Live detection methods, systems, electronic devices, and storage media

Abstract

The application discloses a kind of live detection method, system, electronic equipment and storage medium.Therein, the method includes: using first biological characteristic verification mode, specified action verification is carried out to target object, and first verification result is obtained, and using second biological characteristic verification mode, specified part verification is carried out to target object, and second verification result is obtained;First verification result and second verification result are sent to server;Receive the check result from server;In response to the check result indicating that first verification result and second verification result are checked by server, determine that target object is live.The application solves the technical problems that the live detection mode provided in the related art has low security, high detection implementation cost.

Description

Technical Field

[0001] This application relates to the field of computer technology, and more specifically, to a liveness detection method, system, electronic device, and storage medium. Background Technology

[0002] With the widespread application of biometric technology, liveness detection has become a crucial element in ensuring system security and plays a vital role in modern security verification systems. Liveness detection aims to distinguish real users from inanimate images, videos, or simulated attacks, thereby effectively protecting system security and preventing unauthorized access. Some related technologies rely on verifying simple user actions to determine if a user is truly alive, offering ease of operation but relatively weak security defenses, particularly against advanced attack methods. Other technologies utilize complex hardware for liveness detection, such as 3D structured light sensors. While this significantly improves accuracy and security, the high cost and complexity of the equipment negatively impact user experience and widespread adoption. Therefore, none of the current liveness detection methods have achieved a balance between high security, low cost, and a good user experience.

[0003] There is currently no effective solution to the above problems. Summary of the Invention

[0004] This application provides a liveness detection method, system, electronic device, and storage medium to at least solve the technical problems of low security and high detection implementation cost of liveness detection methods provided in related technologies.

[0005] According to one aspect of the embodiments of this application, a liveness detection method is provided, comprising: performing a specified action verification on a target object using a first biometric verification method to obtain a first verification result; and performing a specified part verification on the target object using a second biometric verification method to obtain a second verification result, wherein the first biometric verification method is used to perform interactive behavioral feature verification on the specified action of the target object, and the second biometric verification method is used to perform interactive color change response verification on the specified part of the target object; sending the first verification result and the second verification result to a server, wherein the server is used to verify the first verification result and the second verification result; receiving a verification result from the server, wherein the verification result is used to indicate whether both the first verification result and the second verification result have passed the server's verification; and determining that the target object is a live object in response to the verification result indicating that both the first verification result and the second verification result have passed the server's verification.

[0006] According to another aspect of the embodiments of this application, a liveness detection method is also provided, comprising: receiving a first verification result and a second verification result from a client, wherein the first verification result is obtained by verifying a specified action of a target object using a first biometric verification method, and the second verification result is obtained by verifying a specified part of the target object using a second biometric verification method, wherein the first biometric verification method is used to perform interactive behavioral feature verification of the specified action of the target object, and the second biometric verification method is used to perform interactive color change response verification of the specified part of the target object; verifying the first verification result and the second verification result to obtain a verification result, wherein the verification result is used to indicate whether both the first verification result and the second verification result have passed the verification; and feeding back the verification result to the client.

[0007] According to another aspect of the embodiments of this application, a liveness detection method is also provided, comprising: verifying a pet's specified actions using a first biometric verification method to obtain a first verification result; and verifying a pet's specified body parts using a second biometric verification method to obtain a second verification result, wherein the first biometric verification method is used to perform interactive behavioral feature verification of the pet's specified actions, and the second biometric verification method is used to perform interactive color change response verification of the pet's specified body parts; sending the first verification result and the second verification result to a server, wherein the server is used to verify the first verification result and the second verification result; receiving a verification result from the server, wherein the verification result is used to indicate whether both the first verification result and the second verification result have passed the server's verification; in response to the verification result indicating that both the first verification result and the second verification result have passed the server's verification, determining that the pet is a live animal; and in response to the pet's specified body part image matching an image pre-stored in the access control system, unlocking the access control system to allow the pet to enter.

[0008] According to another aspect of the embodiments of this application, a liveness detection method is also provided, comprising: obtaining a liveness detection request through a first application programming interface (API), wherein the request data carried in the liveness detection request includes: a first verification result and a second verification result, wherein the first verification result is obtained by verifying a specified action of a target object using a first biometric verification method, and the second verification result is obtained by verifying a specified part of the target object using a second biometric verification method, wherein the first biometric verification method is used to perform interactive behavioral feature verification of a specified action of the target object, and the second biometric verification method is used to perform interactive color change response verification of a specified part of the target object; and returning a liveness detection response through a second API, wherein the response data carried in the liveness detection response includes: a verification result, wherein the verification result is used to indicate whether both the first verification result and the second verification result have passed verification.

[0009] According to another aspect of the embodiments of this application, a liveness detection method is also provided, comprising: acquiring a currently input liveness detection dialogue request, wherein the request data carried in the liveness detection dialogue request includes: a first verification result and a second verification result, wherein the first verification result is obtained by verifying a specified action of a target object using a first biometric verification method, and the second verification result is obtained by verifying a specified part of the target object using a second biometric verification method, wherein the first biometric verification method is used to perform interactive behavioral feature verification of a specified action of the target object, and the second biometric verification method is used to perform interactive color change response verification of a specified part of the target object; responding to the liveness detection dialogue request, returning a liveness detection dialogue response, wherein the information carried in the liveness detection dialogue response includes: a verification result, wherein the verification result is used to indicate whether both the first verification result and the second verification result have passed verification; and displaying the verification result in a graphical user interface.

[0010] According to another aspect of the embodiments of this application, a liveness detection method is also provided, comprising: responding to an input command applied to an operation interface, displaying a first verification result and a second verification result on the operation interface; responding to a processing command applied to the operation interface, displaying a verification result on the operation interface; wherein, the first verification result is obtained by verifying a specified action of a target object using a first biometric verification method, the second verification result is obtained by verifying a specified part of the target object using a second biometric verification method, the first biometric verification method is used to perform interactive behavioral feature verification of a specified action of the target object, the second biometric verification method is used to perform interactive color change response verification of a specified part of the target object, and the verification result is used to indicate whether both the first verification result and the second verification result have passed the verification.

[0011] According to another aspect of the embodiments of this application, a liveness detection system is also provided, comprising: a client, configured to send a first verification result and a second verification result, wherein the first verification result is obtained by verifying a specified action of a target object using a first biometric verification method, and the second verification result is obtained by verifying a specified part of the target object using a second biometric verification method, wherein the first biometric verification method is used to perform interactive behavioral feature verification of the specified action of the target object, and the second biometric verification method is used to perform interactive color change response verification of the specified part of the target object; a server, connected to the client, configured to verify the first verification result and the second verification result to obtain a verification result, and to feed back the verification result to the client, wherein the verification result is used to indicate whether both the first verification result and the second verification result have passed the verification; the client is also configured to output the verification result.

[0012] According to another aspect of the embodiments of this application, a computing device is also provided, including: a memory storing an executable program; and a processor for running the program, wherein the program executes the methods in various embodiments of this application when it runs.

[0013] According to another aspect of the embodiments of this application, an electronic device is also provided, including: a memory storing an executable program; and a processor connected to the memory via a bus for running the program, wherein the program executes the methods in various embodiments of this application when it runs.

[0014] According to another aspect of the embodiments of this application, a computer-readable storage medium is also provided, the computer-readable storage medium including a stored executable program, wherein, when the executable program is running, it controls the device where the computer-readable storage medium is located to perform the methods of various embodiments of this application.

[0015] According to another aspect of the embodiments of this application, a computer program product is also provided, including a computer program that, when executed by a processor, implements the methods of various embodiments of this application.

[0016] According to another aspect of the embodiments of this application, a computer program product is also provided, including a non-volatile computer-readable storage medium storing a computer program that, when executed by a processor, implements the methods in various embodiments of this application.

[0017] According to another aspect of the embodiments of this application, a computer program is also provided, which, when executed by a processor, implements the methods of the various embodiments of this application.

[0018] In this embodiment, a first verification result is obtained by interactively verifying the specified actions of the target object, and a second verification result is obtained by interactively verifying the color change response of a specified part of the target object. The first and second verification results are then sent to the server for verification. Subsequently, the verification result from the server is received. When the verification result shows that both the first and second verification results pass the server's verification, the target object is determined to be a live object. Thus, by integrating the specified action verification and the specified part color change response verification, the security of the biometric system is effectively improved, while optimizing the user experience, reducing the detection implementation cost, and improving environmental adaptability and decision accuracy. This solves the technical problems of low security and high detection implementation cost of the liveness detection methods provided in related technologies.

[0019] It is worth noting that the general description above and the detailed description that follow are merely for illustrative purposes and do not constitute a limitation on this application. Attached Figure Description

[0020] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0021] Figure 1 This is a hardware structure block diagram of a computer terminal (or mobile device) for implementing a liveness detection method according to an embodiment of this application;

[0022] Figure 2 This is a schematic diagram of a liveness detection system according to an embodiment of this application;

[0023] Figure 3 This is a flowchart of a liveness detection method according to an embodiment of this application;

[0024] Figure 4 This is a flowchart of another liveness detection method according to an embodiment of this application;

[0025] Figure 5 This is a flowchart of another liveness detection method according to an embodiment of this application;

[0026] Figure 6 This is a flowchart of another liveness detection method according to an embodiment of this application;

[0027] Figure 7 This is a flowchart of another liveness detection method according to an embodiment of this application;

[0028] Figure 8 This is a flowchart of another liveness detection method according to an embodiment of this application;

[0029] Figure 9 This is a structural block diagram of a liveness detection device according to an embodiment of this application;

[0030] Figure 10 This is a structural block diagram of another liveness detection device according to an embodiment of this application;

[0031] Figure 11 This is a structural block diagram of another liveness detection device according to an embodiment of this application;

[0032] Figure 12 This is a structural block diagram of another liveness detection device according to an embodiment of this application;

[0033] Figure 13 This is a structural block diagram of another liveness detection device according to an embodiment of this application;

[0034] Figure 14This is a structural block diagram of another liveness detection device according to an embodiment of this application;

[0035] Figure 15 This is a structural block diagram of a computer terminal according to an embodiment of this application. Detailed Implementation

[0036] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0037] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0038] According to an embodiment of this application, a method embodiment for liveness detection is also provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0039] The method embodiment provided in Embodiment 1 of this application can be executed on a mobile terminal, computer terminal, or similar computing device. Figure 1 A hardware block diagram of a computer terminal (or mobile device) for implementing a liveness detection method is shown. Figure 1As shown, the computer terminal 10 (or mobile device) may include one or more processors 102 (shown as 102a, 102b, ..., 102n in the figure) 102 (processor 102 may include, but is not limited to, a microprocessor (MCU) or a field-programmable gate array (FPGA) or similar processing device), a memory 104 for storing data, and a transmission device 106 for communication functions. In addition, it may also include: a display, an input / output interface (I / O interface), a Universal Serial Bus (USB) port (which may be included as one of the ports of a BUS bus), a network interface, a power supply, and / or a camera. Those skilled in the art will understand that... Figure 1 The structure shown is for illustrative purposes only and does not limit the structure of the aforementioned electronic device. For example, computer terminal 10 may also include... Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown.

[0040] It should be noted that the aforementioned one or more processors 102 and / or other data processing circuits are generally referred to herein as "data processing circuits". These data processing circuits may be embodied, in whole or in part, in software, hardware, firmware, or any other combination thereof. Furthermore, the data processing circuits may be a single, independent processing module, or may be integrated, in whole or in part, into any other element within the computer terminal 10 (or mobile device). As involved in the embodiments of this application, the data processing circuits serve as a processor control mechanism (e.g., selection of a variable resistor termination path connected to an interface).

[0041] The memory 104 can be used to store software programs and modules of application software, such as the program instructions / data storage device corresponding to the liveness detection method in this embodiment. The processor 102 executes various functional applications and data processing by running the software programs and modules stored in the memory 104, thereby realizing the aforementioned liveness detection method. The memory 104 may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include memory remotely located relative to the processor 102, and these remote memories can be connected to the computer terminal 10 via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0042] The transmission device 106 is used to receive or send data via a network. Specific examples of the network described above may include a wireless network provided by the communication provider of the computer terminal 10. In one example, the transmission device 106 includes a Network Interface Controller (NIC), which can connect to other network devices via a base station to communicate with the Internet. In another example, the transmission device 106 may be a Radio Frequency (RF) module, used for wireless communication with the Internet.

[0043] The display can be, for example, a touchscreen liquid crystal display (LCD), which allows the user to interact with the user interface of the computer terminal 10 (or mobile device).

[0044] Figure 1 The hardware structure block diagram shown can serve not only as an exemplary block diagram of the aforementioned computer terminal 10 (or mobile device), but also as an exemplary block diagram of the aforementioned server. In one optional embodiment, Figure 2 The use of the above is illustrated in a block diagram. Figure 1 The computer terminal 10 (or mobile device) shown is one embodiment of the transmitting end. For example... Figure 2 As shown, computer terminal 10 (or mobile device) can be connected to one or more servers via a data network connection or electronically. In one alternative embodiment, the computer terminal 10 (or mobile device) can be any mobile computing device, etc. The data network connection can be a local area network connection, a wide area network connection, an Internet connection, or other types of data network connection. Computer terminal 10 (or mobile device) can perform network services to connect to a network service performed by a server (e.g., a security server) or a group of servers 20. The network server is a network-based user service, such as social networks, cloud resources, email, online payments, or other online applications.

[0045] Under the aforementioned operating environment, this application provides the following: Figure 3 The liveness detection method shown. Figure 3 This is a flowchart of a liveness detection method according to an embodiment of this application, such as... Figure 3 As shown, the method includes the following steps:

[0046] Step S31: Using a first biometric verification method, the target object is verified for a specified action to obtain a first verification result; and using a second biometric verification method, the target object is verified for a specified part to obtain a second verification result. The first biometric verification method is used to perform interactive behavioral feature verification on the specified action of the target object, and the second biometric verification method is used to perform interactive color change response verification on the specified part of the target object.

[0047] Step S32: Send the first verification result and the second verification result to the server, wherein the server is used to verify the first verification result and the second verification result;

[0048] Step S33: Receive the verification result from the server, wherein the verification result is used to indicate whether both the first verification result and the second verification result have passed the server's verification.

[0049] Step S34: In response to the verification results showing that both the first verification result and the second verification result have passed the server's verification, the target object is determined to be a living being.

[0050] The target objects mentioned above can be individuals requiring biometric verification, such as humans and animals. Liveness detection technology is widely used in facial recognition systems, such as security access control, mobile payment, and login verification. Facial recognition systems can be used to determine whether the target object is a real, living human. In some specific applications, such as farm management and pet identification systems, the target object can also be an animal, and liveness detection is used to confirm the animal's liveness status.

[0051] The aforementioned first biometric verification method is used to interactively verify the behavioral characteristics of a target object's specified actions, including but not limited to: blink verification, head shaking verification, smiling or specific facial expression verification, gesture verification, and voice command response verification. This allows for a quick and intuitive determination of whether the target object is alive. Specifically, during blink verification, the liveness detection system prompts the user to blink slightly. The camera captures this action and analyzes the dynamic changes in eye opening and closing to determine if the user is truly alive. Blink verification is user-friendly and has a fast response time, making it suitable for most biometric scenarios. During head shaking verification, the target object is required to shake their head slightly. By capturing the head movement trajectory, the system determines whether it represents a genuine human head movement, thus performing liveness detection. For smiling or specific facial expression verification, the liveness detection system prompts the user to display a smile or other specific expression, verifying the liveness status by capturing and analyzing subtle changes in facial expressions. During gesture verification, the target object performs specific gestures, such as raising or waving their hand. The camera captures and analyzes the dynamic characteristics of the gesture to verify the liveness status. When verifying voice command response, the target object needs to respond to the voice command, such as reading aloud or repeating specific syllables. By capturing the dynamic characteristics of the sound, its liveness status is verified. This method increases the diversity of verification methods and is suitable for scenarios that require voice recognition.

[0052] Using any one or more of the aforementioned specified actions for verification can effectively perform preliminary interactive verification of the target object's biometrics, ensuring that the target object has the ability to respond in real time and change dynamically, thereby eliminating interference from static images, video playback, or synthetic content, and improving the security and accuracy of the verification. Preferably, in practical applications, blink verification has become the choice for implementing interactive behavioral feature verification due to its simple operation, non-invasiveness, and rapid response.

[0053] The aforementioned second biometric verification method is used to interactively verify the color change response of designated areas of the target object. This effectively combats complex attack methods such as Artificial Intelligence (AI) simulation and injection attacks, improving the security level of the biometric system. The designated areas include, but are not limited to: face, hands, eye area, neck or ears, and specific biometric marker areas. Specifically, the face is a common verification area. By analyzing the changes in light reflection mapped to the target object's facial area using specific colors, the system verifies whether the target object is a real, living person. In some scenarios, such as hand biometric recognition systems, the system can verify the real reaction of the hand's skin by observing changes in screen color to determine if it is a live hand. Besides the entire face, the liveness detection system can also focus on the reaction of the skin around the eyes. Because the thickness of the skin around the eyes results in more significant color differences, this can serve as additional evidence of liveness. When the face is obscured or requires additional confirmation, the liveness detection system can shift to verifying the color change response of the skin around the neck or ears. In some advanced biometric systems, specific biometric regions (such as fingerprints, palm prints, etc.) are set up. By changing the color and intensity of the light displayed in that specific biometric region, the color and texture response can be observed to verify its liveness and uniqueness.

[0054] The core of interactive color change response verification lies in utilizing the natural reflection or absorption characteristics of screen-displayed colors by the biometric features of a target object, as well as its dynamic response to color changes, to determine whether it is a living person. Interactive color change response verification can not only confirm the authenticity of the target object's biometric features but also identify potential attack methods, such as the use of simulated masks or synthetic videos. These methods typically cannot accurately replicate the subtle reactions of a real biological body to color changes. Therefore, interactive color change response verification plays a crucial role in improving the security of biometric systems.

[0055] After obtaining a first verification result using the first biometric verification method and a second verification result using the second biometric verification method, the first and second verification results are sent to the server for verification. To ensure data security, the first and second verification results need to be encrypted to ensure that the data is not intercepted or deciphered by third parties during transmission. The encrypted first and second verification results are encapsulated into data packets, each data packet containing metadata including but not limited to user identifier, verification type, verification timestamp, and encryption key. The data packets are then sent from the local device to the server via a secure network protocol. During network transmission, the integrity and encryption status of the data packets are continuously monitored to prevent data modification en route. Before receiving the data packets, the server can first pass them through a load balancer and firewall to ensure that the data packets are evenly distributed to processing units and that the data source is verified to prevent unauthorized access.

[0056] After receiving the data packet containing the first verification result and the second verification result, the server decrypts the data packet using the corresponding decryption key, parses out the specific first verification result and the second verification result, verifies the first verification result and the second verification result, and returns the verification result to the client.

[0057] If the verification results show that both the first and second verification results pass the server's verification, the target object is determined to be a live entity. After confirming that the target object is a live entity, the client can perform a series of pre-set security operations, such as unlocking the device, allowing login, confirming payment, and opening secure access control. The prerequisite for the above security operations is that the verification results clearly indicate that the target object is a real live entity, thereby ensuring the security and effectiveness of subsequent operations.

[0058] The above verification results not only validate the target object's biometrics but also ensure that the biometrics are dynamic, real-time, and authentic within a specific context, thus effectively resisting various non-liveness detection methods, including injection attacks, video playback, masking, and AI simulation. The close collaboration between the client and server, through efficient data transmission and accurate verification feedback, constitutes a highly secure and user-friendly liveness detection process.

[0059] Based on steps S31 to S34 above, a first verification result is obtained by interactively verifying the specified actions of the target object, and a second verification result is obtained by interactively verifying the color change response of a specified part of the target object. The first and second verification results are then sent to the server for verification. Subsequently, the verification result from the server is received. When the verification result shows that both the first and second verification results pass the server's verification, the target object is determined to be a live object. Thus, by integrating the specified action verification and the specified part color change response verification, the security of the biometric system is effectively improved, while optimizing the user experience, reducing the detection implementation cost, and improving environmental adaptability and decision accuracy. This solves the technical problems of low security and high detection implementation cost of the liveness detection methods provided in related technologies.

[0060] The liveness detection method in the embodiments of this application will be further described below.

[0061] In an optional embodiment, in step S31, a first biometric verification method is used to verify the target object for a specified action, and the first verification result is obtained, including:

[0062] Step S311: Under the first biometric verification method, acquire an image of the specified area captured by the image acquisition component;

[0063] Step S312: Perform a specified action verification on the target object based on the image of the specified part to obtain the first verification result.

[0064] The aforementioned image acquisition component can be a camera component in the client or a dedicated biometric recognition camera. Taking blink verification as the first biometric verification method, the image acquisition component can capture the facial image of the target object and analyze and verify the blinking action performed by the target object based on the facial image to obtain the first verification result, namely the blink verification result.

[0065] Specifically, in the first biometric verification method, the camera component is activated and aimed at the target's face. Depending on the ambient lighting and the target's position, the camera component can automatically or manually adjust parameters such as exposure, white balance, and focus to obtain clear, high-quality facial images. The camera component can continuously capture multiple frames of facial images, encompassing all facial movements, including blinking.

[0066] For example, in the process of verifying a target object for a specified action based on an image of a specified part, the image of the specified part can first be preprocessed, such as cropping, scaling, grayscale conversion, or noise reduction, to focus on the facial region and improve the accuracy of subsequent steps. Then, facial features, especially the eye region, are extracted based on the preprocessing results, specifically using face detection and eye localization techniques from related technologies. Blinking is detected by analyzing changes in the eyes in the image sequence, for example, by comparing changes in eye shape, size, and position between several consecutive frames. A preset threshold condition can be used to determine whether the blinking action is obvious or continuous to avoid false alarms. If the blinking feature meets the preset threshold condition, the first verification result indicates that the blinking action of the target object has been detected; otherwise, the blinking action of the target object has not been detected.

[0067] The first verification result is derived from the detection and analysis of blinking actions, indicating whether the target object has performed the specified blinking action. If the first verification result indicates that one or more blinking events meeting preset threshold conditions have been successfully detected, it can be preliminarily determined that the target object is a living being capable of autonomously performing dynamic actions. If the first verification result indicates that no blinking actions meeting preset threshold conditions have been detected, or if the detected behavior does not conform to the normal pattern of a living being, it can be determined that the target object is a static image, video recording, or other simulation of a non-living being. The preset threshold conditions include, but are not limited to, blinking frequency threshold, blinking duration threshold, and number of consecutive blinks.

[0068] Based on the above optional embodiments, by acquiring an image of a specified part captured by the image acquisition component under the first biometric verification method, and then performing a specified action verification on the target object based on the image of the specified part, a first verification result is obtained. This allows for a preliminary determination of whether the target object is a real living body, laying the foundation for further interactive color change response verification. At the same time, it can effectively filter out most non-living verification attempts, improving the effectiveness and security of the subsequent verification process.

[0069] In an optional embodiment, the liveness detection method in this application further includes:

[0070] In response to the first verification result indicating that no specified action of the target object was detected, a first prompt message is issued, wherein the first prompt message is used to indicate that the verification of the specified action of the target object has failed.

[0071] Specifically, when the initial verification result indicates that the specified action of the target object was not detected, i.e., the blink verification failed, the user should be promptly informed of this situation, guiding them to re-verify or take other measures. For example, if it is determined that the target object did not complete the expected blinking action, or the blinking action does not meet the standards for liveness verification, a clear and user-friendly initial prompt message can be constructed based on the reason for the verification failure. For example, "Verification failed. Please try again, ensuring your eyes are completely closed before opening them." This initial prompt message ensures that the user can quickly understand and react.

[0072] The initial prompt message can be displayed through the client's graphical user interface or broadcast via audio feedback. When displayed, the prompt message should be centered on the screen or within the user's line of sight to ensure the user does not miss it. When using voice feedback, ensure the volume is moderate and the speech is calm and easy to understand.

[0073] While issuing the first prompt message, a "retry" button or a timer to automatically restart the verification process can also be set. It should be noted that the design of the retry mechanism should take into account the balance between user experience and security, which is not limited in the embodiments of this application.

[0074] Based on the above optional embodiments, in response to the first verification result indicating that the specified action of the target object was not detected, a first prompt message is issued. The first prompt message is used to indicate that the verification of the specified action of the target object has failed. This not only informs the user of the verification failure, but also efficiently guides the user to correctly re-perform the blink verification, thereby improving the overall efficiency of the biometric system and the user experience.

[0075] In an optional embodiment, in step S31, a second biometric verification method is used to verify a specified part of the target object, and the second verification result includes:

[0076] Step S313: In response to the first verification result indicating that a specified action of the target object has been detected, under the second biometric verification method, a random color sequence instruction sent by the server is received, wherein the random color sequence instruction is used to control the image display component to display multiple color combinations;

[0077] Step S314: Within a preset distance range, the target object is verified at a specified location based on a random color sequence instruction to obtain a second verification result. The preset distance range is used to control the distance between the target object and the image display component.

[0078] When the first verification result detects a specified action of the target object, such as detecting the target object blinking, a second biometric verification method is further used to perform interactive color change response verification. By detecting the target object's facial response to a random color sequence, its liveness status is further confirmed, enhancing the security of the entire biometric identification process.

[0079] During interactive color change response verification, a request can be sent to the server requesting a random color sequence command for verification. The server responds by sending the random color sequence command, which the client receives and parses to obtain detailed information. After parsing the random color sequence command, the changes in the color sequence are used to detect the target object's facial reaction, thus obtaining a second verification result.

[0080] Specifically, based on the received random color sequence instructions, the image display component is controlled, such as controlling the device screen to display multiple color combinations specified in the random color sequence instructions. These multiple color combinations can contain different colors, such as blue, green, yellow, red, and pink. The random color sequence instructions can also include the order and duration of each color display. For example, based on the random color sequence instructions, seven colors are randomly displayed on the client's device screen each time, ensuring that it is difficult for attackers to predict and simulate.

[0081] To ensure that multiple color combinations are effectively mapped onto the target subject's face, a preset distance range needs to be set. The target subject needs to be verified within this preset distance range to ensure that the face receives sufficient color illumination while avoiding the inability to capture color changes due to excessive distance. Setting the preset distance range is crucial to ensuring the effectiveness of interactive color change response verification. Specifically, it can be precisely adjusted based on the characteristics of the client device's image display components (such as brightness and color saturation), the performance of the image acquisition components (such as camera focusing distance and sensitivity), and ambient lighting conditions. Typically, a preset distance range between 10 and 30 centimeters ensures that color combinations are fully mapped onto the face while avoiding image blurring or overexposure due to excessive distance.

[0082] Based on the above optional embodiments, in response to the first verification result indicating that a specified action of the target object has been detected, under the second biometric verification method, a random color sequence instruction sent by the server is received, and then within a preset distance range, the specified part of the target object is verified based on the random color sequence instruction to obtain the second verification result. This further improves the security of the liveness detection system and ensures the accurate verification of the target object's identity.

[0083] In an optional embodiment, in step S314, within a preset distance range, the target object is verified at a specified location based on a random color sequence command to obtain a second verification result, including:

[0084] Step S3141: Within a preset distance range, acquire multiple frames of images of a specified part of the target object captured by the image acquisition component;

[0085] Step S3142: Verify the target object at a specified location based on the random color sequence command and multiple frames of specified location images to obtain a second verification result.

[0086] Specifically, when the target object is within a preset distance range, the image display component begins to display a series of random colors based on the random color sequence instructions sent by the server. These colors are then mapped onto the target object's face. During the color mapping process, the image acquisition component continuously captures multiple frames of facial images. The number and frequency of captured frames must be high enough to ensure that the entire color change process is captured.

[0087] After collecting multiple frames of facial images, the second verification result is obtained by analyzing the target object's facial response to a random color sequence. By analyzing multiple frames of facial images, the pattern of facial color changes in response to screen color is identified. Then, the color changes of the target object's face are matched with random color sequence commands to determine whether the facial color changes match the screen color change commands. If the color changes of the target object's face match the random color sequence commands displayed on the screen, it indicates that the target object is a living entity capable of responding to environmental changes in real time.

[0088] Based on the above optional embodiments, by acquiring multiple frames of images of a specified part of the target object captured by the image acquisition component within a preset distance range, and then verifying the specified part of the target object based on the random color sequence instruction and the multiple frames of images of the specified part, a second verification result is obtained. This can effectively perform liveness verification based on random color sequences, further enhance the security of the biometric system, and further accurately distinguish whether the target object is a real living person in complex scenarios.

[0089] In an optional embodiment, in step S3142, the target object is verified based on a random color sequence command and multiple frames of images of specified parts to obtain a second verification result, including:

[0090] The target inter-frame image feature difference model is used to calculate the inter-frame image feature difference of multiple frames of specified parts, and the calculation results are obtained. The target inter-frame image feature difference model is used to identify the color difference between the specified parts of adjacent frames.

[0091] The calculation results are compared with the color change of the random color sequence command to obtain the second verification result.

[0092] Specifically, the aforementioned target frame image feature difference model is trained on a large amount of sample data and can accurately identify and distinguish the differences in color changes between real living faces and other non-living faces. The target frame image feature difference model can utilize deep learning technology to calculate the differences between image features of adjacent frames, such as color distribution, texture changes, and brightness fluctuations, thereby simulating the human visual system's ability to perceive and recognize color changes.

[0093] When calculating the inter-frame image feature difference, facial features, such as color information, are first extracted from each frame of the face image. Then, the feature data of adjacent frames are compared to determine the color change pattern between adjacent frames, such as the trend of color value change of a feature point over time. The color change pattern is then converted into specific numerical indicators, such as color difference, rate of change, and range of change, to obtain the calculation result. The calculation result reflects the degree to which the target object's face responds to random color sequence commands across multiple frames.

[0094] The color change pattern in the calculated results is compared with the random color sequence command issued by the server to determine if they match. If the color change pattern of the target object's face matches the random color sequence command displayed on the screen, and the change process is natural and smooth, consistent with the characteristics of a real living object, then the target object verification is confirmed to be successful. Color features are extracted from the target object's facial image captured by the camera to quantify the facial color. These extracted color features are then compared with the color features in the random color sequence command displayed on the screen to check if they change in the same order and pattern. By analyzing the smoothness of color changes between adjacent frames, as well as the speed and amplitude of color transitions, it is determined whether the color change is natural and smooth, consistent with the characteristics of a real living object. If the color changes do not match, or the change process appears unnatural or asynchronous, it indicates that the target object is not a real living object, and the verification fails.

[0095] Based on the above optional embodiments, by using the target inter-frame image feature difference model to calculate the inter-frame image feature difference of multiple frames of specified parts, the calculation result is obtained. Then, the calculation result is compared with the color change of the random color sequence instruction to obtain the second verification result. This can improve the accuracy and robustness of the verification and further enhance the security and accuracy of the liveness detection system.

[0096] In an optional embodiment, the liveness detection method in this application further includes:

[0097] Obtain the training dataset, which includes: illumination data, epidermal color data of a specified area, and environmental data;

[0098] The initial inter-frame image feature difference model is trained using the training dataset to obtain the target inter-frame image feature difference model.

[0099] In order for the target inter-frame image feature difference model to accurately identify and distinguish the differences in color changes between real living and non-living objects, especially under different lighting conditions, skin color of specified parts, and environmental background, it is necessary to construct a comprehensive training dataset and train the initial inter-frame image feature difference model based on this training dataset to obtain the final target inter-frame image feature difference model.

[0100] The construction of the aforementioned training dataset is fundamental to model training. The training dataset includes illumination data, skin color data for specified body parts, and environmental data, enabling the model to learn its ability to recognize color changes under various complex conditions. Specifically, illumination data can be obtained by collecting image samples under different lighting conditions, including indoor lighting, natural light, backlighting, and direct light, to cover various lighting environments in daily biometric verification processes. Skin color data for specified body parts can be obtained by collecting images with diverse skin colors, ensuring that the target frame image feature difference model can accurately identify and process skin color changes in different groups of people under different lighting conditions. Environmental data needs to consider the impact of different backgrounds and environmental factors on color recognition; for example, capturing images in various indoor and outdoor environments, including different background colors, textures, and lighting angles.

[0101] After obtaining the training dataset, data preprocessing can be performed. Data preprocessing is a key step in improving model training performance and includes, but is not limited to, the following operations: image normalization, data augmentation, and labeling. Specifically, image normalization adjusts sample images to the same size and format, performs grayscale conversion, color space transformation, etc., so that the model can focus on color change features. Data augmentation increases the diversity of training samples through techniques such as rotation, scaling, flipping, or color adjustment, helping the model's generalization ability and making it more robust in real-world applications. Labeling involves labeling each image sample with whether it represents a real living organism, as well as the corresponding lighting conditions and environmental background, facilitating the model's learning of relevant features.

[0102] Furthermore, the initial inter-frame image feature difference model is trained using the preprocessed training dataset to construct a target inter-frame image feature difference model capable of effectively identifying color change features of specified parts under different lighting and environmental conditions. Training the target inter-frame image feature difference model is an ongoing process that requires continuous adjustments based on actual application scenarios and user feedback to achieve accurate validation results.

[0103] Based on the above optional embodiments, by acquiring a training dataset and then using the training dataset to train the initial inter-frame image feature difference model, a target inter-frame image feature difference model is obtained for calculating inter-frame image feature differences, thereby further improving the security and accuracy of the liveness detection system.

[0104] In an optional embodiment, the liveness detection method in this application further includes:

[0105] In a real-world environment, color performance tests were conducted on various preset solid colors to obtain color test results.

[0106] Multiple color combinations were determined based on the color test results.

[0107] To ensure the effectiveness and reliability of interactive behavioral feature verification and interactive color change response verification in real-world environments, especially considering the impact of different lighting conditions, screen characteristics, and other factors on color recognition, it is necessary to conduct color performance tests on a variety of preset pure colors in real-world environments to determine the color combinations suitable as verification sequences.

[0108] The preset pure colors mentioned above can be red, blue, green, yellow, pink, etc. These colors have high distinguishability in the color space and can produce obvious color changes under different lighting conditions. Furthermore, a series of real-world test scenarios are set up, including indoor and outdoor environments, different times of day (such as early morning, noon, and evening), and different lighting conditions (such as natural light, incandescent lamps, fluorescent lamps, and backlighting environments), to comprehensively cover the verification environment.

[0109] During color performance testing, the device screen can be sequentially displayed with the aforementioned preset pure colors under each test environment to simulate the execution of random color sequence commands during verification. Multiple frames of images of different target objects' faces displayed on the screen with different pure colors are captured using an image acquisition component, and parameters such as ambient lighting conditions, screen brightness, and color depth are recorded. The above steps are repeated to test the performance of each preset pure color under different environments and target objects, and the color test results are collected. The color test results include, but are not limited to, data on the clarity of color changes, color saturation, contrast, and the naturalness of color response.

[0110] After obtaining the color test results, data analysis can be performed to identify colors that produce significant and discernible color changes in most environments, while also demonstrating good performance on various target objects. This analysis process may involve statistically analyzing indicators such as the average effect of color changes, the range of changes, and stability under different environments.

[0111] Based on the color test results, the color combinations that perform well are selected as multiple color combinations corresponding to the random color sequence instruction. Each color combination contains multiple colors to ensure coverage of a large color space. At the same time, the differences between the colors are large enough to clearly produce color changes on the target object's face, which is convenient for the system to identify and verify.

[0112] Based on the above optional embodiments, color performance tests are conducted on various preset pure colors in a real environment to obtain color test results, and then various color combinations are determined based on the color test results.

[0113] In an optional embodiment, the liveness detection method in this application further includes:

[0114] In a real-world environment, based on the distance between the target object and the image display components, different light color mapping tests are performed on a specified part of the target object to obtain the mapping test results;

[0115] In response to the mapping test results indicating that the mapping effect of the target object on the color of light at a specified part does not meet the preset conditions, a second prompt message is issued, wherein the second prompt message is used to prompt the target object to move closer to the image display component.

[0116] Specifically, before the color mapping test, various real-world environments can be selected for testing, including indoor and outdoor environments. Different lighting conditions can be set, such as natural light, indoor lighting, and backlighting. A series of test distances can also be set, such as different distances from near to far from the image display component to the specified part of the target object.

[0117] At a preset distance, the image display component displays a series of preset light colors, which can cover a wide color range. The image acquisition component captures facial images of the target object under each light color, while simultaneously recording parameters such as test distance, lighting conditions, and screen brightness. The captured facial images are analyzed to evaluate the mapping effect of the target object's face on different light colors, including but not limited to the clarity of color changes, color saturation, and contrast, thereby obtaining the mapping test results.

[0118] When the mapping test results indicate that the mapping effect of the target object's designated area on the color of light does not meet the preset conditions, a second prompt message is issued to prompt the target object to move closer to the image display component. The preset conditions can be lighting conditions, sharpness conditions, etc., and the second prompt message can be conveyed through voice, text, or a graphical user interface to ensure that the user can clearly understand and respond.

[0119] Based on the above optional embodiments, in a real environment, different light color mapping tests are performed on a designated part of the target object according to the distance between the target object and the image display component to obtain mapping test results. Then, in response to the mapping test results showing that the mapping effect of the designated part of the target object on the light color does not meet the preset conditions, a second prompt message is issued to prompt the target object to move closer to the image display component, thereby further improving the accuracy of liveness detection and user experience.

[0120] Figure 4 This is a flowchart of another liveness detection method according to an embodiment of this application, such as... Figure 4 As shown, the method includes the following steps:

[0121] Step S41: Receive the first verification result and the second verification result from the client. The first verification result is obtained by verifying the target object's specified action using the first biometric verification method, and the second verification result is obtained by verifying the target object's specified part using the second biometric verification method. The first biometric verification method is used to perform interactive behavioral feature verification on the target object's specified action, and the second biometric verification method is used to perform interactive color change response verification on the target object's specified part.

[0122] Step S42: Verify the first verification result and the second verification result to obtain a verification result, wherein the verification result is used to indicate whether both the first verification result and the second verification result pass the verification.

[0123] Step S43: Send the verification result back to the client.

[0124] Based on steps S41 to S43 above, by receiving a first verification result and a second verification result from the client, the first verification result is obtained by verifying the target object's specified action using a first biometric verification method, and the second verification result is obtained by verifying the target object's specified body part using a second biometric verification method. The first biometric verification method is used to perform interactive behavioral feature verification of the target object's specified action, and the second biometric verification method is used to perform interactive color change response verification of the target object's specified body part. The first verification result and the second verification result are then verified to obtain a verification result, which indicates whether both the first verification result and the second verification result have passed the verification. Finally, the verification result is fed back to the client. Thus, by integrating specified action verification and specified body part color change response verification, the security of the biometric system is effectively improved, while the user experience is optimized, the detection implementation cost is reduced, and the environmental adaptability and decision-making accuracy are improved. This solves the technical problems of low security and high detection implementation cost of the liveness detection methods provided in related technologies.

[0125] Figure 5 This is a flowchart of another liveness detection method according to an embodiment of this application, such as... Figure 5 As shown, the method includes the following steps:

[0126] Step S51: Using a first biometric verification method, the pet is verified for a specified action to obtain a first verification result; and using a second biometric verification method, the pet is verified for a specified body part to obtain a second verification result. The first biometric verification method is used to perform interactive behavioral feature verification of the pet's specified action, and the second biometric verification method is used to perform interactive color change response verification of the pet's specified body part.

[0127] Step S52: Send the first verification result and the second verification result to the server, wherein the server is used to verify the first verification result and the second verification result;

[0128] Step S53: Receive the verification result from the server, wherein the verification result is used to indicate whether both the first verification result and the second verification result have passed the server's verification.

[0129] Step S54: In response to the verification results showing that both the first verification result and the second verification result have passed the server's verification, the pet is determined to be alive.

[0130] In step S55, in response to the pet's designated body part image matching the image pre-stored in the access control system, the access control is unlocked to allow the pet to enter.

[0131] Based on steps S51 to S55 above, a first biometric verification method is used to verify the pet's specified actions, resulting in a first verification result. A second biometric verification method is used to verify the pet's specified body parts, resulting in a second verification result. The first biometric verification method is used for interactive behavioral feature verification of the pet's specified actions, and the second biometric verification method is used for interactive color change response verification of the pet's specified body parts. The first and second verification results are then sent to the server. The server then receives the verification results. When the verification results show that both the first and second verification results pass the server's verification, the pet is determined to be alive. When the image of the pet's specified body part matches the image pre-stored in the access control system, the access control is unlocked to allow the pet to enter. Thus, by integrating specified action verification and specified body part color change response verification, the security of the access control system is effectively improved, while user experience is optimized, detection implementation costs are reduced, and environmental adaptability and decision-making accuracy are improved. This solves the technical problems of low security and high detection implementation costs associated with existing liveness detection methods.

[0132] Figure 6This is a flowchart of another liveness detection method according to an embodiment of this application, such as... Figure 6 As shown, the method includes the following steps:

[0133] Step S61: Obtain a liveness detection request through the first application programming interface. The request data carried in the liveness detection request includes: a first verification result and a second verification result. The first verification result is obtained by verifying the target object with a specified action using a first biometric verification method. The second verification result is obtained by verifying the target object with a specified part using a second biometric verification method. The first biometric verification method is used to perform interactive behavioral feature verification of the specified action of the target object. The second biometric verification method is used to perform interactive color change response verification of the specified part of the target object.

[0134] Step S62: Return a liveness detection response through the second application programming interface. The response data carried in the liveness detection response includes: a verification result, which indicates whether both the first verification result and the second verification result have passed the verification.

[0135] Based on steps S61 to S62 above, a liveness detection request is obtained through the first application programming interface (API). The request data carried in the liveness detection request includes: a first verification result and a second verification result. The first verification result is obtained by verifying the target object's specified action using a first biometric verification method, and the second verification result is obtained by verifying the target object's specified body part using a second biometric verification method. The first biometric verification method is used to perform interactive behavioral feature verification of the target object's specified action, and the second biometric verification method is used to perform interactive color change response verification of the target object's specified body part. Then, a liveness detection response is returned through the second API. The response data carried in the liveness detection response includes: a verification result, which indicates whether both the first verification result and the second verification result have passed the verification. Thus, by integrating the specified action verification and the specified body part color change response verification, the security of the biometric system is effectively improved, while the user experience is optimized, the detection implementation cost is reduced, and the environmental adaptability and decision accuracy are improved. This solves the technical problems of low security and high detection implementation cost of the liveness detection methods provided in related technologies.

[0136] Figure 7 This is a flowchart of another liveness detection method according to an embodiment of this application, such as... Figure 7 As shown, the method includes the following steps:

[0137] Step S71: Obtain the currently input liveness detection dialogue request. The request data carried in the liveness detection dialogue request includes: a first verification result and a second verification result. The first verification result is obtained by verifying the target object's specified actions using a first biometric verification method. The second verification result is obtained by verifying the target object's specified parts using a second biometric verification method. The first biometric verification method is used to perform interactive behavioral feature verification on the target object's specified actions. The second biometric verification method is used to perform interactive color change response verification on the target object's specified parts.

[0138] Step S72: In response to the liveness detection dialog request, return a liveness detection dialog response, wherein the information carried in the liveness detection dialog response includes: verification result, which is used to indicate whether the first verification result and the second verification result both pass the verification;

[0139] Step S73: Display the verification results within the graphical user interface.

[0140] Based on steps S71 to S73 above, by acquiring the currently input liveness detection dialogue request, the request data carried in the liveness detection dialogue request includes: a first verification result and a second verification result. The first verification result is obtained by verifying the target object's specified action using a first biometric verification method, and the second verification result is obtained by verifying the target object's specified body part using a second biometric verification method. The first biometric verification method is used to perform interactive behavioral feature verification of the target object's specified action, and the second biometric verification method is used to perform interactive color change response verification of the target object's specified body part. In response to the liveness detection dialogue request, a liveness detection dialogue reply is returned. The information carried in the liveness detection dialogue reply includes: a verification result, which indicates whether both the first and second verification results have passed the verification. Finally, the verification result is displayed in the graphical user interface. Thus, by integrating specified action verification and specified body part color change response verification, the security of the biometric system is effectively improved, while optimizing the user experience, reducing the detection implementation cost, and improving environmental adaptability and decision-making accuracy. This solves the technical problems of low security and high detection implementation cost of the liveness detection methods provided in related technologies.

[0141] Figure 8 This is a flowchart of another liveness detection method according to an embodiment of this application, such as... Figure 8 As shown, the method includes the following steps:

[0142] Step S81: In response to the input command applied to the operation interface, display the first verification result and the second verification result on the operation interface;

[0143] Step S82: In response to the processing command applied to the operation interface, the verification result is displayed on the operation interface; wherein, the first verification result is obtained by verifying the target object with a specified action using the first biometric verification method, and the second verification result is obtained by verifying the target object with a specified part using the second biometric verification method. The first biometric verification method is used to perform interactive behavioral feature verification of the target object's specified action, and the second biometric verification method is used to perform interactive color change response verification of the target object's specified part. The verification result is used to indicate whether both the first verification result and the second verification result pass the verification.

[0144] Based on steps S81 to S82 above, by responding to input commands applied to the operation interface, the first verification result and the second verification result are displayed on the operation interface. Then, by responding to processing commands applied to the operation interface, the verification result is displayed on the operation interface. The first verification result is obtained by verifying the target object's specified action using the first biometric verification method. The second verification result is obtained by verifying the target object's specified location using the second biometric verification method. The first biometric verification method is used for interactive behavioral feature verification of the target object's specified action, and the second biometric verification method is used for interactive color change response verification of the target object's specified location. The verification result indicates whether both the first and second verification results have passed verification. Thus, by integrating specified action verification and specified location color change response verification, the security of the biometric system is effectively improved, while simultaneously optimizing the user experience, reducing detection implementation costs, and improving environmental adaptability and decision-making accuracy. This solves the technical problems of low security and high detection implementation costs associated with existing liveness detection methods in related technologies.

[0145] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, use and processing of the relevant data must comply with the relevant laws, regulations and standards of the relevant countries and regions, and corresponding operation portals are provided for users to choose to authorize or refuse.

[0146] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0147] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods according to the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, they can also be implemented by hardware. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0148] According to an embodiment of this application, a liveness detection device for implementing the above-described liveness detection method is also provided. Figure 9 This is a structural block diagram of a liveness detection device according to an embodiment of this application, such as... Figure 9 As shown, the device includes:

[0149] The verification module 901 is used to verify a specified action of a target object using a first biometric verification method to obtain a first verification result, and to verify a specified part of the target object using a second biometric verification method to obtain a second verification result. The first biometric verification method is used to perform interactive behavioral feature verification of the specified action of the target object, and the second biometric verification method is used to perform interactive color change response verification of the specified part of the target object.

[0150] The sending module 902 is used to send the first verification result and the second verification result to the server, wherein the server is used to verify the first verification result and the second verification result;

[0151] The receiving module 903 is used to receive the verification result from the server, wherein the verification result is used to indicate whether both the first verification result and the second verification result have passed the server's verification.

[0152] The determination module 904 is used to determine that the target object is a living person in response to the verification results showing that both the first verification result and the second verification result have passed the server's verification.

[0153] Optionally, the verification module 901 is further configured to: acquire an image of a specified part captured by the image acquisition component under the first biometric verification method; perform a specified action verification on the target object based on the image of the specified part, and obtain a first verification result.

[0154] Optionally, the liveness detection device further includes: a prompting module 905, used to issue a first prompting message in response to a first verification result indicating that no specified action of the target object was detected, wherein the first prompting message is used to indicate that the verification of the specified action of the target object failed.

[0155] Optionally, the verification module 901 is further configured to: in response to the first verification result indicating that a specified action of the target object has been detected, in the second biometric verification mode, receive a random color sequence instruction sent by the server, wherein the random color sequence instruction is used to control the image display component to display multiple color combinations; within a preset distance range, verify a specified part of the target object based on the random color sequence instruction to obtain a second verification result, wherein the preset distance range is used to control the distance between the target object and the image display component.

[0156] Optionally, the verification module 901 is further configured to: acquire multiple frames of images of a specified part of the target object captured by the image acquisition component within a preset distance range; verify the specified part of the target object based on the random color sequence instruction and the multiple frames of images of the specified part, and obtain a second verification result.

[0157] Optionally, the verification module 901 is further configured to: calculate the inter-frame image feature difference for multiple frames of specified parts using the target inter-frame image feature difference model, and obtain the calculation result, wherein the target inter-frame image feature difference model is used to identify the color difference between adjacent frames of specified parts; and compare the calculation result with the color change of the random color sequence instruction to obtain the second verification result.

[0158] Optionally, the liveness detection device further includes: an acquisition module 906 for acquiring a training dataset, wherein the training dataset includes: illumination data, epidermal color data of a specified area, and environmental data; and a training module 907 for training an initial inter-frame image feature difference model using the training dataset to obtain a target inter-frame image feature difference model.

[0159] Optionally, the liveness detection device further includes: a testing module 908, used to perform color performance tests on multiple preset pure colors in a real environment to obtain color test results; and a determination module 904, used to determine multiple color combinations based on the color test results.

[0160] Optionally, the test module 908 is further configured to perform different light color mapping tests on a designated part of the target object in a real environment based on the distance between the target object and the image display component, and obtain mapping test results; the prompt module 905 is further configured to issue a second prompt message in response to the mapping test results indicating that the mapping effect of the designated part of the target object on the light color does not meet the preset conditions, wherein the second prompt message is used to prompt the target object to move closer to the image display component.

[0161] It should be noted that the verification module 901, sending module 902, receiving module 903, and determining module 904 correspond to steps S31 to S34 in the above embodiments. The four modules and their corresponding steps implement the same instances and application scenarios, but are not limited to the content disclosed in the above embodiments. It should be noted that the above modules or units can be hardware or software components stored in memory (e.g., memory 104) and processed by one or more processors (e.g., processors 102a, 102b, ..., 102n). The above modules can also run as part of a device in the computer terminal 10 provided in the embodiments of this application.

[0162] Figure 10 This is a structural block diagram of another liveness detection device according to an embodiment of this application, such as... Figure 10 As shown, the device includes:

[0163] The receiving module 1001 is used to receive a first verification result and a second verification result from the client. The first verification result is obtained by verifying the target object by performing a specified action using a first biometric verification method. The second verification result is obtained by verifying the target object by performing a specified part using a second biometric verification method. The first biometric verification method is used to perform interactive behavioral feature verification of the specified action of the target object. The second biometric verification method is used to perform interactive color change response verification of the specified part of the target object.

[0164] The verification module 1002 is used to verify the first verification result and the second verification result to obtain a verification result, wherein the verification result is used to indicate whether the first verification result and the second verification result both pass the verification.

[0165] Feedback module 1003 is used to send the verification results back to the client.

[0166] It should be noted that the receiving module 1001, verification module 1002, and feedback module 1003 correspond to steps S41 to S43 in the above embodiments. The three modules and their corresponding steps implement the same instances and application scenarios, but are not limited to the content disclosed in the above embodiments. It should be noted that the above modules or units can be hardware or software components stored in memory (e.g., memory 104) and processed by one or more processors (e.g., processors 102a, 102b, ..., 102n). The above modules can also run as part of a device in the computer terminal 10 provided in the embodiments of this application.

[0167] Figure 11 This is a structural block diagram of another liveness detection device according to an embodiment of this application, such as... Figure 11 As shown, the device includes:

[0168] The verification module 1101 is used to verify a pet's specified actions using a first biometric verification method to obtain a first verification result, and to verify a pet's specified body parts using a second biometric verification method to obtain a second verification result. The first biometric verification method is used to perform interactive behavioral feature verification of the pet's specified actions, and the second biometric verification method is used to perform interactive color change response verification of the pet's specified body parts.

[0169] The sending module 1102 is used to send the first verification result and the second verification result to the server, wherein the server is used to verify the first verification result and the second verification result;

[0170] The receiving module 1103 is used to receive the verification result from the server, wherein the verification result is used to indicate whether the first verification result and the second verification result both pass the server's verification.

[0171] The determination module 1104 is used to determine that the pet is alive in response to the verification result showing that both the first verification result and the second verification result have passed the server's verification.

[0172] The processing module 1105 is used to unlock the access control system to allow the pet to enter in response to a matching image of a specified part of the pet with an image pre-stored in the access control system.

[0173] It should be noted that the verification module 1101, sending module 1102, receiving module 1103, determining module 1104, and processing module 1105 mentioned above correspond to steps S51 to S55 in the above embodiments. The five modules and their corresponding steps implement the same instances and application scenarios, but are not limited to the content disclosed in the above embodiments. It should be noted that the above modules or units can be hardware or software components stored in memory (e.g., memory 104) and processed by one or more processors (e.g., processors 102a, 102b, ..., 102n). The above modules can also run as part of a device in the computer terminal 10 provided in the embodiments of this application.

[0174] Figure 12 This is a structural block diagram of another liveness detection device according to an embodiment of this application, such as... Figure 12 As shown, the device includes:

[0175] The acquisition module 1201 is used to acquire a liveness detection request through a first application programming interface. The request data carried in the liveness detection request includes a first verification result and a second verification result. The first verification result is obtained by verifying a specified action of the target object using a first biometric verification method. The second verification result is obtained by verifying a specified part of the target object using a second biometric verification method. The first biometric verification method is used to perform interactive behavioral feature verification of the specified action of the target object. The second biometric verification method is used to perform interactive color change response verification of the specified part of the target object.

[0176] The return module 1202 is used to return a liveness detection response through the second application programming interface. The response data carried in the liveness detection response includes: a verification result, which indicates whether both the first verification result and the second verification result have passed the verification.

[0177] It should be noted that the acquisition module 1201 and return module 1202 correspond to steps S61 to S62 in the above embodiments. The two modules and their corresponding steps implement the same instances and application scenarios, but are not limited to the content disclosed in the above embodiments. It should be noted that the above modules or units may be hardware or software components stored in memory (e.g., memory 104) and processed by one or more processors (e.g., processors 102a, 102b, ..., 102n). The above modules may also run as part of a device in the computer terminal 10 provided in the embodiments of this application.

[0178] Figure 13 This is a structural block diagram of another liveness detection device according to an embodiment of this application, such as... Figure 13 As shown, the device includes:

[0179] The acquisition module 1301 is used to acquire the currently input liveness detection dialogue request. The request data carried in the liveness detection dialogue request includes: a first verification result and a second verification result. The first verification result is obtained by verifying the target object for a specified action using a first biometric verification method. The second verification result is obtained by verifying the target object for a specified part using a second biometric verification method. The first biometric verification method is used to perform interactive behavioral feature verification on the specified action of the target object. The second biometric verification method is used to perform interactive color change response verification on the specified part of the target object.

[0180] Return module 1302 is used to respond to the liveness detection dialogue request and return a liveness detection dialogue response, wherein the information carried in the liveness detection dialogue response includes: verification result, which is used to indicate whether the first verification result and the second verification result have both passed the verification;

[0181] Display module 1303 is used to display the verification results within the graphical user interface.

[0182] It should be noted that the acquisition module 1301, return module 1302, and display module 1302 correspond to steps S71 to S73 in the above embodiments. The three modules and their corresponding steps implement the same instances and application scenarios, but are not limited to the content disclosed in the above embodiments. It should be noted that the above modules or units may be hardware or software components stored in memory (e.g., memory 104) and processed by one or more processors (e.g., processors 102a, 102b, ..., 102n). The above modules may also be part of a device and run in the computer terminal 10 provided in the embodiments of this application.

[0183] Figure 14 This is a structural block diagram of another liveness detection device according to an embodiment of this application, such as... Figure 14 As shown, the device includes:

[0184] The first display module 1401 is used to respond to input commands applied to the operation interface and display the first verification result and the second verification result on the operation interface.

[0185] The second display module 1402 is used to respond to processing instructions applied to the operation interface and display the verification results on the operation interface. The first verification result is obtained by verifying the target object with a specified action using a first biometric verification method, and the second verification result is obtained by verifying the target object with a specified part using a second biometric verification method. The first biometric verification method is used to perform interactive behavioral feature verification of the target object's specified action, and the second biometric verification method is used to perform interactive color change response verification of the target object's specified part. The verification result is used to indicate whether both the first verification result and the second verification result have passed the verification.

[0186] It should be noted that the first display module 1401 and the second display module 1402 mentioned above correspond to steps S81 to S82 in the above embodiments. The two modules and the corresponding steps implement the same instances and application scenarios, but are not limited to the content disclosed in the above embodiments. It should be noted that the above modules or units can be hardware components or software components stored in memory (e.g., memory 104) and processed by one or more processors (e.g., processors 102a, 102b, ..., 102n). The above modules can also run as part of the device in the computer terminal 10 provided in the embodiments of this application.

[0187] Embodiments of this application may provide a liveness detection system, comprising: a client, configured to send a first verification result and a second verification result, wherein the first verification result is obtained by verifying a specified action of a target object using a first biometric verification method, and the second verification result is obtained by verifying a specified part of the target object using a second biometric verification method; the first biometric verification method is used to perform interactive behavioral feature verification of the specified action of the target object, and the second biometric verification method is used to perform interactive color change response verification of the specified part of the target object; a server, connected to the client, configured to verify the first verification result and the second verification result to obtain a verification result, and to feed back the verification result to the client, wherein the verification result is used to indicate whether both the first verification result and the second verification result have passed verification; the client is also configured to output the verification result.

[0188] Embodiments of this application may provide a computer terminal, which may be any computer terminal device in a group of computer terminals. Optionally, in this embodiment, the aforementioned computer terminal may also be replaced by a mobile terminal or other terminal device.

[0189] Optionally, in this embodiment, the computer terminal may be located in at least one of a plurality of network devices in a computer network.

[0190] Optionally, in this embodiment, the computer terminal described above can execute any of the methods described in the above embodiments.

[0191] Optionally, Figure 15 This is a structural block diagram of a computer terminal according to an embodiment of this application. Figure 15 As shown, the computer terminal may include: one or more (only one is shown in the figure) processors 152, memory 154, memory controller, and peripheral interfaces, wherein the peripheral interfaces are connected to a radio frequency module, an audio module, and a display.

[0192] The memory can be used to store software programs and modules, such as the program instructions / modules corresponding to the liveness detection method and apparatus in this application embodiment. The processor executes various functional applications and data processing by running the software programs and modules stored in the memory, thereby realizing the aforementioned liveness detection method. The memory may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory may further include memory remotely located relative to the processor, and these remote memories can be connected to the terminal via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0193] The processor can invoke an executable program stored in memory via a transmission device to execute the method described in any of the above embodiments.

[0194] Those skilled in the art will understand that Figure 15 The structure shown is for illustrative purposes only. The computer terminal can also be a smartphone (such as an Android phone, an iOS phone, etc.), a tablet computer, a PDA, or a mobile Internet device (MID). Figure 15 This does not limit the structure of the aforementioned electronic devices. For example, a computer terminal may also include components that are more... Figure 15 The more or fewer components shown (such as network interfaces, display devices, etc.), or having the same Figure 15 The different configurations shown.

[0195] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be implemented by a program instructing the hardware related to the terminal device. The program can be stored in a computer-readable storage medium, which may include: flash drive, read-only memory (ROM), random access memory (RAM), disk or optical disk, etc.

[0196] Embodiments of this application also provide a computer-readable storage medium. Optionally, in this embodiment, the computer-readable storage medium can be used to store program code executed by the method provided in the above embodiments.

[0197] Optionally, in this embodiment, the storage medium may be located in a computing device.

[0198] Optionally, in this embodiment, the computer-readable storage medium is configured to store an executable program, which, when the executable program is running, controls the device where the computer-readable storage medium is located to execute the method described in any of the above embodiments.

[0199] Embodiments of this application also provide a computer program product. Optionally, in this embodiment, the computer program product may include a computer program that, when executed by a processor, implements the methods provided in the embodiments described above.

[0200] Embodiments of this application also provide a computer program product. Optionally, the computer program product may include a non-volatile computer-readable storage medium, which can be used to store a computer program that, when executed by a processor, implements the method provided in the above embodiments.

[0201] Embodiments of this application also provide a computer program. Optionally, in this embodiment, when the computer program is executed by a processor, it implements the method provided in the above embodiments.

[0202] The sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0203] In the above embodiments of this application, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0204] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling, direct coupling, or communication connection may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0205] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0206] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0207] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard drive, magnetic disk, or optical disk.

[0208] The above description is only a preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A method for detecting liveness, characterized in that, include: A first biometric verification method is used to verify a specified action of the target object to obtain a first verification result, and a second biometric verification method is used to verify a specified part of the target object to obtain a second verification result. The first biometric verification method is used to perform interactive behavioral feature verification of the specified action of the target object, and the second biometric verification method is used to perform interactive color change response verification of the specified part of the target object. The first verification result and the second verification result are sent to the server, wherein the server is used to verify the first verification result and the second verification result; Receive a verification result from the server, wherein the verification result is used to indicate whether both the first verification result and the second verification result have passed the server's verification; In response to the verification result indicating that both the first verification result and the second verification result have passed the server's verification, the target object is determined to be a living being.

2. The liveness detection method according to claim 1, characterized in that, Using the first biometric verification method, a specified action verification is performed on the target object to obtain the first verification result, including: Under the first biometric verification method, an image of a specified area is acquired by the image acquisition component; The target object is subjected to a specified action verification based on the image of the specified part, and the first verification result is obtained.

3. The live detection method according to claim 1, characterized in that, The liveness detection method further includes: In response to the first verification result indicating that no specified action of the target object was detected, a first prompt message is issued, wherein the first prompt message is used to indicate that the verification of the specified action of the target object has failed.

4. The liveness detection method according to claim 1, characterized in that, Using the second biometric verification method, the target object is verified at a specified location, and the second verification result obtained includes: In response to the first verification result indicating that a specified action of the target object has been detected, under the second biometric verification method, a random color sequence instruction sent by the server is received, wherein the random color sequence instruction is used to control the image display component to display multiple color combinations; Within a preset distance range, the target object is verified at a specified location based on the random color sequence instruction to obtain the second verification result, wherein the preset distance range is used to control the distance between the target object and the image display component.

5. The liveness detection method according to claim 4, characterized in that, Within the preset distance range, the target object is verified at a specified location based on the random color sequence instruction, and the second verification result is obtained including: Within the preset distance range, acquire multiple frames of images of specified parts of the target object captured by the image acquisition component; The target object is verified based on the random color sequence instruction and the multi-frame image of the specified part to obtain the second verification result.

6. The liveness detection method according to claim 5, characterized in that, Based on the random color sequence instruction and the multi-frame image of the specified part, the target object is verified at the specified part, and the second verification result is obtained, including: The inter-frame image feature difference model is used to calculate the inter-frame image feature difference of the specified parts of the multi-frame images to obtain the calculation result. The inter-frame image feature difference model is used to identify the color difference between the specified parts of the images in adjacent frames. The calculation result is compared with the random color sequence instruction by performing a color change to obtain the second verification result.

7. The liveness detection method according to claim 6, characterized in that, The liveness detection method further includes: Obtain a training dataset, wherein the training dataset includes: illumination data, epidermal color data of a specified area, and environmental data; The initial inter-frame image feature difference model is trained using the training dataset to obtain the target inter-frame image feature difference model.

8. The liveness detection method according to claim 4, characterized in that, The liveness detection method further includes: In a real-world environment, color performance tests were conducted on various preset solid colors to obtain color test results. The multiple color combinations are determined based on the color test results.

9. The liveness detection method according to claim 4, characterized in that, The liveness detection method further includes: In a real environment, based on the distance between the target object and the image display component, different light color mapping tests are performed on a specified part of the target object to obtain mapping test results; In response to the mapping test result indicating that the mapping effect of the specified part of the target object on the color of light does not meet the preset conditions, a second prompt message is issued, wherein the second prompt message is used to prompt the target object to move closer to the image display component.

10. A method for detecting liveness, characterized in that, include: The system receives a first verification result and a second verification result from the client. The first verification result is obtained by verifying a specified action of the target object using a first biometric verification method. The second verification result is obtained by verifying a specified part of the target object using a second biometric verification method. The first biometric verification method is used to perform interactive behavioral feature verification on the specified action of the target object. The second biometric verification method is used to perform interactive color change response verification on the specified part of the target object. The first verification result and the second verification result are verified to obtain a verification result, wherein the verification result is used to indicate whether both the first verification result and the second verification result pass the verification; The verification result is then sent back to the client.

11. A method for detecting liveness, characterized in that, include: A first biometric verification method is used to verify a pet's specified actions to obtain a first verification result, and a second biometric verification method is used to verify a pet's specified body parts to obtain a second verification result. The first biometric verification method is used to perform interactive behavioral feature verification of the pet's specified actions, and the second biometric verification method is used to perform interactive color change response verification of the pet's specified body parts. The first verification result and the second verification result are sent to the server, wherein the server is used to verify the first verification result and the second verification result; Receive a verification result from the server, wherein the verification result is used to indicate whether both the first verification result and the second verification result have passed the server's verification; In response to the verification result indicating that both the first verification result and the second verification result have passed the server's verification, it is determined that the pet is alive; In response to a specified part of the pet's image matching an image pre-stored in the access control system, the access control is unlocked to allow the pet to enter.

12. A method for detecting liveness, characterized in that, include: A liveness detection request is obtained through a first application programming interface. The request data carried in the liveness detection request includes a first verification result and a second verification result. The first verification result is obtained by verifying a specified action of the target object using a first biometric verification method. The second verification result is obtained by verifying a specified part of the target object using a second biometric verification method. The first biometric verification method is used to perform interactive behavioral feature verification of the specified action of the target object. The second biometric verification method is used to perform interactive color change response verification of the specified part of the target object. A liveness detection response is returned via a second application programming interface, wherein the response data carried in the liveness detection response includes a verification result, which indicates whether both the first verification result and the second verification result have passed the verification.

13. A method for detecting liveness, characterized in that, include: Obtain the currently input liveness detection dialogue request, wherein the request data carried in the liveness detection dialogue request includes: a first verification result and a second verification result. The first verification result is obtained by verifying the target object for a specified action using a first biometric verification method, and the second verification result is obtained by verifying the target object for a specified part using a second biometric verification method. The first biometric verification method is used to perform interactive behavioral feature verification on the specified action of the target object, and the second biometric verification method is used to perform interactive color change response verification on the specified part of the target object. In response to the liveness detection dialogue request, a liveness detection dialogue response is returned, wherein the information carried in the liveness detection dialogue response includes: a verification result, which is used to indicate whether both the first verification result and the second verification result have passed the verification; The verification results are displayed within the graphical user interface.

14. A method for detecting liveness, characterized in that, include: In response to input commands applied to the operation interface, the first verification result and the second verification result are displayed on the operation interface; In response to the processing instructions applied to the operation interface, the verification result is displayed on the operation interface; The first verification result is obtained by verifying a specified action of the target object using a first biometric verification method, and the second verification result is obtained by verifying a specified part of the target object using a second biometric verification method. The first biometric verification method is used to perform interactive behavioral feature verification of a specified action of the target object, and the second biometric verification method is used to perform interactive color change response verification of a specified part of the target object. The verification result is used to indicate whether both the first verification result and the second verification result pass the verification.

15. A liveness detection system, characterized in that, include: The client is used to send a first verification result and a second verification result. The first verification result is obtained by verifying a specified action of the target object using a first biometric verification method. The second verification result is obtained by verifying a specified part of the target object using a second biometric verification method. The first biometric verification method is used to perform interactive behavioral feature verification on the specified action of the target object. The second biometric verification method is used to perform interactive color change response verification on the specified part of the target object. The server, connected to the client, is configured to verify the first verification result and the second verification result to obtain a verification result, and to feed back the verification result to the client, wherein the verification result is used to indicate whether both the first verification result and the second verification result have passed the verification; The client is also used to output the verification result.

16. An electronic device, characterized in that, include: Memory, which stores executable programs; A processor for running the program, wherein the program, when running, performs the liveness detection method according to any one of claims 1 to 14.

17. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored executable program, wherein, when the executable program is executed, it controls the device on which the computer-readable storage medium is located to perform the liveness detection method according to any one of claims 1 to 14.

18. A computer program product, characterized in that, It includes a computer program that, when executed by a processor, implements the liveness detection method according to any one of claims 1 to 14.

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