Depth perception evaluation method and device, storage medium and electronic equipment

Abstract

The invention discloses a depth perception evaluation method and device, a storage medium and electronic equipment, and the method comprises the steps: obtaining a recommendation task level of a target user, wherein the task level comprises a task parameter; constructing a 3D scene and a virtual reality VR scene based on the task parameters; in the 3D scene and the virtual reality VR scene, obtaining the distance between the controlled object and the reference object and the time spent by the target user for completing the task; and evaluating the depth perceptual ability of the target user based on the distance and the time spent by the target user in completing the task. The evaluation method provided by the invention is not limited by physical equipment and environmental conditions, and can accurately evaluate the depth perception ability of the user.

Description

Technical Field

[0001] The present application relates to the technical field of personnel ability assessment, and in particular to a depth perception assessment method, a depth perception assessment device, a computer-readable storage medium, and an electronic device. Background Art

[0002] Depth perception refers to a person's perception of the distance of an object, i.e. the depth. It is an assessment of an individual's ability to judge the distance of an object, and is crucial for professional skill training and daily activities. For example, a car driver's visual depth perception is significantly positively correlated with safe driving conditions; stereoscopic vision examinations when enlisting in the army are very necessary to ensure the quality of military personnel; and individual depth perception training can effectively improve the effectiveness of ball game teaching and training. However, traditional depth perception assessments are usually conducted in laboratory environments, which are limited by physical equipment and environmental conditions, and their accuracy and practicality need to be improved. Summary of the invention

[0003] The present application aims to solve at least one of the technical problems in the related art to a certain extent. To this end, the first purpose of the present application is to propose a depth perception evaluation method, obtain the recommended task level of the target user, the task level includes task parameters, and construct a 3D scene and a virtual reality VR scene based on the task parameters; in the 3D scene and the virtual reality VR scene, obtain the distance between the controlled object and the reference object and the time taken by the target user to complete the task, and evaluate the depth perception ability of the target user based on the distance and the time taken by the target user to complete the task, thereby accurately evaluating the depth perception ability of the user without being restricted by physical equipment and environmental conditions.

[0004] The second objective of this application is to propose a depth perception assessment device.

[0005] The third object of the present application is to provide a computer-readable storage medium.

[0006] The fourth objective of the present application is to provide an electronic device.

[0007] To achieve the above-mentioned objectives, the first aspect of the present application proposes a depth perception assessment method, which includes: obtaining a recommended task level for a target user, wherein the task level includes task parameters; constructing a 3D scene and a virtual reality (VR) scene based on the task parameters; in the 3D scene and the virtual reality (VR) scene, obtaining the distance between a controlled object and a reference object and the time taken by the target user to complete the task; and evaluating the depth perception ability of the target user based on the distance and the time taken by the target user to complete the task.

[0008] According to the depth perception evaluation method of the embodiment of the present application, the recommended task level of the target user is obtained, and the task level includes task parameters. A 3D scene and a virtual reality VR scene are constructed based on the task parameters. In the 3D scene and the virtual reality VR scene, the distance between the controlled object and the reference object and the time taken by the target user to complete the task are obtained, and the depth perception ability of the target user is evaluated based on the distance and the time taken by the target user to complete the task. Therefore, the method can accurately evaluate the depth perception ability of the user without being restricted by physical equipment and environmental conditions.

[0009] In addition, the depth perception evaluation method according to the above embodiment of the present application may also have the following additional technical features:

[0010] According to one embodiment of the present application, the depth perception ability of the target user is evaluated based on the distance and the time taken by the target user to complete the task, including: when the distance is less than a distance threshold corresponding to the recommended task level and the time taken by the target user to complete the task is less than a time threshold corresponding to the recommended task level, determining the depth perception evaluation result; wherein, the smaller the distance is, the shorter the time taken by the target user to complete the task, and the better the depth perception evaluation ability is.

[0011] According to one embodiment of the present application, the task parameters include at least one of the reference object type, the number of reference objects, the reference object position, and the set moving speed of the controlled object, wherein the more the number of reference objects, the higher the task level, the greater the set moving speed of the controlled object, the higher the task level, and the more complex the reference object type, the higher the task level.

[0012] According to one embodiment of the present application, obtaining the recommended task level of a target user includes: obtaining the last subjective evaluation result and the last objective evaluation result of the target user; when the last objective evaluation result and the last subjective evaluation result meet a preset condition, using the next level of the task level at the last evaluation as the recommended task level; when the last objective evaluation result and the last subjective evaluation result do not meet the preset condition, using the task level at the last evaluation as the recommended task level.

[0013] According to an embodiment of the present application, the method further includes: during the evaluation of the target user, dynamically adjusting the recommended task level based on the moving speed of the object manipulated by the target user.

[0014] According to an embodiment of the present application, the method further includes: acquiring a speed change rate of the controlled object; and determining that the user operation is abnormal when the speed change rate is greater than a preset threshold.

[0015] According to an embodiment of the present application, the method further includes: acquiring a target motion trajectory of the controlled object; and determining that the user operation is abnormal when the current motion trajectory is inconsistent with the target motion trajectory.

[0016] To achieve the above-mentioned purpose, the second aspect of the present application proposes a device based on depth perception evaluation, which includes: a first acquisition module, used to obtain the recommended task level of the target user, and the task level includes task parameters; a construction module, used to construct a 3D scene and a virtual reality VR scene based on the task parameters; a second acquisition module, used to obtain the distance between the controlled object and the reference object and the time taken by the target user to complete the task in the 3D scene and the virtual reality VR scene; an evaluation module, used to evaluate the depth perception ability of the target user based on the distance and the time taken by the target user to complete the task.

[0017] According to the depth perception evaluation device of the embodiment of the present application, the first acquisition module is used to obtain the recommended task level of the target user, the task level includes task parameters, the construction module is used to construct 3D scenes and virtual reality VR scenes based on the task parameters, the second acquisition module is used to obtain the distance between the controlled object and the reference object and the time it takes for the target user to complete the task in the 3D scene and virtual reality VR scene, and the evaluation module is used to evaluate the depth perception ability of the target user based on the distance and the time it takes for the target user to complete the task. As a result, the device can accurately evaluate the depth perception ability of the user without being restricted by physical equipment and environmental conditions.

[0018] To achieve the above-mentioned purpose, the third aspect of the present application proposes a computer-readable storage medium on which a program is stored, and when the program is executed by a processor, the above-mentioned depth perception assessment method is implemented.

[0019] According to the computer-readable storage medium of the embodiment of the present application, the above-mentioned depth perception assessment method is implemented during execution, which is not limited by physical equipment and environmental conditions and can accurately assess the user's depth perception ability.

[0020] To achieve the above-mentioned purpose, an electronic device proposed in the fourth aspect of the present application includes a memory, a processor, and a program stored in the memory and executable on the processor. When the processor executes the program, the above-mentioned depth perception assessment method is implemented.

[0021] According to the electronic device of the embodiment of the present application, by executing the above-mentioned depth perception assessment method, it is possible to accurately assess the user's depth perception ability without being restricted by physical equipment and environmental conditions.

[0022] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 is a flow chart of a depth perception evaluation method according to an embodiment of the present application;

[0024] Figure 2 is a flowchart of a depth perception evaluation method according to a specific example of the present application;

[0025] Figure 3 Schematic diagram of a depth perception evaluation device according to an embodiment of the present application;

[0026] Figure 4 Schematic diagram of a block diagram of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0027] Embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0028] The following describes the depth perception assessment method, depth perception assessment device, computer-readable storage medium and electronic device proposed in the embodiments of the present application with reference to the accompanying drawings.

[0029] Figure 1 Flowchart of a depth perception assessment method according to an embodiment of the present application.

[0030] like Figure 1 As shown, the depth perception evaluation method of the embodiment of the present application may include the following steps:

[0031] S1, obtaining the recommended task level of the target user, where the task level includes task parameters.

[0032] S2, constructs 3D scenes and virtual reality VR scenes based on task parameters.

[0033] S3, in 3D scenes and virtual reality VR scenes, obtains the distance between the controlled object and the reference object and the time it takes for the target user to complete the task.

[0034] S4, evaluates the depth perception ability of the target user based on the distance and the time it takes for the target user to complete the task.

[0035] Specifically, the recommended task level of the target user can be obtained first, and the task level includes task parameters. For example, the recommended task level can be determined based on the user's past performance, ability assessment results, and personal preferences. The task level includes task parameters such as the type of reference objects, the number of reference objects, the location of the reference objects, and the set moving speed of the controlled object. Suppose that based on the user's last evaluation results, the user is recommended to perform a task of medium difficulty. The parameters corresponding to this task level may be: the number of reference objects is 5, the type of reference object is a medium-complexity graphic, and the set moving speed of the controlled object is medium speed.

[0036] After determining the task parameters, 3D scenes and virtual reality (VR) scenes can be constructed according to the task parameters. These scenes will simulate the depth perception challenges of the real world for users to conduct depth perception assessments. For example, by using graphics libraries such as OpenGL, 3D models and scenes are constructed by defining information such as vertices and texture coordinates. For example, a scene containing multiple reference objects of different types and positions is created, and the user needs to manipulate the controlled object in the scene. In a virtual reality (VR) scene, the user will immerse himself in a virtual environment through a head-mounted device and interact with objects in the 3D scene.

[0037] For example, the task uses a right-handed coordinate system, which is a coordinate system in three-dimensional space in which the X-axis, Y-axis, and Z-axis are perpendicular to each other. The positive direction of the X-axis is defined as to the right, the positive direction of the Y-axis is defined as upward, and the positive direction of the Z-axis points to the outside of the screen, that is, from the screen to the observer. In the 3D scene, one or more reference objects and at least one target object are displayed. The reference objects are located at different X-coordinates but have the same Y and Z coordinates, which means that they are scattered in the horizontal direction but at the same distance from the observer in the vertical direction and depth direction. The target object is not initially at the same Z-coordinate as the reference object, that is, it is not in the same position as the reference object in the depth direction. The user's task is to move the target object on the Z-axis by operating (such as using a VR handle, keyboard, mouse, etc.). The goal is to adjust the position of the target object until it is visually in the same position as the reference object, which means that the user needs to accurately judge and operate the target object so that it is aligned with the reference object in depth. The user needs to rely on visual cues to judge whether the target object has been aligned with the reference object in depth. This task tests the user's depth perception, that is, the ability to judge the distance of objects, which is very important for many professional skills (such as driving, flying, sports, etc.). Through this objective assessment task, the user's depth perception ability and their ability to manipulate objects in a virtual environment can be evaluated. The time and accuracy required for the user to complete the task will be recorded. This data can be used to evaluate the user's depth perception ability and serve as a basis for subsequent training and assessment.

[0038] That is, in 3D scenes and virtual reality VR scenes, the distance between the controlled object and the reference object and the time it takes for the target user to complete the task are obtained. For example, the user needs to move a virtual sphere to a position aligned with multiple virtual cubes. The distance between the sphere and the nearest cube can be measured, and the time required for the user to complete this task, that is, the time it takes for the user to complete the task, can be recorded. Therefore, the user's depth perception ability can be evaluated based on the distance error between the controlled object manipulated by the user and the reference object, and the time required to complete the task. For example, in the task, the user moves the sphere to a position very close to the cube and takes a short time, indicating that the user's depth perception ability is good. As a result, personalized task recommendations can be provided to users, and the user's depth perception ability can be accurately evaluated.

[0039] According to an embodiment of the present application, the depth perception ability of the target user is evaluated based on the distance and the time taken by the target user to complete the task, including: when the distance is less than the distance threshold corresponding to the recommended task level and the time taken by the target user to complete the task is less than the time threshold corresponding to the recommended task level, determining the depth perception evaluation result; wherein, the smaller the distance, the shorter the time taken by the target user to complete the task, and the better the depth perception evaluation ability. The distance threshold and the time threshold can be determined according to actual conditions.

[0040] Specifically, when evaluating the depth perception ability of the target user based on the distance and the time it takes for the target user to complete the task, each recommended task level corresponds to a distance threshold and a time threshold. The distance threshold refers to the maximum distance error allowed for the user to complete the task, and the time threshold refers to the maximum time allowed for completing the same task. During the evaluation process, the actual distance error and time required for the user to manipulate the object are recorded, and these data will be compared with the corresponding task level threshold. If the distance error of the user in the evaluation is less than or equal to the distance threshold corresponding to the recommended task level, and the time it takes for the target user to complete the task is less than or equal to the time threshold corresponding to the recommended task level, the user's depth perception evaluation result is considered to be good. In this case, the user's depth perception ability is considered to be good because they can complete the task with less error and time. And the smaller the distance, that is, the smaller the error between the actual position of the object manipulated by the user and the target position, the more accurate the user's depth perception is, and the shorter the time it takes for the target user to complete the task, the higher the user's reaction speed and operation efficiency are, which is also a sign of good depth perception ability. In other words, the shorter the time and the shorter the distance, the stronger the depth perception ability of the subject.

[0041] Therefore, based on the evaluation results, the difficulty of subsequent tasks can be adjusted to adapt to the user's depth perception ability, ensuring that the user is trained and improved at a level that suits their ability. In this way, the user's depth perception ability in a virtual environment can be objectively evaluated, and personalized task recommendations can be provided to optimize the user's training effect.

[0042] According to one embodiment of the present application, the task parameters include at least one of the reference object type, the number of reference objects, the reference object position, and the set moving speed of the controlled object, wherein the more the number of reference objects, the higher the task level, the greater the set moving speed of the controlled object, the higher the task level, and the more complex the reference object type, the higher the task level.

[0043] Specifically, the task parameters include the type of reference object, the number of reference objects, the position of the reference objects, and the set movement speed of the controlled object. These parameters together determine the difficulty and complexity of the task. Among them, the type of reference object: involves the visual complexity of the reference object. For example, the more complex the style of the reference object is, the greater the challenge to the user's depth perception ability. The number of reference objects: affects the difficulty of the task. The more the number, the greater the amount of information the user needs to process, and the task level increases accordingly. The position of the reference object: the position information determines the layout of the reference object in the virtual space, which affects the user's judgment of depth. The set movement speed of the controlled object: affects the speed requirements of the user's operation. The faster the speed, the higher the requirements for the user's reaction speed and operation accuracy.

[0044] In addition, the number of reference objects, the setting and moving speed of the controlled object, and the complexity of the reference object type are positively correlated with the task level, that is, the more reference objects there are, the higher the task level is, the faster the setting and moving speed of the controlled object is, the higher the task level is, the more complex the reference object type is, and the higher the task level is; the fewer reference objects there are, the lower the task level is, the slower the setting and moving speed of the controlled object is, the lower the task level is, the easier the reference object type is, and the lower the task level is.

[0045] According to an embodiment of the present application, obtaining the recommended task level of the target user includes: obtaining the last subjective evaluation result and the last objective evaluation result of the target user; when the last objective evaluation result and the last subjective evaluation result meet the preset conditions, taking the next level of the task level at the last evaluation as the recommended task level; when the last objective evaluation result and the last subjective evaluation result do not meet the preset conditions, taking the task level at the last evaluation as the recommended task level. The preset conditions may be determined according to actual conditions.

[0046] Specifically, the subjective and objective evaluation results of the target user in the last depth perception test are obtained. The subjective evaluation may include the user's self-evaluation of his or her own performance, such as by providing a subjective questionnaire scale, so that the user can evaluate his or her own performance after the task. The objective evaluation is an evaluation based on the user's actual performance in the task (such as the accuracy and speed of manipulating objects). A series of preset conditions are set, which may include the user's score in the objective evaluation, the time to complete the task, the accuracy of manipulating objects, etc. These conditions are used to evaluate whether the user is ready to accept more difficult tasks.

[0047] Determine whether the last subjective assessment result and the last objective assessment result meet the preset conditions. If the user's last objective assessment result and the last subjective assessment result both meet the preset conditions, indicating that the user performed well in the last assessment, the next level of the task level at the time of the last assessment will be used as the recommended task level. This means that a more difficult task will be recommended to the user to challenge the user's limits and promote the improvement of his or her ability. If the user's last objective assessment result and the last subjective assessment result do not meet the preset conditions, the user's task level at the time of the last assessment will be maintained as the recommended task level. This is done to ensure that users can continue to practice and improve at the current level until they are ready to accept more difficult tasks. This method of dynamically adjusting task levels based on user performance can provide more personalized recommendations, allowing each user to train at a difficulty level that suits them, thereby maximizing learning efficiency and effectiveness.

[0048] As a result, the recommended task level can be dynamically adjusted according to the user's real-time performance and ability level to achieve personalized and effective ability improvement.

[0049] According to an embodiment of the present application, the depth perception evaluation method further includes: during the evaluation of the target user, dynamically adjusting the recommended task level based on the moving speed of the object manipulated by the target user.

[0050] Specifically, by tracking the user's behavior of manipulating objects in a virtual environment, the speed of movement is measured in real time. This measurement can be achieved through various sensors, cameras or VR devices to obtain accurate speed data. The speed data of the user's manipulation of objects is analyzed to evaluate the user's depth perception ability and reaction speed. That is, the speed can reflect the user's mastery of the task and the accuracy of the operation. Therefore, the recommended task level can be automatically adjusted according to the user's manipulation speed of the object. For example, if the user's operation speed is fast, it means that the user has a high degree of mastery of the current task, and a higher difficulty task will be recommended to provide a challenge; if the operation speed is slow, a lower difficulty task can be recommended to ensure that the user can gradually adapt and improve his skills.

[0051] Continuously track the user's performance at different task levels and evaluate changes in their depth perception ability. In this way, the task difficulty can be adjusted more accurately to match the user's real-time ability and learning needs. As a result, it can be more flexible and responsive to user needs, providing a personalized and adaptive assessment experience, thereby improving the accuracy and effectiveness of the assessment.

[0052] According to an embodiment of the present application, the depth perception evaluation method further includes: obtaining a speed change rate of the controlled object; and determining that the user operation is abnormal when the speed change rate is greater than a preset threshold value. The preset threshold value may be determined according to actual conditions.

[0053] Specifically, by tracking the movement of the controlled object in the virtual environment, its speed is calculated in real time. The speed change rate refers to the amount of change in the speed of an object in a short period of time, which can be obtained by calculating the speed difference between two consecutive time points, that is, the speed change rate = speed at the next time point - speed at the previous time point / time interval. And in order to determine whether the user operation is abnormal, it is necessary to set a preset threshold value for the speed change rate. This threshold value is determined based on the speed change range under normal operating conditions and can be obtained by expert experience, historical data or statistical analysis. In addition, the setting of the preset threshold value needs to consider a variety of factors, including the complexity of the task, the user's skill level, environmental conditions, etc., to ensure that the threshold value can both sensitively capture abnormalities and not be falsely reported due to minor fluctuations in normal operations.

[0054] The speed change rate calculated in real time is compared with the preset threshold. If the speed change rate exceeds this threshold, it can be considered that the user's operation is abnormal. That is, when the speed change rate exceeds the preset threshold, this event will be marked as an operation abnormality, which may mean that the user has encountered difficulties in performing the task, or their operation method does not meet the expected standards. This abnormality may be caused by user mistakes, deviations in task understanding, lack of skills, or external interference (such as equipment failure, environmental changes, etc.). Once an operation abnormality is detected, corresponding measures can also be taken, such as providing immediate feedback, adjusting task difficulty, providing additional guidance, or pausing the task to help users correct operations or adapt to new task requirements. And these abnormal events can also be recorded for subsequent analysis of user performance, optimization of the evaluation system, or for training and education purposes.

[0055] As a result, users’ operational performance can be evaluated more accurately, and operational anomalies can be identified and responded to in a timely manner, thereby improving the accuracy and effectiveness of the evaluation.

[0056] According to an embodiment of the present application, the depth perception evaluation method further includes: obtaining a target motion trajectory of the controlled object; and determining that the user operation is abnormal when the current motion trajectory is inconsistent with the target motion trajectory.

[0057] Specifically, the target motion trajectory of the controlled object is obtained. The target motion trajectory is a standard path set based on task requirements and expected operation results. This trajectory reflects the ideal operation method and efficiency required to complete the task. The current motion trajectory can be accurately captured by sensors, cameras, or tracking technology in VR devices, so that the current motion trajectory can be compared with the target motion trajectory. This process can be automatically completed by algorithms to evaluate the accuracy and efficiency of user operations. If the user's current motion trajectory is inconsistent with the target motion trajectory, this deviation will be identified. This inconsistency indicates that the user has encountered difficulties in performing the task, or their operation method does not meet the expected standards, and the user's operation can be determined to be abnormal. A threshold can be set to determine the degree of deviation. If it exceeds this threshold, it is considered abnormal. This abnormality detection mechanism can help identify possible problems that users may have in depth perception tasks, such as operational errors, understanding deviations, or insufficient skills.

[0058] Once an anomaly is detected, corresponding measures can be taken, such as providing immediate feedback, adjusting the difficulty of the task, or providing additional guidance, which helps the user correct the operation and improve the accuracy and efficiency of task completion. In this way, not only can the user's depth perception ability be evaluated, but personalized feedback and guidance can also be provided through the anomaly detection mechanism, thereby improving the user's depth perception skills and task execution ability.

[0059] Combine the following Figure 2 To describe the method of the present application.

[0060] As a specific example, the depth perception evaluation method of the present application may include the following steps:

[0061] S101, obtaining the last subjective evaluation result and the last objective evaluation result of the target user.

[0062] S102, judging whether the last objective evaluation result and the last subjective evaluation result meet the preset conditions. If yes, executing step S103; if not, executing step S113.

[0063] S103, taking the next level of the task level in the last evaluation as the recommended task level.

[0064] S104, obtaining the recommended task level of the target user, the task level includes task parameters, and the task parameters include at least one of the reference object type, the number of reference objects, the reference object position, and the set moving speed of the controlled object. Among them, the more the number of reference objects, the higher the task level; the greater the set moving speed of the controlled object, the higher the task level; the more complex the reference object type, the higher the task level.

[0065] S105, constructing a 3D scene and a virtual reality VR scene based on the task parameters.

[0066] S106, in the 3D scene and the virtual reality VR scene, obtaining the distance between the controlled object and the reference object and the time taken by the target user to complete the task.

[0067] S107, determine whether the distance is less than the distance threshold corresponding to the recommended task level and whether the time taken by the target user to complete the task is less than the time threshold corresponding to the recommended task level. If yes, execute step S108; if not, execute step S104.

[0068] S108, determining the evaluation result of depth perception, wherein the smaller the distance is, the shorter the time taken by the target user to complete the task is, and the better the depth perception evaluation capability is.

[0069] S109, obtaining the speed change rate of the controlled object and the target motion trajectory of the controlled object.

[0070] S110, determining whether the speed change rate is greater than a preset threshold or whether the current motion trajectory is inconsistent with the target motion trajectory. If yes, executing step S111; if not, executing step S112.

[0071] S111, determining that the user operation is abnormal.

[0072] S112, dynamically adjust the recommended task level based on the moving speed of the object manipulated by the target user, and proceed to step S104.

[0073] S113, taking the task level at the last evaluation as the recommended task level, and proceeding to step S104.

[0074] In summary, according to the depth perception evaluation method of the embodiment of the present application, the recommended task level of the target user is obtained, and the task level includes task parameters. A 3D scene and a virtual reality VR scene are constructed based on the task parameters; in the 3D scene and the virtual reality VR scene, the distance between the controlled object and the reference object and the time taken by the target user to complete the task are obtained, and the depth perception ability of the target user is evaluated based on the distance and the time taken by the target user to complete the task. Therefore, the method can accurately evaluate the depth perception ability of the user without being restricted by physical equipment and environmental conditions.

[0075] Corresponding to the above embodiments, the present application also proposes a depth perception assessment device.

[0076] like Figure 3 As shown, the depth perception evaluation device 100 according to the embodiment of the present application includes: a first acquisition module 110 , a construction module 120 , a second acquisition module 130 and an evaluation module 140 .

[0077] The first acquisition module 110 is used to obtain the recommended task level of the target user, and the task level includes task parameters. The construction module 120 is used to construct a 3D scene and a virtual reality VR scene based on the task parameters. The second acquisition module 130 is used to obtain the distance between the controlled object and the reference object and the time it takes for the target user to complete the task in the 3D scene and the virtual reality VR scene. The evaluation module 140 is used to evaluate the depth perception ability of the target user based on the distance and the time it takes for the target user to complete the task.

[0078] According to one embodiment of the present application, the evaluation module 140 evaluates the depth perception ability of the target user based on the distance and the time taken by the target user to complete the task, and is specifically used to: determine the evaluation result of the depth perception when the distance is less than the distance threshold corresponding to the recommended task level and the time taken by the target user to complete the task is less than the time threshold corresponding to the recommended task level; wherein, the smaller the distance, the shorter the time taken by the target user to complete the task, and the better the depth perception evaluation ability.

[0079] According to one embodiment of the present application, the task parameters include at least one of the reference object type, the number of reference objects, the reference object position, and the set moving speed of the controlled object, wherein the more the number of reference objects, the higher the task level, the greater the set moving speed of the controlled object, the higher the task level, and the more complex the reference object type, the higher the task level.

[0080] According to one embodiment of the present application, the first acquisition module 110 acquires the recommended task level of the target user, and is specifically used to: acquire the target user's last subjective evaluation result and the last objective evaluation result; when the last objective evaluation result and the last subjective evaluation result meet the preset conditions, use the next level of the task level at the time of the last evaluation as the recommended task level; when the last objective evaluation result and the last subjective evaluation result do not meet the preset conditions, use the task level at the time of the last evaluation as the recommended task level.

[0081] According to an embodiment of the present application, the evaluation module 140 is further used to: during the evaluation of the target user, dynamically adjust the recommended task level based on the moving speed of the object manipulated by the target user.

[0082] According to an embodiment of the present application, the evaluation module 140 is further used to: obtain the speed change rate of the controlled object; and determine that the user operation is abnormal when the speed change rate is greater than a preset threshold.

[0083] According to an embodiment of the present application, the evaluation module 140 is further used to: obtain the target motion trajectory of the controlled object; and determine that the user operation is abnormal when the current motion trajectory is inconsistent with the target motion trajectory.

[0084] It should be noted that for details not disclosed in the depth perception assessment device in the embodiment of the present application, please refer to the details disclosed in the depth perception assessment method in the embodiment of the present application, and the details will not be repeated here.

[0085] According to the depth perception evaluation device of the embodiment of the present application, the first acquisition module is used to obtain the recommended task level of the target user, the task level includes task parameters, the construction module is used to construct 3D scenes and virtual reality VR scenes based on the task parameters, the second acquisition module is used to obtain the distance between the controlled object and the reference object and the time it takes for the target user to complete the task in the 3D scene and virtual reality VR scene, and the evaluation module is used to evaluate the depth perception ability of the target user based on the distance and the time it takes for the target user to complete the task. As a result, the device can accurately evaluate the depth perception ability of the user without being restricted by physical equipment and environmental conditions.

[0086] Corresponding to the above embodiments, the present application also proposes a computer-readable storage medium.

[0087] The computer-readable storage medium of the embodiment of the present application stores a program thereon, and when the program is executed by a processor, the above-mentioned depth perception assessment method is implemented.

[0088] According to the computer-readable storage medium of the embodiment of the present application, by executing the above-mentioned depth perception assessment method, it is possible to accurately assess the user's depth perception ability without being restricted by physical equipment and environmental conditions.

[0089] Corresponding to the above embodiment, the present application also proposes an electronic device.

[0090] like Figure 4 As shown, the electronic device 200 of the embodiment of the present application may include: a memory 210, a processor 220, and a program stored in the memory 210 and executable on the processor 220. When the processor 220 executes the program, the above-mentioned depth perception assessment method is implemented.

[0091] According to the electronic device of the embodiment of the present application, by executing the above-mentioned depth perception assessment method, it is possible to accurately assess the user's depth perception ability without being restricted by physical equipment and environmental conditions.

[0092] It should be noted that the logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be specifically implemented in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection portion with one or more wirings (electronic device), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or processing in other suitable ways if necessary, and then stored in a computer memory.

[0093] It should be understood that the various parts of the present application can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0094] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0095] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In the description of this application, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0096] In this application, unless otherwise clearly specified and limited, the terms "installed", "connected", "connected", "fixed" and the like should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, it can be the internal connection of two elements or the interaction relationship between two elements, unless otherwise clearly defined. For ordinary technicians in this field, the specific meanings of the above terms in this application can be understood according to specific circumstances.

[0097] Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limitations on the present application. Ordinary technicians in this field can change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A depth perception evaluation method, characterized in that: The method comprises: Obtaining a recommended task level for a target user, wherein the task level includes task parameters; Constructing a 3D scene and a virtual reality VR scene based on the task parameters; In the 3D scene and the virtual reality VR scene, obtaining the distance between the controlled object and the reference object and the time taken by the target user to complete the task; The depth perception ability of the target user is assessed based on the distance and the time taken by the target user to complete a task.

2. The depth perception evaluation method according to claim 1, characterized in that: The depth perception ability of the target user is evaluated based on the distance and the time taken by the target user to complete the task, including: When the distance is less than the distance threshold corresponding to the recommended task level and the time taken by the target user to complete the task is less than the time threshold corresponding to the recommended task level, the depth perception assessment result is determined; wherein, the smaller the distance is, the shorter the time taken by the target user to complete the task is, and the better the depth perception assessment ability is.

3. The depth perception evaluation method according to claim 1, characterized in that: The task parameters include at least one of the reference object type, the number of reference objects, the reference object position and the set moving speed of the controlled object, wherein the more the number of reference objects, the higher the task level; the greater the set moving speed of the controlled object, the higher the task level; the more complex the reference object type, the higher the task level.

4. The depth perception evaluation method according to claim 1, characterized in that: Get the recommended task level of the target user, including: Obtain the last subjective evaluation result and the last objective evaluation result of the target user; When the last objective evaluation result and the last subjective evaluation result meet the preset conditions, the next level of the task level at the last evaluation is used as the recommended task level; When the last objective evaluation result and the last subjective evaluation result do not satisfy the preset condition, the task level at the last evaluation is used as the recommended task level.

5. The depth perception evaluation method according to claim 1, characterized in that: The method further comprises: In the process of evaluating the target user, the recommended task level is dynamically adjusted based on the moving speed of the object manipulated by the target user.

6. The depth perception evaluation method according to claim 1, characterized in that: The method further comprises: Obtain the speed change rate of the controlled object; When the speed change rate is greater than a preset threshold, it is determined that the user operation is abnormal.

7. The depth perception evaluation method according to claim 1, characterized in that: The method further comprises: Obtain the target motion trajectory of the controlled object; When the current motion trajectory is inconsistent with the target motion trajectory, it is determined that the user operation is abnormal.

8. A depth perception evaluation device, characterized in that: The device comprises: A first acquisition module is used to acquire a recommended task level for a target user, wherein the task level includes task parameters; A construction module, used to construct a 3D scene and a virtual reality VR scene based on the task parameters; A second acquisition module is used to acquire the distance between the controlled object and the reference object and the time taken by the target user to complete the task in the 3D scene and the virtual reality VR scene; An evaluation module is used to evaluate the depth perception ability of the target user based on the distance and the time taken by the target user to complete the task.

9. A computer-readable storage medium, characterized in that: A program is stored thereon, and when the program is executed by a processor, the depth perception assessment method according to any one of claims 1-7 is implemented.

10. An electronic device, characterized in that: include: A memory, a processor, and a program stored in the memory and executable on the processor, wherein when the processor executes the program, the depth perception assessment method according to any one of claims 1 to 7 is implemented.

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