to obtain a first positioning position of the target; (2) an acquisition module, the acquisition module being used to control a camera device to capture a first image to perform secondary positioning of the target to obtain a second positioning position of the target; and, controlling the camera device to capture a second image to identify the target; and (3) a control module, the control module being used to control the camera device to rotate toward the first positioning position, and, based on the second positioning position of the target, to adjust the rotation position of the camera device.

[0086] See also Figure 4 , Figure 4 This is a structural diagram of an embodiment of an electronic device provided in the present application. The electronic device 60 includes a memory 61 and a processor 62 connected to each other. The memory 61 is used to store a computer program. When the computer program is executed by the processor 62, it is used to implement the target recognition method in the above embodiment.

[0087] The method of the above embodiment may exist in the form of a computer program, so the present application proposes a computer readable storage medium, see Figure 5 , Figure 5 1 is a schematic structural diagram of an embodiment of a computer-readable storage medium provided in the present application. The computer-readable storage medium 80 is used to store a computer program 81, which can be executed to implement the target recognition method in the above embodiment.

[0088] The computer-readable storage medium 80 can be a server, a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, etc., which can store program codes.

[0089] If the technical solution of this application involves personal information, the product that applies the technical solution of this application has clearly informed the personal information processing rules and obtained the individual's voluntary consent before processing personal information. If the technical solution of this application involves sensitive personal information, the product that applies the technical solution of this application has obtained the individual's separate consent before processing sensitive personal information, and at the same time meets the "explicit consent" requirement. For example, on personal information collection devices such as cameras, a clear and prominent sign is set to inform that the personal information collection scope has been entered and personal information will be collected. If the individual voluntarily enters the collection scope, it is deemed that they agree to the collection of their personal information; or on the personal information processing device, when the personal information processing rules are notified by obvious signs / information, the individual's authorization is obtained through pop-up information or by asking the individual to upload their personal information; among which, the personal information processing rules may include information such as the personal information processor, the purpose of personal information processing, the processing method, and the type of personal information processed.

[0090] The above description is merely an embodiment of the present application and does not limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present application.

Claims

1. A target recognition method, characterized in that: The target recognition is applied to a door lock, which includes a camera and a Bluetooth module. The method includes: Performing preliminary positioning of the target through the Bluetooth module to obtain a first positioning position of the target; controlling the camera device to rotate toward the first positioning position; Performing secondary positioning of the target based on the first image captured by the rotated camera device to obtain a second positioning position of the target; adjusting a rotational position of the camera device based on a second positioning position of the target; The target is identified using the second image captured by the adjusted camera device.

2. The method according to claim 1, characterized in that The preliminary positioning of the target by the Bluetooth module to obtain the first positioning position of the target includes: Calculating the distance and azimuth of the target by using the signal sent by the target device carried by the target and received by the Bluetooth module; The first positioning position is obtained based on the distance and azimuth of the target.

3. The method according to claim 2, characterized in that The Bluetooth module is configured with a plurality of antennas, and the calculation of the distance and azimuth of the target by using the signal sent by the target device carried by the target and received by the Bluetooth module includes: Performing signal strength detection on the signal emitted by the target device to obtain signal strength data, and calculating the distance to the target based on the signal strength data and a signal attenuation model; and Calculating the signal arrival time difference of the signal emitted by the target device at each of the antennas, and calculating the signal incidence angle based on the signal arrival time difference and the antenna spacing between the plurality of antennas to obtain the signal incidence angle as the azimuth of the target; And / or, before calculating the distance and azimuth of the target using the signal sent by the target device carried by the target and received by the Bluetooth module, the method further includes: The signal strength of several signals within a preset range from the door lock is obtained through the Bluetooth module, and the signal strengths of the several signals are fitted based on the least squares method to obtain a path signal emitted by the target device, wherein the path signal is used to calculate the distance and / or azimuth of the target.

4. The method according to claim 1, wherein The first positioning position includes the distance and azimuth of the target; and controlling the camera device to rotate toward the first positioning position includes: The horizontal adjustment angle of the camera device is calculated using the azimuth angle, and the vertical adjustment angle of the camera device is calculated using the distance and the azimuth angle; Controlling the camera device to rotate horizontally according to the horizontal adjustment angle and to rotate vertically according to the vertical adjustment angle; And / or, performing secondary positioning of the target based on the first image captured by the rotated camera device to obtain a second positioning position of the target includes: Performing feature point detection on the first image to obtain an image position of a second key point in the first image, wherein the second key point is located on the face; According to the calibration parameters of the camera device and the image position of the second key point, the actual position of the second key point is calculated as the second positioning position.

5. The method according to claim 4, characterized in that The step of calculating the horizontal adjustment angle of the camera device by using the azimuth angle includes: Using the azimuth angle as the horizontal adjustment angle of the camera device; The method of calculating the vertical adjustment angle of the camera device by using the distance and the azimuth angle includes: Obtaining a height difference between a height of a first key point on the target's face and a height of the camera device, and a product of the distance and a cosine value of the azimuth angle, and using an arc tangent value of a first ratio between the height difference and the product as the vertical adjustment angle of the camera device; And / or, the actual position of the second key point includes the actual height of the second key point, and the image position of the second key point includes the pixel height of the second key point in the first image; and calculating the actual position of the second key point according to the calibration parameters of the camera device and the image position of the second key point includes: The actual height of the second key point is the product of the focal length of the camera device and a second ratio, wherein the second ratio is the ratio between the pixel height of the second key point in the first image and the actual size of each pixel in the first image.

6. The method according to claim 1, characterized in that The adjusting the rotation position of the camera device based on the second positioning position of the target includes: fusing the first positioning position and the second positioning position to obtain a fused positioning position; According to the fusion positioning position, the rotation position of the camera device is adjusted.

7. The method according to claim 6, characterized in that The fusing the first positioning position and the second positioning position to obtain a fused positioning position includes: Calculate a fused position of the first positioning position and the second positioning position based on a Kalman filter algorithm or a data fusion algorithm to obtain the fused positioning position; The adjusting the rotation position of the camera device according to the fusion positioning position includes: Obtaining a correction angle corresponding to the camera device from the first positioning position to the fusion positioning position; The camera device is controlled to rotate toward the fusion positioning position according to the correction angle.

8. The method according to claim 1, characterized in that Before performing preliminary positioning of the target by the Bluetooth module to obtain the first positioning position of the target, the method includes: Controlling the Bluetooth module to establish a connection with a target device carried by the target; Acquire the device information and permission information of the target device through the Bluetooth module, and send the device information and permission information of the target device to the cloud server for verification; In response to the verification being passed, the preliminary positioning of the target by using the Bluetooth module is performed to obtain the first positioning position of the target and subsequent steps.

9. An electronic device, characterized in that: The electronic device includes a processor and a memory, wherein the processor is coupled to the memory, and the processor is configured to execute one or more steps of the target recognition method according to any one of claims 1 to 8 based on instructions stored in the memory.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and the computer program is executed by a processor to implement the steps of the target recognition method according to any one of claims 1 to 8.

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