CN108595928A - Information processing method, device and terminal equipment for face recognition - Google Patents

Abstract

The application discloses an information processing method, an information processing device and terminal equipment for face recognition, wherein the method comprises the following steps: acquiring attribute information of an application program calling face recognition; judging whether the face recognition process needs to be executed under a Trusted Execution Environment (TEE) according to the attribute information; if the face recognition process needs to be executed under the trusted execution environment TEE, controlling the application program to enter a trusted execution environment TEE mode, and executing the face recognition process in series under the trusted execution environment TEE; and if the face recognition process is not required to be executed under the trusted execution environment TEE, controlling the application program to enter a common execution environment REE mode, and executing the face recognition process under the common execution environment REE in parallel. The information processing method and device for face recognition and the terminal device can ensure information safety in scenes with high safety requirements and can realize quick response in scenes with low safety requirements.

Description

Information processing method, device and terminal equipment for face recognition

technical field

The present application relates to the field of information processing technology, and in particular to an information processing method, device and terminal equipment for face recognition.

Background technique

With the continuous advancement of science and technology, the application of biometric technology is becoming more and more extensive, especially face recognition, which has been widely used in scenarios such as identity authentication, mobile payment, and simulated dynamic expressions. For example, when a user needs to log in to a security application (wealth management APP), the face recognition function can be enabled through the application to obtain the user's face information and compare it with the pre-stored face information. If the comparison is consistent, the authentication is passed and the user login is successful. How to improve the security of operations such as identity authentication and mobile payment, and reduce the risk of user information being stolen has become an urgent problem to be solved.

application content

The present application provides an information processing method, device, and terminal equipment for face recognition, which can ensure information security in scenarios with high security requirements, and can also achieve rapid response in scenarios with relatively low security requirements.

An embodiment of the present application provides an information processing method for face recognition, including:

Obtain the attribute information of the application that calls face recognition;

Judging whether the face recognition process needs to be executed under the Trusted Execution Environment TEE according to the attribute information;

If the face recognition process needs to be executed under the Trusted Execution Environment TEE, control the application program to enter the Trusted Execution Environment TEE mode, and serially execute the face recognition process under the Trusted Execution Environment TEE steps in the identification process;

If the face recognition process does not need to be executed under the trusted execution environment TEE, control the application program to enter the normal execution environment REE mode, and execute the steps of the face recognition process in parallel under the normal execution environment REE.

Optionally, the attribute information of the application program includes the security level of the application program.

Optionally, the face recognition process includes a face detection step, a face element acquisition step, a live face detection step, and a face recognition step.

Optionally, the step of detecting human face includes:

emit infrared light to the subject;

capturing an infrared image passing through the subject;

sending the infrared image to a micro control unit MCU, and using the micro control unit MCU to process the infrared image to obtain infrared image data; and

The infrared image data is provided to the application program through a preset interface, so that the application program calls the infrared image data.

Optionally, the step of obtaining face elements includes:

Take visible light images of the subject;

sending the visible light image to a micro control unit MCU, and using the micro control unit MCU to process the visible light image to obtain visible light image data; and

The visible light image data is provided to the application program through a preset interface, so that the application program calls the visible light image data.

Optionally, the human face detection step includes:

emitting infrared light and the structured light to the subject;

capturing an infrared image passing through the subject and the structured light image;

Sending the infrared image and the structured light image to a micro control unit MCU, and using the micro control unit MCU to process the infrared image and the structured light image to obtain infrared image data and the depth of field data ;as well as

The infrared image data and the depth of field data are provided to the application program through a preset interface, so that the application program calls the infrared image data and the depth of field data.

Optionally, the face recognition step includes:

Take visible light images of the subject;

sending the visible light image to a micro control unit MCU, and using the micro control unit MCU to process the visible light image to obtain facial feature data; and

The facial feature data is provided to the application program through a preset interface, so that the application program invokes the facial feature data.

Optionally, using the micro control unit MCU to calculate and obtain the depth of field data corresponding to the subject, including:

Demodulating the phase information corresponding to the deformed position pixel in the structured light image;

converting the phase information into height information;

Depth of field data corresponding to the subject is determined according to the height information.

Optionally, the preset interface is a bus interface conforming to a preset standard, including a MIPI bus interface, an I2C synchronous serial bus interface, and an SPI bus interface.

Another embodiment of the present application provides an information processing device for face recognition, including:

The acquisition module is used to acquire the attribute information of the application program that calls the face recognition;

A judging module, configured to judge whether the face recognition process needs to be executed under the Trusted Execution Environment TEE according to the attribute information;

A processing module, configured to control the application program to enter the trusted execution environment TEE mode if the face recognition process needs to be executed under the trusted execution environment TEE, and execute serially under the trusted execution environment TEE Execute the step of the face recognition process, if the face recognition process does not need to be executed under the trusted execution environment TEE, then control the application program to enter the common execution environment REE mode, and parallelize it under the common execution environment REE The steps of the face recognition process are performed.

Optionally, the attribute information of the application program includes the security level of the application program.

Optionally, the face recognition process includes a face detection step, a face element acquisition step, a live face detection step, and a face recognition step.

Optionally, the processing module is specifically used for:

emit infrared light to the subject;

capturing an infrared image passing through the subject;

sending the infrared image to a micro control unit MCU, and using the micro control unit MCU to process the infrared image to obtain infrared image data; and

The infrared image data is provided to the application program through a preset interface, so that the application program calls the infrared image data.

Optionally, the processing module is specifically used for

Take visible light images of the subject;

sending the visible light image to a micro control unit MCU, and using the micro control unit MCU to process the visible light image to obtain visible light image data; and

The visible light image data is provided to the application program through a preset interface, so that the application program calls the visible light image data.

Optionally, the processing module is specifically used for

emitting infrared light and the structured light to the subject;

capturing an infrared image passing through the subject and the structured light image;

Sending the infrared image and the structured light image to a micro control unit MCU, and using the micro control unit MCU to process the infrared image and the structured light image to obtain infrared image data and the depth of field data ;as well as

The infrared image data and the depth of field data are provided to the application program through a preset interface, so that the application program calls the infrared image data and the depth of field data.

Optionally, the processing module is specifically used for

Take visible light images of the subject;

sending the visible light image to a micro control unit MCU, and using the micro control unit MCU to process the visible light image to obtain facial feature data; and

The facial feature data is provided to the application program through a preset interface, so that the application program invokes the facial feature data.

Optionally, the processing module is specifically used for

Demodulating the phase information corresponding to the deformed position pixel in the structured light image;

converting the phase information into height information;

Depth of field data corresponding to the subject is determined according to the height information.

Optionally, the preset interface is a bus interface conforming to a preset standard, including a MIPI bus interface, an I2C synchronous serial bus interface, and an SPI bus interface.

Another embodiment of the present application provides a terminal device, including a laser camera, a floodlight, a visible light camera, a laser light, a micro control unit MCU, and a processor, wherein the processor is used for:

Obtain the attribute information of the application that calls face recognition;

Judging whether the face recognition process needs to be executed under the Trusted Execution Environment TEE according to the attribute information;

If the face recognition process needs to be executed under the Trusted Execution Environment TEE, control the application program to enter the Trusted Execution Environment TEE mode, and serially execute the face recognition process under the Trusted Execution Environment TEE steps in the identification process;

If the face recognition process does not need to be executed under the trusted execution environment TEE, control the application program to enter the normal execution environment REE mode, and execute the steps of the face recognition process in parallel under the normal execution environment REE.

Yet another embodiment of the present application provides a non-transitory computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the face recognition information as described in the embodiment of the first aspect of the present application is realized. Approach.

The technical solutions provided by the embodiments of the present application may include the following beneficial effects:

By acquiring the attribute information of the application program that invokes face recognition, and judging whether the face recognition process needs to be executed under the trusted execution environment TEE according to the attribute information, if the face recognition process needs to be executed under the trusted execution environment Execute under the TEE, then control the application program to enter the trusted execution environment TEE mode, and execute the steps of the face recognition process serially under the trusted execution environment TEE, if the face recognition process does not need to be in the trusted execution environment TEE If it is executed under the trusted execution environment TEE, the application program is controlled to enter the normal execution environment REE mode, and the steps of the face recognition process are executed in parallel under the normal execution environment REE, which can ensure the high security requirements in the scene. information security, and can achieve rapid response in scenarios with relatively low security requirements.

Additional aspects and advantages of the application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the application.

Description of drawings

The above and/or additional aspects and advantages of the present application will become apparent and easy to understand from the following description of the embodiments in conjunction with the accompanying drawings, wherein:

FIG. 1 is a flowchart of an information processing method for face recognition according to an embodiment of the present application;

Fig. 2 is the flow chart of the detection human face step according to an embodiment of the present application;

Fig. 3 is the flow chart of the step of obtaining human face element according to one embodiment of the present application;

Fig. 4 is a flow chart of the human face detection steps according to one embodiment of the present application;

Fig. 5 is a schematic diagram of a scene of structured light measurement according to an embodiment of the present application;

FIG. 6 is a flow chart of face recognition steps according to one embodiment of the present application;

Fig. 7 is a structural block diagram of an information processing device for face recognition according to an embodiment of the present application;

Fig. 8 is a structural block diagram of a terminal device according to an embodiment of the present application;

Fig. 9 is a schematic structural diagram of a terminal device according to an embodiment of the present application.

Detailed ways

Embodiments of the present application are described in detail below, examples of which are shown in the drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the figures are exemplary, and are intended to explain the present application, and should not be construed as limiting the present application.

The information processing method, device and terminal equipment for face recognition according to the embodiments of the present application will be described below with reference to the accompanying drawings.

Fig. 1 is a flowchart of an information processing method for face recognition according to an embodiment of the present application.

As shown in Figure 1, the information processing method for face recognition includes:

S101. Acquire attribute information of an application that invokes face recognition.

At present, face recognition has been widely used in various scenarios, such as identity authentication scenarios, mobile payment scenarios, simulated dynamic expression scenarios, video conference scenarios, and so on. In the above scenarios, the face recognition is realized by calling hardware devices such as cameras, so as to realize the response function. Among them, some scenarios have higher requirements for operational security, such as identity authentication scenarios and mobile payment scenarios. Some scenarios have relatively low security requirements for operations, such as simulating dynamic expression scenes, video conference scenes, etc. For this reason, the present application proposes an information processing method for face recognition, which can not only ensure information security in scenarios with high security requirements, but also realize rapid response in scenarios with relatively low security requirements.

In an embodiment of the present application, firstly, the attribute information of the application calling the face recognition can be obtained. Wherein, the attribute information of the application program may include the security level of the application program. For example: the security level of banking applications, payment applications, and identity verification applications is high; the security level of ordinary camera applications is low.

S102. Determine whether the face recognition process needs to be executed under the Trusted Execution Environment TEE according to the attribute information.

In one embodiment of the present application, if the security level of the application program is high, the face recognition process needs to be performed under TEE (Trusted Execution Environment, Trust Execution Environment); The face recognition process does not need to be executed under TEE, it only needs to be executed under REE (ordinary execution environment, Rich ExecutionEnvironment). For example, when a user uses WeChat, Alipay and other applications to pay, he needs to turn on the camera to recognize the face and compare it with the pre-stored face. If the comparison results are consistent, the verification is successful and the payment operation is performed. Due to the information related to personal payment, etc., it may cause the loss of the user's personal property. Therefore, it needs to be executed under TEE to ensure security. In the simulated dynamic expression scene, the camera is turned on to recognize the face, just to track and capture the facial expression, and then simulate various interesting dynamic expressions to enhance the fun, so it only needs to be executed under REE.

S103, if the face recognition process needs to be executed under the TEE, control the application program to enter the TEE mode, and execute the steps of the face recognition process serially under the TEE.

Wherein, the face recognition process may include a face detection step, a face element acquisition step, a live face detection step, and a face recognition step. Due to the security feature of the TEE, the above steps are executed serially under the TEE. Under REE, the requirements for security are not high, and it can be executed in parallel. Among them, the step of detecting a human face refers to the process of emitting infrared light by invoking a floodlight, receiving an infrared image by a laser camera, and using the infrared image to determine whether it is a human face. The step of obtaining face elements is a process of using a visible light camera to shoot a face, and obtaining features related to image quality such as face brightness and face shooting angle. The face detection step is to combine infrared light and structured light, emit infrared light through floodlights, laser light emit structured light, receive infrared images and structured light images through laser cameras, and then analyze the above images to obtain human-like images. Face skin texture features, building a 3D face model, multi-frame face dynamic features, etc., to perform liveness detection. The face recognition step is to use the visible light camera to shoot the face to obtain features such as the size of the eyes, the position of the nose on the face, the length of the eyebrows, etc., for face recognition.

In this embodiment, when the above steps are executed serially, the execution sequence is not limited. The above steps can also be combined arbitrarily according to the actual application situation of the application program to realize corresponding functions. For example, in the face payment scenario, only the face liveness detection step is combined with the face recognition step, and the face element step is not required. It should be understood that the above scenario is only an example, and is not intended as a limitation on the technical solution.

S104, if the face recognition process does not need to be executed under the trusted execution environment TEE, control the application program to enter the normal execution environment REE mode, and execute the steps of the face recognition process in parallel under the normal execution environment REE.

In one embodiment of the present application, under the REE, the face recognition process does not have high security requirements, therefore, the steps of the face recognition process can be executed in parallel to increase the execution speed of the face recognition process.

The steps of face detection, face element acquisition, live face detection and face recognition in the face recognition process are explained in detail below.

As shown in Figure 2, the face detection steps include:

S201, emit infrared light to the subject.

In particular, infrared light can be emitted by floodlights.

S202. Capture an infrared image passing through the subject.

The infrared image of the passing object is captured by the laser camera.

S203. Send the infrared image to the micro control unit MCU, and use the micro control unit MCU to process the infrared image to obtain infrared image data.

Due to hacking, most of them are based on the intrusion of the application program side, so the infrared image is sent to the MCU, and the infrared image is processed by the hardware MCU to prevent the original data from being intercepted on the application program side, which can effectively improve the security of the data. safety.

S204. Provide the infrared image data to the application program through the preset interface, so that the application program calls the infrared image data.

In this embodiment, an application program can be used to invoke infrared image data to realize face detection.

Wherein, the preset interface is a bus interface conforming to a preset standard, including a MIPI (Mobile Industry Processor Interface) bus interface, an I2C synchronous serial bus interface, and an SPI bus interface.

As shown in Figure 3, the steps of obtaining face elements include:

S301. Shoot a visible light image of a subject.

Specifically, a visible light image of the subject may be captured by a visible light camera.

S302. Send the visible light image to the micro control unit MCU, and use the micro control unit MCU to process the visible light image to obtain visible light image data.

Due to hacking, most of them are based on the intrusion of the application program side, so the visible light image is sent to the MCU, and the visible light image is processed by the hardware MCU to prevent the original data from being intercepted on the application program side, which can effectively improve the security of the data. safety.

S303. Provide the visible light image data to the application program through a preset interface, so that the application program calls the visible light image data.

In this embodiment, the application program can be used to call visible light image data to extract face elements, such as obtaining features related to image quality such as face brightness and face shooting angle, which can be used as the data basis for the next step.

As shown in Figure 4, the face detection steps include:

S401. Emit infrared light and structured light to a subject.

In one embodiment of the present application, the structured light can be generated by PWM modulation in the MCU, the structured light can be emitted through the laser light, and the infrared light can be emitted to the subject through the floodlight (infrared light emitter).

S402. Capture an infrared image and a structured light image passing through the subject.

In one embodiment of the present application, a laser camera (infrared light receiver) can be used to capture infrared images and structured light images passing through the subject.

S403. Send the infrared image and the structured light image to the micro control unit MCU, and use the micro control unit MCU to process the infrared image and the structured light image to obtain infrared image data and depth of field data.

Specifically, the infrared image and the structured light image can be processed by using the depth engine in the MCU to obtain infrared image data and depth of field data.

S404. Provide the infrared image data and the depth of field data to the application program through a preset interface, so that the application program calls the infrared image data and the depth of field data for security verification.

In one embodiment of the present application, the MCU can be used to modulate and generate structured light, and the structured light can be emitted to the subject through a laser lamp (structured light projection device). Assuming that the current scene is an authentication scene, the subject may be the user's face. After the structured light irradiates the subject, due to the shape characteristics of the subject, the structured light will be deformed. By collecting the above structured light information, a structured light image with the outline and depth of the subject can be obtained.

Wherein, the type of the structured light may include laser stripes, gray codes, sinusoidal stripes, or non-uniform speckle, etc.

The following uses a widely used fringe projection technology as an example to illustrate its specific principles. Among them, the fringe projection technology belongs to surface structured light in a broad sense.

When using surface structured light projection, as shown in Figure 5, the MCU generates sinusoidal fringes, and the sinusoidal fringes are projected to the subject through a laser lamp (structured light projection device), and the laser camera is used to capture the fringes modulated by the object. degree, demodulate the curved fringe to obtain the phase, and then convert the phase into the height of the whole field.

It should be understood that, in practical applications, according to different specific application scenarios, the structured light used in the embodiment of the present application may be in any other pattern besides the above-mentioned stripes.

After that, the structured light image can be sent to the micro control unit MCU, and the micro control unit MCU is used to calculate and obtain the depth of field data corresponding to the subject. In order to further improve security, the structured light image can be sent to the MCU, and the structured light image can be processed in the MCU of the hardware. Compared with sending it directly to the application program for processing, the data has already been calculated in the hardware, and hackers cannot obtain the original data. , and therefore more secure. Specifically, the MCU can be used to demodulate the phase information corresponding to the deformed position pixels in the structured light image, then convert the phase information into height information, and finally determine the depth of field data corresponding to the subject according to the height information. Finally, the depth of field data is provided to the application program through the preset interface, so that the application program calls the depth of field data. For example: Based on the structured light image of the face, the data information such as the contour and height of the face is calculated. The above data information has been calculated in the MCU, and the application only needs to call the above data information and perform feature comparison with the pre-stored data to realize identity verification. If the verification is passed, the user can obtain the permission of the application and perform further operations on the application. For example, use structured light to build a 3D model of the face, obtain the 3D features of the face, combine infrared image data or multi-frame face dynamic features, etc., to perform liveness detection, and detect that the currently captured face is a living body rather than a flat photo.

As shown in Figure 6, the face recognition steps include:

S601. Shoot a visible light image of a subject.

S602. Send the visible light image to the micro control unit MCU, and use the micro control unit MCU to process the visible light image to obtain facial feature data.

Due to hacking, most of them are based on the intrusion of the application program side, so the visible light image is sent to the MCU, and the visible light image is processed by the hardware MCU to prevent the original data from being intercepted on the application program side, which can effectively improve the security of the data. safety.

Among them, the face feature data may include the size of the eyes, the position information of the nose on the face, the length of the eyebrows, etc.

S603. Provide the face feature data to the application program through a preset interface, so that the application program calls the face feature data.

In this embodiment, an application program can be used to call visible light image data for face recognition.

The face recognition information processing method of the embodiment of the present application obtains the attribute information of the application program that calls the face recognition, and judges whether the face recognition process needs to be executed under the Trusted Execution Environment TEE according to the attribute information. The process needs to be executed under the trusted execution environment TEE, then the control application enters the trusted execution environment TEE mode, and serially executes the steps of the face recognition process under the trusted execution environment TEE, if the face recognition process does not need to be in the trusted execution environment Execute under the execution environment TEE, control the application program to enter the normal execution environment REE mode, and execute the steps of the face recognition process in parallel under the normal execution environment REE, which can ensure information security in scenarios with high security requirements, and can realize Quick response in scenarios with relatively low security requirements.

In order to realize the above embodiment, the present application also proposes an information processing device for face recognition. FIG. 7 is a structural block diagram of an information processing device for face recognition according to an embodiment of the present application. As shown in FIG. 7 , the device It includes an acquisition module 710 , a judgment module 720 and a processing module 730 .

Wherein, the acquiring module 710 is configured to acquire the attribute information of the application calling the face recognition.

The judging module 720 is configured to judge whether the face recognition process needs to be executed under the trusted execution environment TEE according to the attribute information.

The processing module 730 is used to control the application program to enter the trusted execution environment TEE mode if the face recognition process needs to be executed under the trusted execution environment TEE, and execute the steps of the face recognition process serially under the trusted execution environment TEE , if the face recognition process does not need to be executed under the trusted execution environment TEE, the control application program enters the common execution environment REE mode, and executes the steps of the face recognition process in parallel under the common execution environment REE.

It should be noted that the foregoing explanations on the information processing method for face recognition are also applicable to the information processing device for face recognition in the embodiment of the present application, and the details not disclosed in the embodiment of the present application will not be repeated here.

The face recognition information processing device of the embodiment of the present application obtains the attribute information of the application program that calls the face recognition, and judges whether the face recognition process needs to be executed under the Trusted Execution Environment TEE according to the attribute information. The process needs to be executed under the trusted execution environment TEE, then the control application enters the trusted execution environment TEE mode, and serially executes the steps of the face recognition process under the trusted execution environment TEE, if the face recognition process does not need to be in the trusted execution environment Execute under the execution environment TEE, control the application program to enter the normal execution environment REE mode, and execute the steps of the face recognition process in parallel under the normal execution environment REE, which can ensure information security in scenarios with high security requirements, and can realize Quick response in scenarios with relatively low security requirements.

In order to implement the foregoing embodiments, the present application also proposes a terminal device.

As shown in FIG. 8 , the terminal device 800 includes a laser camera 810 , a floodlight 820 , a visible light camera 830 , a laser light 840 , a micro control unit MCU 850 and a processor 860 . The laser camera 810, the floodlight 820, the visible light camera 830, and the laser light 840 are respectively connected with the MCU850. The MCU 850 is connected with the processor 860 .

The processor 860 is specifically configured to perform the following steps:

S101', acquire the attribute information of the application that calls the face recognition.

In an embodiment of the present application, firstly, the attribute information of the application calling the face recognition can be obtained. Wherein, the attribute information of the application program may include the security level of the application program. For example: the security level of banking applications, payment applications, and identity verification applications is high; the security level of ordinary camera applications is low.

S102', judge whether the face recognition process needs to be executed under the trusted execution environment TEE according to the attribute information.

In one embodiment of the present application, if the security level of the application program is high, the face recognition process needs to be performed under TEE (Trusted Execution Environment, Trust Execution Environment); The face recognition process does not need to be executed under TEE, it only needs to be executed under REE (ordinary execution environment, Rich ExecutionEnvironment). For example, when a user uses WeChat, Alipay and other applications to pay, he needs to turn on the camera to recognize the face and compare it with the pre-stored face. If the comparison results are consistent, the verification is successful and the payment operation is performed. Due to the information related to personal payment, etc., it may cause the loss of the user's personal property. Therefore, it needs to be executed under TEE to ensure security. In the simulated dynamic expression scene, the camera is turned on to recognize the face, just to track and capture the facial expression, and then simulate various interesting dynamic expressions to enhance the fun, so it only needs to be executed under REE.

S103', if the face recognition process needs to be executed under the trusted execution environment TEE, the control application program enters the trusted execution environment TEE mode, and serially executes the steps of the face recognition process under the trusted execution environment TEE.

Wherein, the face recognition process may include a face detection step, a face element acquisition step, a live face detection step, and a face recognition step. Due to the security feature of the TEE, the above steps are executed serially under the TEE. Under REE, the requirements for security are not high, and it can be executed in parallel. Among them, the step of detecting a human face refers to the process of emitting infrared light by invoking a floodlight, receiving an infrared image by a laser camera, and using the infrared image to determine whether it is a human face. The step of obtaining face elements is a process of using a visible light camera to shoot a face, and obtaining features related to image quality such as face brightness and face shooting angle. The face detection step is to combine infrared light and structured light, emit infrared light through floodlights, laser light emit structured light, receive infrared images and structured light images through laser cameras, and then analyze the above images to obtain human-like images. Face skin texture features, building a 3D face model, multi-frame face dynamic features, etc., to perform liveness detection. The face recognition step is to use the visible light camera to shoot the face to obtain features such as the size of the eyes, the position of the nose on the face, the length of the eyebrows, etc., for face recognition.

In this embodiment, when the above steps are executed serially, the execution sequence is not limited. The above steps can also be combined arbitrarily according to the actual application situation of the application program to realize corresponding functions. For example, in the face payment scenario, only the face liveness detection step is combined with the face recognition step, and the face element step is not required. It should be understood that the above scenario is only an example, and is not intended as a limitation on the technical solution.

S104', if the face recognition process does not need to be executed under the trusted execution environment TEE, control the application program to enter the common execution environment REE mode, and execute the steps of the face recognition process in parallel under the common execution environment REE.

In one embodiment of the present application, under the REE, the face recognition process does not have high security requirements, so the steps of the face recognition process can be executed in parallel.

The terminal device of the embodiment of the present application obtains the attribute information of the application program that calls the face recognition, and judges whether the face recognition process needs to be executed under the Trusted Execution Environment TEE according to the attribute information. Execution under the execution environment TEE, the control application enters the trusted execution environment TEE mode, and executes the steps of the face recognition process serially under the trusted execution environment TEE, if the face recognition process does not need to be executed under the trusted execution environment TEE , then control the application program to enter the normal execution environment REE mode, and execute the steps of the face recognition process in parallel under the common execution environment REE, which can ensure the information security in the scene with high security requirements, and can realize the relatively low security requirements. Fast response in high scene.

As shown in FIG. 9 , a terminal device 900 according to an embodiment of the present application includes one or more processors 910 , a memory 920 and one or more programs 901 . One or more programs 901 are stored in memory 920 and configured to be executed by one or more processors 910 . The program 901 includes instructions for executing the information processing method for face recognition in any one of the above-mentioned embodiments.

For example, program 901 includes instructions for performing the following steps of an information processing method for face recognition:

S101', acquire the attribute information of the application that calls the face recognition.

S102', judge whether the face recognition process needs to be executed under the trusted execution environment TEE according to the attribute information.

S103', if the face recognition process needs to be executed under the trusted execution environment TEE, the control application program enters the trusted execution environment TEE mode, and serially executes the steps of the face recognition process under the trusted execution environment TEE.

S104', if the face recognition process does not need to be executed under the trusted execution environment TEE, control the application program to enter the common execution environment REE mode, and execute the steps of the face recognition process in parallel under the common execution environment REE.

In order to realize the above-mentioned embodiments, the present application also proposes a non-transitory computer-readable storage medium on which a computer program is stored, which is characterized in that, when the program is executed by a processor, the face recognition of the embodiment of the first aspect is realized. information processing methods.

In the description of this specification, descriptions referring to the terms "one embodiment", "some embodiments", "example", "specific examples", or "some examples" mean that specific features described in connection with the embodiment or example , structure, material or characteristic is included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms are not necessarily directed to the same embodiment or example. Furthermore, the described specific features, structures, materials or characteristics may be combined in any suitable manner in any one or more embodiments or examples. In addition, those skilled in the art can combine and combine different embodiments or examples and features of different embodiments or examples described in this specification without conflicting with each other.

In addition, the terms "first" and "second" are used for descriptive purposes only, and cannot be interpreted as indicating or implying relative importance or implicitly specifying the quantity of indicated technical features. Thus, the features defined as "first" and "second" may explicitly or implicitly include at least one of these features. In the description of the present application, "plurality" means at least two, such as two, three, etc., unless otherwise specifically defined.

Any process or method descriptions in flowcharts or otherwise described herein may be understood to represent modules, segments or portions of code comprising one or more executable instructions for implementing specific logical functions or steps of the process , and the scope of preferred embodiments of the present application includes additional implementations in which functions may be performed out of the order shown or discussed, including in substantially simultaneous fashion or in reverse order depending on the functions involved, which shall It should be understood by those skilled in the art to which the embodiments of the present application belong.

The logic and/or steps represented in the flowcharts or otherwise described herein, for example, can be considered as a sequenced listing of executable instructions for implementing logical functions, can be embodied in any computer-readable medium, For use with instruction execution systems, devices, or devices (such as computer-based systems, systems including processors, or other systems that can fetch instructions from instruction execution systems, devices, or devices and execute instructions), or in conjunction with these instruction execution systems, devices or equipment used. For the purposes of this specification, a "computer-readable medium" may be any device that can contain, store, communicate, propagate or transmit a program for use in or in conjunction with an instruction execution system, device or device. More specific examples (non-exhaustive list) of computer-readable media include the following: electrical connection with one or more wires (electronic device), portable computer disk case (magnetic device), random access memory (RAM), Read Only Memory (ROM), Erasable and Editable Read Only Memory (EPROM or Flash Memory), Fiber Optic Devices, and Portable Compact Disc Read Only Memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program may be printed, as it may be possible, for example, by optically scanning the paper or other medium, followed by editing, interpretation or other suitable means if necessary. Processing to obtain programs electronically and store them in computer memory.

It should be understood that each part of the present application may be realized by hardware, software, firmware or a combination thereof. In the embodiments described above, various steps or methods may be implemented by software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented by any one or combination of the following techniques known in the art: Discrete logic circuits, ASICs with suitable combinational logic gates, programmable gate arrays (PGAs), field programmable gate arrays (FPGAs), etc.

Those of ordinary skill in the art can understand that all or part of the steps carried by the methods of the above embodiments can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable storage medium. When the program is executed , including one or a combination of the steps of the method embodiment.

In addition, each functional unit in each embodiment of the present application may be integrated into one processing module, each unit may exist separately physically, or two or more units may be integrated into one module. The above-mentioned integrated modules can be implemented in the form of hardware or in the form of software function modules. If the integrated modules are realized in the form of software function modules and sold or used as independent products, they can also be stored in a computer-readable storage medium.

The storage medium mentioned above may be a read-only memory, a magnetic disk or an optical disk, and the like. Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as limitations on the present application, and those skilled in the art can make the above-mentioned The embodiments are subject to changes, modifications, substitutions and variations.

Claims (20)

1. An information processing method for face recognition, comprising the following steps: Obtain the attribute information of the application that calls face recognition; Judging whether the face recognition process needs to be executed under the Trusted Execution Environment TEE according to the attribute information; If the face recognition process needs to be executed under the Trusted Execution Environment TEE, control the application program to enter the Trusted Execution Environment TEE mode, and serially execute the face recognition process under the Trusted Execution Environment TEE steps in the identification process; If the face recognition process does not need to be executed under the trusted execution environment TEE, control the application program to enter the normal execution environment REE mode, and execute the steps of the face recognition process in parallel under the normal execution environment REE. 2. The method according to claim 1, wherein the attribute information of the application program includes a security level of the application program. 3. The method according to claim 1, wherein the face recognition process comprises a face detection step, a face element acquisition step, a live face detection step and a face recognition step. 4. method as claimed in claim 3, is characterized in that, described detecting people's face step, comprises: emit infrared light to the subject; capturing an infrared image passing through the subject; sending the infrared image to a micro control unit MCU, and using the micro control unit MCU to process the infrared image to obtain infrared image data; and The infrared image data is provided to the application program through a preset interface, so that the application program calls the infrared image data. 5. method as claimed in claim 3, is characterized in that, described obtaining people's face element step, comprises: Take visible light images of the subject; sending the visible light image to a micro control unit MCU, and using the micro control unit MCU to process the visible light image to obtain visible light image data; and The visible light image data is provided to the application program through a preset interface, so that the application program calls the visible light image data. 6. method as claimed in claim 3, is characterized in that, described human face detection step, comprises: emitting infrared light and the structured light to the subject; capturing an infrared image passing through the subject and the structured light image; Sending the infrared image and the structured light image to a micro control unit MCU, and using the micro control unit MCU to process the infrared image and the structured light image to obtain infrared image data and the depth of field data ;as well as The infrared image data and the depth of field data are provided to the application program through a preset interface, so that the application program calls the infrared image data and the depth of field data. 7. The method according to claim 3, wherein the face recognition step comprises: Take visible light images of the subject; sending the visible light image to a micro control unit MCU, and using the micro control unit MCU to process the visible light image to obtain facial feature data; and The facial feature data is provided to the application program through a preset interface, so that the application program invokes the facial feature data. 8. The method according to claim 6, characterized in that, using the MCU to calculate and obtain the depth-of-field data corresponding to the object comprises: Demodulating the phase information corresponding to the deformed position pixel in the structured light image; converting the phase information into height information; Depth of field data corresponding to the subject is determined according to the height information. 9. The method according to any one of claims 4 to 7, wherein the preset interface is a bus interface conforming to a preset standard, including a MIPI bus interface, an I2C synchronous serial bus interface, and an SPI bus interface. 10. An information processing device for face recognition, comprising: The acquisition module is used to acquire the attribute information of the application program that calls the face recognition; A judging module, configured to judge whether the face recognition process needs to be executed under the Trusted Execution Environment TEE according to the attribute information; A processing module, configured to control the application program to enter the trusted execution environment TEE mode if the face recognition process needs to be executed under the trusted execution environment TEE, and execute serially under the trusted execution environment TEE Execute the step of the face recognition process, if the face recognition process does not need to be executed under the trusted execution environment TEE, then control the application program to enter the common execution environment REE mode, and parallelize it under the common execution environment REE The steps of the face recognition process are performed. 11. The apparatus according to claim 10, wherein the attribute information of the application program includes a security level of the application program. 12 . The device according to claim 10 , wherein the face recognition process comprises a face detection step, a face element acquisition step, a live face detection step, and a face recognition step. 13 . 13. The device according to claim 12, wherein the processing module is specifically used for: emit infrared light to the subject; capturing an infrared image passing through the subject; sending the infrared image to a micro control unit MCU, and using the micro control unit MCU to process the infrared image to obtain infrared image data; and The infrared image data is provided to the application program through a preset interface, so that the application program calls the infrared image data. 14. The device according to claim 12, wherein the processing module is specifically used to Take visible light images of the subject; sending the visible light image to a micro control unit MCU, and using the micro control unit MCU to process the visible light image to obtain visible light image data; and The visible light image data is provided to the application program through a preset interface, so that the application program calls the visible light image data. 15. The device according to claim 12, wherein the processing module is specifically used to emitting infrared light and the structured light to the subject; capturing an infrared image passing through the subject and the structured light image; Sending the infrared image and the structured light image to a micro control unit MCU, and using the micro control unit MCU to process the infrared image and the structured light image to obtain infrared image data and the depth of field data ;as well as The infrared image data and the depth of field data are provided to the application program through a preset interface, so that the application program calls the infrared image data and the depth of field data. 16. The device according to claim 12, wherein the processing module is specifically used to Take visible light images of the subject; sending the visible light image to a micro control unit MCU, and using the micro control unit MCU to process the visible light image to obtain facial feature data; and The facial feature data is provided to the application program through a preset interface, so that the application program invokes the facial feature data. 17. The device according to claim 15, wherein the processing module is specifically used to Demodulating the phase information corresponding to the deformed position pixel in the structured light image; converting the phase information into height information; Depth of field data corresponding to the subject is determined according to the height information. 18. The device according to any one of claims 13 to 16, wherein the preset interface is a bus interface conforming to a preset standard, including a MIPI bus interface, an I2C synchronous serial bus interface, and an SPI bus interface. 19. A non-transitory computer-readable storage medium, on which a computer program is stored, characterized in that, when the program is executed by a processor, the information processing of face recognition as described in any one of claims 1-9 is realized method. 20. A terminal device, characterized in that it includes a laser camera, a floodlight, a visible light camera, a laser light, a micro control unit MCU and a processor, wherein the processor is used for: Obtain the attribute information of the application that calls face recognition; Judging whether the face recognition process needs to be executed under the Trusted Execution Environment TEE according to the attribute information; If the face recognition process needs to be executed under the Trusted Execution Environment TEE, control the application program to enter the Trusted Execution Environment TEE mode, and serially execute the face recognition process under the Trusted Execution Environment TEE steps in the identification process; If the face recognition process does not need to be executed under the trusted execution environment TEE, control the application program to enter the normal execution environment REE mode, and execute the steps of the face recognition process in parallel under the normal execution environment REE.