CN113660395B

CN113660395B - Safety prompt method and equipment based on target identification

Info

Publication number: CN113660395B
Application number: CN202110901972.8A
Authority: CN
Inventors: 王大勇; 张焕斌; 李恩征
Original assignee: Hisense Visual Technology Co Ltd
Current assignee: Hisense Visual Technology Co Ltd
Priority date: 2021-08-06
Filing date: 2021-08-06
Publication date: 2023-08-01
Anticipated expiration: 2041-08-06
Also published as: CN113660395A

Abstract

The application relates to the technical field of VR (virtual reality), and provides a safety prompt method and equipment based on target identification, in particular to a method and equipment for respectively acquiring RGB (red, green and blue) images in a field angle area acquired by a binocular camera at the current moment and motion data of VR equipment acquired by an inertial sensor; determining a multidimensional vector matrix representing real scene depth information in the view angle area according to the two RGB images and the motion data; determining the difference value of the multidimensional vector matrixes at two adjacent moments according to the multidimensional vector matrix at the current moment and the multidimensional vector matrix at the last moment; identifying whether a target object exists in the view angle area according to the multi-dimensional vector matrix difference value; if the target object is identified, when the target object is located in a preset safety area of the VR equipment, safety prompt information is given so that an experimenter of the VR equipment avoids the target object in the safety area, and the safety of experience is improved while the immersion of the experimenter is not influenced.

Description

Safety prompt method and equipment based on target identification

Technical Field

The application relates to the technical field of Virtual Reality (VR), in particular to a safety prompting method and device based on target recognition.

Background

VR devices typically have a pre-labeled secure area where the user experiences immersion, as shown in fig. 1.

At present, whether an experimenter moves out of a safety area is identified by a visual-based space positioning method, when the experimenter is identified to leave the safety area, the VR equipment pauses the current human-computer interaction process, and a real field scene is displayed through a camera of the VR equipment so that the experimenter can avoid obstacles. And when the target object is in the safety area, the obstacle entering the safety area cannot be perceived, so that potential safety hazards are brought to experimenters.

Disclosure of Invention

The embodiment of the application provides a safety prompt method and equipment based on target identification, which are used for improving the safety of an experience process of VR equipment experienters.

In a first aspect, an embodiment of the present application provides a security prompt method based on target identification, which is applied to VR equipment, and includes:

respectively acquiring RGB images in a field angle area acquired by a binocular camera at the current moment and motion data of the VR equipment acquired by an inertial sensor;

determining a multidimensional vector matrix representing real scene depth information in the view angle area according to the two RGB images and the motion data;

determining the difference value of the multidimensional vector matrixes at two adjacent moments according to the multidimensional vector matrix at the current moment and the multidimensional vector matrix at the last moment;

identifying whether a target object exists in the view angle area according to the multi-dimensional vector matrix difference value;

if the target object is identified, when the target object is located in a preset safety area of the VR equipment, safety prompt information is given.

In a first aspect, embodiments of the present application provide a VR device, including a display screen, a lens, a binocular camera, an inertial sensor, a memory, and a processor:

the display screen is configured to display VR images;

the lens is configured to map a picture displayed on the display screen onto retina by utilizing a light ray principle;

the binocular camera is configured to collect RGB images of a real scene in a view angle area;

the inertial sensor is configured to collect motion data of the VR device;

the memory is configured to store computer program instructions;

the processor is configured to perform the following operations in accordance with the computer program instructions:

In a third aspect, the present application provides a computer-readable storage medium storing computer-executable instructions for causing a computer to perform the object recognition-based security prompt method provided by the embodiments of the present application.

In the above embodiment of the present application, according to the RGB images collected by the binocular cameras at two adjacent moments, the difference value of the multidimensional vector matrix of the real scene depth information in the view angle area of the binocular cameras at two adjacent moments is determined, the target object in the view angle area is identified according to the multidimensional vector matrix difference value, and when the target object is located in the preset safety area of the VR device, safety prompt information is given out, so that the experimenter of the VR device avoids the target object in the safety area, and the safety of experience is improved while the immersion feeling of the experimenter is not affected.

Drawings

In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, and it is obvious that the drawings in the following description are some embodiments of the present application, and other drawings may be obtained according to these drawings without inventive effort to a person skilled in the art.

FIG. 1 schematically illustrates a secure enclave provided by an embodiment of the present application;

fig. 2 schematically illustrates a VR all-in-one machine provided in an embodiment of the present application;

fig. 3 schematically illustrates an operation manner of the VR integrated machine provided in an embodiment of the present application;

fig. 4 illustrates an interface diagram of an external device control VR device display provided in an embodiment of the present application;

FIG. 5 schematically illustrates an object within an identified security zone provided by an embodiment of the present application;

FIG. 6 illustrates a flow chart of a security prompt method based on object recognition provided by an embodiment of the present application;

fig. 7 schematically illustrates a binocular camera pose calculation method provided in an embodiment of the present application;

FIG. 8 schematically illustrates a method for measuring three-dimensional information using triangles provided in an embodiment of the present application;

FIG. 9 is a schematic diagram illustrating a secure enclave partition provided by an embodiment of the present application;

FIG. 10 illustrates a hint interface diagram provided by embodiments of the present application;

fig. 11 illustrates a hardware configuration diagram of a VR device provided in an embodiment of the present application.

Detailed Description

For purposes of clarity, embodiments and advantages of the present application, the following description will make clear and complete the exemplary embodiments of the present application, with reference to the accompanying drawings in the exemplary embodiments of the present application, it being apparent that the exemplary embodiments described are only some, but not all, of the examples of the present application.

Based on the exemplary embodiments described herein, all other embodiments that may be obtained by one of ordinary skill in the art without making any inventive effort are within the scope of the claims appended hereto. Furthermore, while the disclosure is presented in the context of an exemplary embodiment or embodiments, it should be appreciated that the various aspects of the disclosure may, separately, comprise a complete embodiment.

It should be noted that the brief description of the terms in the present application is only for convenience in understanding the embodiments described below, and is not intended to limit the embodiments of the present application. Unless otherwise indicated, these terms should be construed in their ordinary and customary meaning.

Furthermore, the terms "comprise" and "have," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a product or apparatus that comprises a list of elements is not necessarily limited to those elements expressly listed, but may include other elements not expressly listed or inherent to such product or apparatus.

In order to clearly describe the embodiments of the present application, the following terms of the present application are explained.

3 degrees of freedom (Degree of Freedom, doF): the VR device can detect free rotation of the experimenter's head in different directions, but cannot detect spatial displacement of the head up, down, back, forth, left, and right.

6DOF: the VR device can detect changes in the vertical, front-to-back, left-to-right displacement due to movement of the experimenter's body in addition to changes in the angle of view due to rotation of the experimenter's head.

Field of View (FOV): also known as the field of view, determines the field of view of an optical instrument (e.g., a camera), and the angle of view is determined by the hardware of the optical instrument itself.

Safety area: the safe movable range of VR equipment experimenter, according to the difference of VR equipment, the setting method of safe region is also different. For example, for VR devices without external devices, a secure area is typically established centered on the VR device with a fixed length as a radius; for VE devices with external devices (e.g., handles), a safe area is established around the VR device based on the signal range of the external device.

Embodiments of the present application are described in detail below with reference to the accompanying drawings.

Fig. 2 schematically illustrates a structural diagram of a VR all-in-one machine provided in an embodiment of the present application. As shown in fig. 2, the VR device itself is provided with a plurality of cameras including, but not limited to, a conventional camera, a fisheye camera. A 6DOF algorithm based on Computer Vision (CV) can be implemented with the camera captured images.

As shown in fig. 2, the VR device also has an associated external device (e.g., a handle) that can transmit ultrasound outwards, thereby implementing a CV or ultrasound based 6DOF algorithm for the external device.

Based on the VR all-in-one machine shown in fig. 2, an experimenter of the VR device may conduct an immersive experience of the interactive class game based on the manner of operation shown in fig. 3. In the interaction process, an experimenter can control the display content of the VR device display screen through an operation handle, as shown in FIG. 4.

It should be noted that fig. 1-4 are only examples, and the number of external devices is not limited in the embodiments of the present application. For example, for VR devices with gesture recognition functionality, no external device may be present.

Based on the VR device, the embodiment of the application provides a security prompt method based on target identification. As shown in fig. 5, the security area of the VR device may be regarded as a cylinder, and for objects entering the security area, a corresponding security prompt is given. Specifically, whether the depth information of the real scene in the visual field angle area is changed is confirmed through images acquired by the binocular cameras at different moments, object shape identification of 3D information is carried out based on a multidimensional vector matrix difference value representing the change of the depth information, whether an object is located in a preset safety area of VR equipment is determined, if so, the identified object is displayed in a 3D interface at the current moment in a virtual model mode, and the experimenter is ensured to obtain corresponding reminding to avoid potential safety hazards while the immersion feeling of the experimenter is not influenced.

Fig. 6 illustrates a flowchart of a security prompt method based on object recognition according to an embodiment of the present application, and as shown in fig. 5, the process is performed by a VR device, and mainly includes the following steps:

s601: RGB images in the field angle area acquired by the binocular camera at the current moment and motion data of VR equipment acquired by the inertial sensor are respectively acquired.

In S601, the VR device includes an inertial sensor (Inertial Measurement Unit, IMU). Generally, the IMU is to be mounted on the center of gravity of the object under test, i.e., the location of the center of gravity of the VR device. Typically, an IMU contains three single axis accelerometers for measuring acceleration of the VR device and three single axis gyroscopes for measuring angular velocity of the VR device. Thus, the motion data includes acceleration and angular velocity of the VR device.

In the embodiment of the application, the field angle size of the (left and right) binocular camera of the VR device determines the field area range, in S601, the field angle size of the binocular camera is about 105 °, the RGB image in the field angle area at the current moment is collected by the binocular camera, and the pose information of the VR device can be calculated by combining the motion data of the VR device at the current moment collected by the IMU.

S602: and determining a multidimensional vector matrix representing the depth information of the real scene in the field angle area according to the two RGB images and the motion data.

In S602, because there is a significant drift in the angular velocity and acceleration of the VR device measured by the IMU, when the acquired motion data is integrated multiple times, the pose estimation error is large, while the visual image acquired by the binocular camera has no drift and the texture information is rich, so that the pose information of the VR device can be determined by the motion data acquired by the IMU and the RGB image acquired by the binocular camera, and the pose error estimated by the IMU is optimized by using the visual data, thereby improving the estimation accuracy. The specific estimation process has been described in the related art, and will not be described in detail herein since this section is not important to the present application.

In S602, the pose information includes position information and rotation angle information, and since the IMU is generally disposed at the center of gravity of the VR device, the pose information estimated in S602 is overall pose information of the VR device. Further, pose information of the left binocular camera and the right binocular camera is respectively determined according to pose information of the VR device.

Specifically, as shown in fig. 7, assuming that the position information of the VR device is P0, the rotation angle information is R0, the measured position deviation L1 of the left camera relative to the VR device, the measured angle deviation R01 of the left camera relative to the VR device, the measured position deviation L2 of the right camera relative to the VR device, and the measured angle deviation R02 of the right camera relative to the VR device, the position information p1=p0-L1 of the left camera, the rotation angle information r1=r0×r01 of the left camera, the position information p2=p0+l2 of the right camera, and the rotation angle information r2=r0×r02 of the right camera.

After pose information of the left (binocular) camera and the right (binocular) camera is obtained, two-dimensional information (including depth information) of a real scene is determined by combining two-dimensional information of the real scene in a view angle area extracted from RGB images acquired by the left (binocular) camera and the right (binocular) camera respectively by adopting a deep learning model (such as convolutional neural networks (Convolutional Neural Networks, CNN) and cyclic neural networks (Recurrent Neural Network, RNN), and a multidimensional vector matrix representing the depth information of the real scene is obtained.

Wherein the depth information may be determined using triangulation. As shown in fig. 8, O1 is the optical center of the left camera, O2 is the optical center of the right camera, I1 is the RGB image collected by the left camera (denoted as left RGB image), I2 is the RGB image collected by the right camera (denoted as right RGB image), p1 is the pixel point on the left RGB image, p2 is the pixel point in the right RGB image, and t is the transformation matrix of the right RGB image with respect to the left RGB image (or the transformation matrix of the left RGB image with respect to the right RGB image). In theory, O1P1 and O2P2 intersect at a point P in a three-dimensional space, but due to the influence of noise, O1P1 and O2P2 cannot intersect, a point P' closest to the point P can be solved by a least square method, three-dimensional depth information of a real scene is obtained, and the three-dimensional depth information is represented in a vector matrix form.

The specific calculation process is packaged in an OpenCV function, and the three-dimensional depth information of the real scene can be directly determined through function call, and the specific function is as follows:

cv：：triangulatePoints(PoseL，PoseR，Point2DL，Point2DR，Point3D)

the PoseL represents pose information of the left camera, the PoseR represents pose information of the right camera, the Point2DL represents 2D coordinates of a Point P in a three-dimensional space in a left RGB image, the Point2DR represents 2D coordinates of the Point P in the three-dimensional space in the right RGB image, and the Point3D is the 3D coordinates of the Point P after solving and comprises depth information.

S603: and determining the difference value of the multidimensional vector matrixes at the two adjacent moments according to the multidimensional vector matrix at the current moment and the multidimensional vector matrix at the last moment.

In S603, the manner of determining the multi-dimensional vector matrix at the previous time is the same as that at the current time, and is not repeated here.

In S603, according to the difference between the multidimensional vector matrices at the current time and the previous time, the depth information change condition of the real scene in the view angle area at the two adjacent times can be obtained, so as to identify the shape of the object in the real scene.

In some embodiments, for VR devices of the associated external device (e.g., a handle), when the VR display screen content is controlled by the external device, the external device may enter into the field angle region of the binocular camera, so after determining the multi-dimensional vector matrix difference between two adjacent moments in S602, the method further includes: and updating the multidimensional vector matrix difference value according to the position change matrix of the external device associated with the VR device from the last moment to the current moment so as to reduce the interference of the external device on the identification target object. Specifically, on the basis of the determined multidimensional vector matrix difference value, subtracting the position change matrix of the external equipment to obtain an updated multidimensional vector matrix difference value.

It should be noted that, VR devices support spatial positioning of external devices, and may obtain position change information of the external devices, and represent the position change information in a matrix form.

Experimental results prove that the embodiment of the application has good recognition effect on target objects in shapes such as human, sphere, ellipse, cylinder and the like.

S604: and identifying whether a target object exists in the field angle area according to the multi-dimensional vector matrix difference value, if so, executing S605, otherwise, returning to S601.

In S604, the multidimensional vector matrix difference is input into a pre-trained shape recognition model, and whether a target object exists in the view angle area is recognized based on the confidence results of the respective shapes output from the shape recognition model. Optionally, the shape corresponding to the highest confidence in the confidence degrees larger than the confidence degree threshold is taken as the shape of the target object in the view angle area. Wherein the shape recognition model is trained based on object data comprising a plurality of shape contours of depth information.

S605: and determining whether the target object is located in a preset safety area of the VR device, if so, executing S606, otherwise, returning to S601.

In S605, after identifying the target object, determining a center point of the target object, and determining whether the center point is within a preset safety area, if it is determined that the center point is within the preset safety area, determining that the target object is within the safety area.

S606: and (5) giving a safety prompt message.

In S606, when the target object is located in the preset security area of the VR device, a potential safety hazard is brought to the VR experimenter, so that prompt information needs to be given to enable the experimenter to avoid the target object.

It should be noted that, the mode of the prompt message is not limited, for example, the prompt message may be displayed on a display screen of the VR device, or may be broadcast in a voice mode, or may be prompted in a vibration mode.

In some embodiments of the present application, according to the field angle range of the binocular camera, the preset safety area of the VR device may be divided into areas with different safety levels in advance, as shown in fig. 9, the binocular camera is denoted by 1 and 2, the field angle range is denoted by stippling, and the preset safety area (denoted by dotted line) is divided into A, B, C three areas, where the safety level of the area a is two, the safety level of the area B, C is one, and the safety level of the area a is less than the safety level of the area a. In S606, according to the security level corresponding to the security area where the target object is located, a security prompt message matching the security level is given.

For example, when the target object is located in the area a, the security level of the area a is two, and the identified target object is displayed in a special manner (such as strobing, adding a dashed box, etc.) on the display screen, and a voice prompt is performed, so that attention of the experimenter is drawn.

For another example, when the target object is located in the region C, the security level of the region C is first level, and then the target object (spherical object) is directly displayed in the display screen to remind the experimenter to bypass the object, and the display interface is shown in fig. 10.

In some embodiments, there may be multiple objects simultaneously entering the field of view range, i.e., when multiple target objects are identified in S604, priority levels of the multiple target objects may be determined first.

Alternatively, the priority level is determined according to the area size of each of the plurality of target objects, and the larger the area is, the higher the risk coefficient of the target object is, the higher the corresponding priority should be, that is, the higher and lower the priority level is positively correlated with the area size. Alternatively, the priority level is determined according to the distance between the plurality of target objects and the VR device, and the closer the distance is, the higher the risk coefficient of the target object is, the higher the corresponding priority should be, and the height of the priority level is inversely related to the distance.

Further, in S605, it is determined whether the center points of the plurality of target objects are located within a preset security area of the VR device, respectively, according to the determined priority levels.

It should be noted that, when two or more areas of the target object form a communication area, the target object may be regarded as one target object.

In some embodiments, the recognition frequency of the target object is set to be 20fps, in order to reduce the interference of the safety prompt information on the VR experimenter, for the target object smaller than the preset threshold, for example, the pixel number of the area occupied by the shape of the target object is less than 32×40, or the distance between the center point of the target object and the VR device is greater than 5m, a vibration sound about 5s may be given to prompt that an object enters the safety area.

Based on the same technical concept, the embodiments of the present application provide a VR device, which may implement the target recognition-based security prompt method provided in the embodiments of the present application, and may achieve the same technical effects, which are not repeated herein.

The device comprises a display 1101, a lens 1102, a binocular camera 1103, an inertial sensor 1104, a memory 1105, a processor 1106 as shown in fig. 11. Wherein the display screen 1101 is configured to display VR images, the lens 1102 is configured to map a picture displayed on the display screen 1101 onto a retina using a ray refraction principle, the binocular camera 1103 is configured to acquire binocular images in a real scene, the inertial sensor 1104 is configured to acquire motion data of the VR device, the memory 1105 is configured to store computer program instructions, and the processor 1106 is configured to perform the following operations according to the computer program instructions stored by the memory 1105:

respectively acquiring RGB images in a field angle area acquired by a binocular camera at the current moment and motion data of VR equipment acquired by an inertial sensor;

determining a multidimensional vector matrix representing real scene depth information in a view angle area according to the two RGB images and the motion data;

identifying whether a target object exists in the field angle area according to the difference value of the multidimensional vector matrix;

if the target object is identified, when the target object is located in a preset safety area of the VR device, safety prompt information is given.

Optionally, if the VR device has an associated external device 1107, after determining the multidimensional vector matrix difference between two adjacent time instances, the processor 1106 is further configured to:

and updating the multidimensional vector matrix difference value according to the position change matrix of the external device associated with the VR device from the last time to the current time.

Optionally, when the field angle region includes a plurality of target objects, the processor 1106 is specifically configured to:

determining priority levels of a plurality of target objects;

and respectively determining whether the center points of the plurality of target objects are positioned in a preset safety area of the VR equipment according to the priority level, and if so, determining that the corresponding target objects are positioned in the preset safety area of the VR equipment.

Optionally, the processor 1106 is specifically configured to:

determining a priority level according to the area sizes of the target objects, wherein the priority level is positively correlated with the area sizes; or alternatively

And determining a priority level according to the distance between the plurality of target objects and the VR equipment, wherein the height of the priority level is inversely related to the distance.

Optionally, the preset security area is divided into a plurality of security level areas, and the processor 1106 is specifically configured to:

and according to the security level corresponding to the security area where the target object is located, giving out security prompt information matched with the security level.

Optionally, the security level is divided according to the field angle of the binocular camera.

It should be noted that the processor referred to above in the embodiments of the present application may be a central processing unit (central processing unit, CPU), a general purpose processor, a digital signal processor (digital signal processor, DSP), an application-specific integrated circuit (application-specific integrated circuit, ASIC), a field programmable gate array (field programmable gate array, FPGA) or other programmable logic device, a transistor logic device, a hardware component, or any combination thereof. Which may implement or perform the various exemplary logic blocks, modules, and circuits described in connection with this disclosure. A processor may also be a combination that performs computing functions, e.g., including one or more microprocessors, a combination of a DSP and a microprocessor, and so forth. The memory may be integrated into the processor or may be provided separately from the processor.

The present application also provides a computer-readable storage medium storing computer-executable instructions for causing a computer to perform the methods of the above embodiments.

The present application also provides a computer program product for storing a computer program for performing the method of the foregoing embodiments.

Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present application.

The foregoing description, for purposes of explanation, has been presented in conjunction with specific embodiments. However, the illustrative discussions above are not intended to be exhaustive or to limit the embodiments to the precise forms disclosed above. Many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles and the practical application, to thereby enable others skilled in the art to best utilize the embodiments and various embodiments with various modifications as are suited to the particular use contemplated.

Claims

1. The safety prompting method based on target identification is characterized by being applied to Virtual Reality (VR) equipment, wherein the VR equipment has associated external equipment and comprises the following steps:

respectively acquiring RGB images in a field angle area acquired by a binocular camera at the current moment and motion data of the VR equipment acquired by an inertial sensor, wherein the binocular camera comprises a left camera and a right camera;

determining pose information of VR equipment through two RGB images and the motion data, respectively determining pose information of left and right cameras according to the pose information of the VR equipment, respectively extracting two-dimensional information of a real scene in a view angle area from the RGB images acquired by the left and right cameras by utilizing the pose information of the left and right cameras and a pre-trained model, and determining depth information based on the two-dimensional information by utilizing a triangle measurement method to obtain a multidimensional vector matrix for representing the depth information of the real scene in the view angle area;

determining the difference value of the multidimensional vector matrixes at two adjacent moments according to the multidimensional vector matrix at the current moment and the multidimensional vector matrix at the last moment; the multi-dimensional vector matrix difference values of the two adjacent moments are used for representing the depth information change condition of the real scene in the view angle area of the two adjacent moments;

updating the multidimensional vector matrix difference value according to the position change matrix of the external device associated with the VR device from the last time to the current time;

if the target object is identified, when the target object is located in a preset safety area of the VR equipment, safety prompt information is given; the preset safety area is divided into a plurality of safety-level areas, and the step of giving the safety prompt information comprises the following steps: and according to the security level corresponding to the security area where the target object is located, security prompt information matched with the security level is given, wherein the security level comprises a first security level and a second security level, when the security level is the first security level, the target object is displayed in a display screen to remind an experienter to bypass, and when the security level is the second security level, the security prompt information is displayed in the display screen in a stroboscopic or dashed line frame adding mode.

2. The method of claim 1, wherein when a plurality of target objects are included in the field of view region, determining whether the target objects are located in a preset safe region of the VR device is performed by:

determining a priority level of the plurality of target objects;

3. The method of claim 2, wherein the determining the priority level of the plurality of target objects comprises:

determining the priority level according to the area size of each of the plurality of target objects, wherein the height of the priority level is positively correlated with the area size; or alternatively

And determining the priority level according to the distance between the plurality of target objects and the VR equipment, wherein the height of the priority level is inversely related to the distance.

4. The method of claim 1, wherein the security level is divided according to a field angle of the binocular camera, and a security level of a common coverage area of the binocular camera is higher than a security level of a non-common coverage area.

5. The utility model provides a virtual reality VR equipment, its characterized in that includes display screen, lens, binocular camera, inertial sensor, memory, treater, VR equipment exists associated external device:

the display screen is configured to display VR images;

the inertial sensor is configured to collect motion data of the VR device;

the memory is configured to store computer program instructions;

if the target object is identified, when the target object is located in a preset safety area of the VR device, a safety prompt message is given, wherein the preset safety area is divided into a plurality of safety-level areas, and the processor is specifically configured to: and according to the security level corresponding to the security area where the target object is located, security prompt information matched with the security level is given, wherein the security level comprises a first security level and a second security level, when the security level is the first security level, the target object is displayed in a display screen to remind an experienter to bypass, and when the security level is the second security level, the security prompt information is displayed in the display screen in a stroboscopic or dashed line frame adding mode.

6. The VR device of claim 5, wherein when the field of view region includes a plurality of target objects, the processor is specifically configured to:

determining a priority level of the plurality of target objects;