Vision detection method, robot and equipment

Abstract

The invention discloses a vision detection method, a robot and equipment. The method comprises the following steps: acquiring first image data of a detection object; based on the first image data of the detection object, determining a current vision detection type of the detection object; the current vision detection type is used for representing whether the detected object wears a vision correction appliance or not; based on the current vision detection type of the detection object, determining a vision detection strategy of the detection object; and performing vision detection on the detected object by adopting the vision detection strategy to obtain a vision detection result of the detected object. In this way, the efficiency and convenience of vision testing can be improved.

Description

Technical Field

[0001] This application relates to the field of robotics, and particularly to a vision detection method, a robot, and a device. Background Art

[0002] In the field of medical health, vision detection is a basic and important examination item. Most traditional vision detection methods rely on manual operations, which are time-consuming and laborious, and are difficult to meet the needs of modern society. Existing technical solutions rely on professional medical staff, professional equipment, and medical institutions, which limit the convenience of detection, especially in remote areas or when users have limited time. Summary of the Invention

[0003] In view of this, at least one vision detection method, a robot, and a device are provided in the embodiments of this application.

[0004] The technical solution of the embodiments of this application is implemented as follows:

[0005] In a first aspect, an embodiment of this application provides a vision detection method, which is applied to a robot; the method includes:

[0006] Obtain first image data of a detection object;

[0007] Based on the first image data of the detection object, determine the current vision detection type of the detection object; the current vision detection type is used to represent whether the detection object wears vision correction appliances;

[0008] Based on the current vision detection type of the detection object, determine the vision detection strategy of the detection object;

[0009] Adopt the vision detection strategy to perform vision detection on the detection object to obtain the vision detection result of the detection object.

[0010] In a second aspect, an embodiment of this application provides a robot, which includes a controller and an image acquisition unit; wherein,

[0011] The image acquisition unit is configured to acquire first image data of a detection object;

[0012] The controller is configured to, based on the first image data of the detection object, determine the current vision detection type of the detection object; the current vision detection type is used to represent whether the detection object wears vision correction appliances; based on the current vision detection type of the detection object, determine the vision detection strategy of the detection object; adopt the vision detection strategy to perform vision detection on the detection object to obtain the vision detection result of the detection object.

[0013] In a third aspect, an embodiment of the present application provides a computer device, including a memory and a processor. The memory stores a computer program that can run on the processor. When the processor executes the program, some or all of the steps in the above method are implemented.

[0014] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, some or all of the steps in the above method are implemented.

[0015] In a fifth aspect, an embodiment of the present application provides a computer program product, including a computer program or instruction. When the computer program or instruction is executed by a processor, some or all of the steps in the above method are implemented.

[0016] In the embodiments of the present application, by detecting the first image data of an object, the current vision detection type for characterizing whether the object wears a vision correction device is determined, and then the vision detection strategy of the object is determined through the current vision detection type; finally, the vision detection strategy is adopted to perform vision detection on the object. In this way, by determining the current vision detection type of the object, the vision of the object can be predicted, and then a vision detection strategy matching the predicted vision of the object is adopted to perform vision detection on the object, thereby improving the efficiency of vision testing. Moreover, by using a robot to perform vision testing, the convenience of vision testing can also be improved compared with manual operation.

[0017] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and do not limit the technical solution of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The accompanying drawings here are incorporated into the specification and form a part of this specification. These drawings show embodiments consistent with the present application and, together with the specification, are used to explain the technical solution of the present application.

[0019] Figure 1 Schematic diagram of the implementation process of a vision detection method provided by an embodiment of the present application Figure 1 ;

[0020] Figure 2 Schematic diagram of the implementation process of a vision detection method provided by an embodiment of the present application Figure 2 ;

[0021] Figure 3 Schematic diagram of the implementation process of a vision detection method provided by an embodiment of the present application Figure 3 ;

[0022] Figure 4 Schematic diagram of the implementation process of a vision detection method provided by an embodiment of the present application Figure 4 ;

[0023] Figure 5 Schematic diagram of the implementation process of a vision detection method provided by an embodiment of the present application Figure 5 ;

[0024] Figure 6 Schematic diagram of the implementation process of a vision detection method provided by an embodiment of the present application Figure 6 ;

[0025] Figure 7 Schematic diagram of the implementation process of a vision detection method provided by an embodiment of the present application Figure 7 ;

[0026] Figure 8 Schematic diagram of the structure of the robotic arm provided by an embodiment of the present application;

[0027] Figure 9 Schematic diagram of a hardware entity of a computer device provided by an embodiment of the present application. Detailed implementation manners

[0028] In order to make the objectives, technical solutions, and advantages of the present application clearer, the technical solutions of the present application will be further elaborated in detail below in conjunction with the accompanying drawings and embodiments. The described embodiments should not be construed as limitations on the present application. All other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the scope of protection of the present application.

[0029] In the following description, reference is made to "some embodiments", which describe a subset of all possible embodiments. However, it can be understood that "some embodiments" can be the same subset or different subsets of all possible embodiments, and can be combined with each other without conflict.

[0030] The terms "first / second / third" involved are only used to distinguish similar objects and do not represent a specific order for the objects. It can be understood that "first / second / third" can be interchanged with a specific order or sequence when permitted, so that the embodiments of the present application described herein can be implemented in an order other than that illustrated or described herein.

[0031] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the technical field to which this application belongs. The terms used herein are only for the purpose of describing this application and are not intended to limit this application.

[0032] To solve the technical problem in the related art that vision detection is inaccurate due to manual vision detection, an embodiment of the present application provides a vision detection method, which can be applied to the controller of a robot. Exemplarily, the robot can be an embodied intelligent robot. For exampleFigure 1 As shown in Figure 1 , the vision detection method includes steps S101 to S104:

[0033] Step S101, obtaining first image data of a detection object.

[0034] In the embodiments of the present application, the robot can collect the first image data of the detection object through its own image acquisition unit. In some embodiments, the first image data of the detection object can also be collected through an image acquisition device on another device different from the robot, and then the other device sends the first image data to the robot.

[0035] Step S102, determining the current vision detection type of the detection object based on the first image data of the detection object; the current vision detection type is used to characterize whether the detection object wears vision correction appliances.

[0036] In the embodiments of the present application, after the robot obtains the first image data of the detection object, it can perform image analysis on the first image data to determine whether the detection object wears vision correction appliances. Among them, the vision correction appliances can be frame glasses or contact lenses.

[0037] When the vision correction appliance is frame glasses, the current vision detection type of the detection object can be determined by performing image recognition on the image of the eye region.

[0038] In some embodiments, image recognition can be performed on the image of the eye region through a preset detection algorithm. Exemplarily, the edge information in the image can be extracted through the Canny edge detection algorithm to determine whether the edge information is the contour of glasses; or the corner point information of the image can be detected through the Harris corner point detection algorithm, and based on the corner point information, it can be determined whether there are glasses, and the corner point information can be the position and distribution information of the corner points.

[0039] In some embodiments, image recognition can also be performed on the image of the eye region through a trained detection model. Among them, a training data set can be constructed, and the training data set includes face images with and without glasses, and the position and category information of the glasses are marked in the face images. Then, the detection model is trained through the training data set to obtain a trained detection model.

[0040] In the case where the vision correction device is a contact lens, since the contact lens changes the optical properties of the corneal surface, the reflection of the cornea under light irradiation is different from that without wearing the contact lens. Therefore, the optical properties of the eyeball of the detection object in the first image data can be extracted and compared with the preset optical properties. If the two are inconsistent, it can be determined that the detection object wears contact lenses. Among them, the preset optical properties are the optical properties of the eyeball of the user in the image collected when the user does not wear contact lenses.

[0041] In some embodiments, the contact lens may have a certain color. Therefore, the color characteristics of the eyeball of the detection object in the first image data can be extracted. If the color characteristics match the color characteristics of the contact lens, it is determined that the detection object wears contact lenses.

[0042] Step S103: Determine the vision detection strategy of the detection object based on the current vision detection type of the detection object.

[0043] Here, the vision detection strategy can characterize the size of the vision identifier used at the beginning stage of vision detection. That is to say, the vision detection strategy can indicate which size of vision identifier is used to detect the vision of the detection object at the beginning stage of vision detection.

[0044] It can be understood that in the related art, when manually performing a vision test, a relatively large vision identifier is often manually selected to start the vision detection according to experience. Then, as the vision test progresses, the size of the vision identifier gradually becomes smaller until the vision detection result of the detection object is obtained. The problem with this solution is that if the vision of the detection object is good (for example, wearing a vision correction device), starting the vision detection from a relatively large vision identifier requires reducing the size of the vision identifier multiple times to obtain a vision identifier that matches the vision of the detection object, thereby reducing the efficiency of vision detection.

[0045] Therefore, in order to improve the efficiency of vision detection, the current vision detection type of the detection object can be determined first, and then the vision detection strategy of the detection object can be determined according to the current vision detection type of the detection object. Exemplarily, when the current vision detection type of the detection object indicates that the detection object wears a vision correction device, a relatively small vision identifier can be used; when the current vision detection type of the detection object indicates that the detection object does not wear a vision correction device, a relatively large vision identifier can be used.

[0046] Step S104: Use the vision detection strategy to perform vision detection on the detection object to obtain the vision detection result of the detection object.

[0047] In the embodiments of the present application, a vision identification corresponding to a vision detection strategy may be used to perform vision detection on a detection object to obtain a vision detection result of the detection object.

[0048] In the embodiments of the present application, based on the first image data of the detection object, the current vision detection type for characterizing whether the detection object wears a vision correction device is determined, and then the vision detection strategy for the detection object is determined through the current vision detection type; finally, the vision detection strategy is used to perform vision detection on the detection object. In this way, by determining the current vision detection type of the detection object, the vision of the detection object can be predicted, and then a vision detection strategy matching the predicted vision of the detection object is used to perform vision detection on the detection object, thereby improving the efficiency of vision testing. Moreover, by using a robot to perform vision testing, the convenience of vision testing can also be improved compared with manual operation.

[0049] In some embodiments, the vision detection strategy includes size information of an initial vision identification; as Figure 2 shown, the above step S103 can be implemented through step S201 and step S202:

[0050] Step S201, when the current vision detection type is a corrected vision detection type, determine that the size information of the initial vision identification is first size information.

[0051] Step S202, when the current vision detection type is an uncorrected vision detection type, determine that the size information of the initial vision identification is second size information;

[0052] wherein, the first size information is smaller than the second size information.

[0053] Here, when the initial vision identification is a two-dimensional image, the size information may be the area information of the initial vision identification; when the initial vision identification is a three-dimensional image, the size information may be the surface area information and / or volume information of the initial vision identification.

[0054] It can be understood that when the current vision detection type is a corrected vision detection type, it can be determined that the detection object wears a vision correction device. Generally, the vision of a user wearing a vision correction device is better than that of a user not wearing a vision correction device. Therefore, a smaller initial vision identification (i.e., the initial vision identification with the size information being the first size information) can be determined. Similarly, when the current vision detection type is an uncorrected vision detection type, it can be determined that the detection object does not wear a vision correction device, and at this time, a larger initial vision identification (i.e., the initial vision identification with the size information being the second size information) can be determined.

[0055] In the embodiments of the present application, when the current visual acuity detection type is the corrected visual acuity detection type, a smaller initial visual acuity identifier is determined; when the current visual acuity detection type is the uncorrected visual acuity detection type, a larger initial visual acuity identifier is determined. In this way, for different types of visual acuity detection, initial visual acuity identifiers of different sizes can be used to detect the visual acuity of the detection object, so that the size of the initial visual acuity identifier matches the current visual acuity detection type of the detection object, thereby reducing the number of times of changing the size of the visual acuity identifier during the visual acuity detection process and improving the efficiency of the visual acuity detection.

[0056] In some embodiments, as Figure 3 shown, the above step S103 can be implemented through step S301 and step S302:

[0057] Step S301, based on the historical visual acuity detection information of the detection object, determine the historical visual acuity detection type of the detection object.

[0058] In the embodiments of the present application, when the historical visual acuity detection information of the detection object is stored in the robot, the historical visual acuity detection information of the detection object can be obtained, so as to determine the historical visual acuity detection type of the detection object. Among them, the historical visual acuity detection type indicates whether the detection object wears vision correction appliances.

[0059] Step S302, based on the historical visual acuity detection type, the current visual acuity detection type, and the historical visual acuity detection information, determine the visual acuity detection strategy of the detection object.

[0060] In the embodiments of the present application, the matching degree between the historical visual acuity detection type and the current visual acuity detection type can be determined first, and then the visual acuity detection strategy of the detection object can be determined based on the matching degree between the two and the historical detection information.

[0061] In the embodiments of the present application, the historical visual acuity detection type of the detection object can be determined through the historical visual acuity detection information of the detection object; then, based on the historical visual acuity detection type, the current visual acuity detection type, and the historical visual acuity detection information, the visual acuity detection strategy of the detection object is determined. In this way, through the historical visual acuity detection information, the current visual acuity level of the detection object can be predicted more accurately, so that a visual acuity detection strategy that matches the current visual acuity of the detection object can be determined, thereby reducing the number of times of changing the size of the visual acuity identifier during the visual acuity detection process and improving the efficiency of the visual acuity detection.

[0062] In some embodiments, the visual acuity detection strategy includes the size information of the initial visual acuity identifier; as Figure 3 shown, the above step S302 can be implemented through step S3021 and step S3022:

[0063] Step S3021, when the historical vision detection type is the same as the current vision detection type, determine the size information of the initial vision identifier based on the size information of the vision identifier corresponding to the historical vision test result in the historical vision detection information.

[0064] Here, the historical vision detection type being the same as the current vision detection type may mean that both the historical vision detection type and the current vision detection type indicate that the detection object wears vision correction devices, or both indicate that the detection object does not wear vision correction devices.

[0065] In the embodiments of the present application, when the historical vision detection type is the same as the current vision detection type, obtain the size information of the vision identifier corresponding to the historical vision test result in the historical vision detection information, and the size information of the vision identifier corresponding to the historical vision test result can be determined as the size information of the initial vision identifier. In some embodiments, the size information greater than the preset value of the size information of the vision identifier corresponding to the historical vision test result can also be determined as the size information of the initial vision identifier.

[0066] It can be understood that when the time distance between the historical vision detection and the current vision detection is not too far, the vision of the detection object will not change significantly between the two times. Therefore, the size information of the initial vision identifier can be determined based on the size information of the vision identifier corresponding to the historical vision test result with the same vision detection type. Exemplarily, if the historical vision test result is 5.0, the vision identifier corresponding to 5.0 can be determined as the initial vision identifier, or the vision identifier corresponding to 4.9 can also be determined as the initial vision identifier.

[0067] Step S3022, when the historical vision detection type is different from the current vision detection type, determine the vision detection strategy of the detection object based on the historical vision detection information.

[0068] In the embodiments of the present application, the historical vision detection type being different from the current vision detection type may mean that the historical vision detection type is the corrected vision detection type and the current vision detection type is the uncorrected vision detection type. Because when the detection object has had its corrected vision detected historically, the degree information of the historical vision correction device is generally stored. For example, for 300-degree myopia glasses, the corrected vision is 5.0. Therefore, the degree information of the historical vision correction device and the historical vision test result can be obtained through the historical vision detection information, and thus the vision detection strategy of the detection object can be determined based on the degree information of the historical vision correction device and the historical vision test result.

[0069] In some embodiments, if the historical vision detection type is the uncorrected vision detection type, the current vision detection type is the corrected vision detection type, and the historical vision detection information stores the degree information of the historical vision correction device, the corrected vision of the detection object can also be predicted based on the degree information of the historical vision correction device and the historical vision test result, so as to determine the vision detection strategy of the detection object based on the predicted corrected vision.

[0070] In the embodiments of the present application, the corresponding relationship between the degree information of the vision correction device, the uncorrected vision and the corrected vision can be established in advance, and then the predicted corrected vision can be determined in the above corresponding relationship based on the degree information of the historical vision correction device and the historical vision test result.

[0071] In some embodiments, as Figure 4 shown, the above step S3022 can be implemented through steps S401 to S403:

[0072] Step S401, when the historical vision detection type is the corrected vision detection type and the current vision detection type is the uncorrected vision detection type, obtain the degree information of the historical vision correction device of the detection object from the historical vision detection information.

[0073] It can be understood that when detecting the corrected vision of the detection object, the detection object needs to wear a vision correction device, and at the same time record the degree information of the vision correction device, so as to store the corrected vision result and the degree information of the vision correction device together, that is, the above historical vision detection information. Therefore, when the historical vision detection type is the corrected vision detection type, the degree information of the historical vision correction device of the detection object can be obtained from the historical vision detection information.

[0074] Step S402, determine the predicted vision information of the detection object based on the degree information of the historical vision correction device and the historical vision test result.

[0075] Step S403, determine the size information of the vision identifier corresponding to the predicted vision information as the size information of the initial vision identifier.

[0076] In the embodiments of the present application, a mapping table corresponding to different degree ranges for degree information, corrected vision, and uncorrected vision can be constructed in advance according to the degree information of vision correction devices. That is, different degree ranges correspond to different mapping tables. Exemplarily, different degree ranges can include low-degree myopia / hyperopia ranges (degree less than 300 degrees), moderate myopia / hyperopia (degree between 300 degrees and 600 degrees), and high-degree myopia / hyperopia (degree greater than 600 degrees). Then, according to the degree information of the historical vision correction device, a target degree range is determined among multiple degree ranges, and the predicted vision information of the detection object is determined in the mapping table corresponding to the target degree range based on the historical vision test results.

[0077] In the embodiments of the present application, in the case where the historical vision detection type is inconsistent with the current vision detection type, the current vision information of the detection object can be predicted through the degree information of the detection object's historical vision correction device and the historical vision test results, so as to determine the size information of the initial vision identifier through the size information of the vision identifier corresponding to the predicted current vision information. In this way, a vision detection strategy with a size matching the current vision of the detection object can be determined, thereby reducing the number of times of changing the size of the vision identifier during the vision detection process and improving the efficiency of vision detection.

[0078] In some embodiments, the robot includes a display, or there is a display device externally connected to the robot, and the robot further includes an arm component; as Figure 5 shown, "performing vision detection on the detection object using the vision detection strategy" in step S104 above can be implemented through step S501 and step S502:

[0079] Step S501, controlling the display screen or the display device to display an initial vision identifier.

[0080] In the embodiments of the present application, after determining the size information of the initial vision identifier, the initial vision identifier can be displayed on the display of the robot or on the display device externally connected to the robot according to the size information, so as to start vision detection on the detection object.

[0081] Step S502, controlling the arm component to point to the initial vision identifier to prompt the detection object to perform vision detection.

[0082] In the embodiments of the present application, the robot is an embodied intelligent robot. Therefore, the robot includes an arm component. In order to guide the detection object to complete vision detection, the controller of the robot can control the arm component to point to the initial vision identifier displayed on the display screen or the display device to remind the detection object to perform vision detection.

[0083] In some embodiments, whenever the display screen or display device changes the size of the vision identifier, the robotic arm component will point to the vision identifier, thereby actively guiding the detection object to complete the vision detection process.

[0084] In some embodiments, the above vision detection method can also be implemented through Step 11 and Step 12:

[0085] Step 11, obtain the feedback information fed back by the detection object for the initial vision identifier.

[0086] Here, the feedback methods of the detection object for the initial vision identifier may include at least one of the following: gesture feedback and voice feedback. Among them, when the feedback method of the detection object is gesture feedback, the above feedback information may be the image data of the detection object collected by the robot; when the feedback method of the detection object is voice feedback, the above feedback information may be the voice data of the detection object collected by the robot.

[0087] Step 12, based on the feedback information, control the moving component to change the distance between the robot and the detection object, and each time the distance is changed, prompt the detection object to perform vision detection through the arm component.

[0088] In the embodiments of the present application, after the robot obtains the feedback information, it is necessary to determine whether the feedback information is consistent with the direction information represented by the initial vision identifier. If not, the robot does not need to move, keeps the size of the initial vision identifier, changes the direction information of the initial vision identifier, and guides the detection object to perform vision detection again, or shortens the distance between the robot and the detection object. In this way, within the perspective of the detection object, the size of the initial vision identifier increases, and then the detection object is prompted to perform vision detection through the arm component. When the feedback information is consistent with the direction information represented by the initial vision identifier, the controller of the robot can control the moving component to move and extend the distance between the robot and the detection object. In this way, within the perspective of the detection object, the size of the initial vision identifier decreases, and then the detection object is prompted to perform vision detection through the arm component. In some embodiments, when the feedback information is consistent with the direction information represented by the initial vision identifier, the robot may also not move, keep the size of the initial vision identifier, and change the direction information of the initial vision identifier to guide the detection object to perform vision detection again.

[0089] In the embodiments of the present application, by utilizing the flexibility of the robot to move, the moving component is used to move the robot to change the distance between the robot and the detection object, so as to achieve enlarging and reducing the size of the initial vision identifier, thereby completing the vision detection process. In this way, the flexibility of vision detection can be improved.

[0090] In some embodiments, such as Figure 6As shown in the figure, the above-mentioned vision detection method can also be implemented through steps S601 to S603:

[0091] Step S601, output a prompt message for prompting the detection object to cover the eyes.

[0092] In the embodiment of the present application, after the robot detects that the detection object can start vision detection, a prompt message for prompting the detection object to cover the eyes can be output to the detection image. Among them, the prompt message can be a voice prompt message, such as emitting a voice prompt message of "Please cover your eyes". In some embodiments, the prompt message can also be a gesture message. For example, when it is necessary for the detection object to cover the right eye, the robot controls the right arm in the arm component to lift, and when it is necessary for the detection object to cover the left eye, the robot controls the left arm in the arm component to lift.

[0093] Step S602, based on the second image data of the detection object, determine the position information of the target eye of the detection object.

[0094] In the embodiment of the present application, the robot can collect the image information of the detection object to obtain the second image data, and then determine the position information of the target eye to be tested for vision of the detection object by recognizing the second image data. Among them, the position information can indicate that the target eye is the left eye or the right eye of the detection object.

[0095] It can be understood that when the prompt message does not indicate which eye to cover, it is necessary to collect the image data of the detection object to determine the actual position information of the eye covered by the detection object. Even if the prompt message indicates which eye to cover, it is also necessary to collect the image data of the detection object to determine the actual position information of the eye covered by the detection object.

[0096] Step S603, associate the vision detection result with the position information of the target eye to obtain the first association information, and store the first association information.

[0097] In the embodiment of the present application, after obtaining the vision detection result of the target eye, the vision detection result can be associated with the position information of the target eye. Exemplarily, the vision of the right eye of the detection object is 5.0, and the first association information can be right eye - 5.0.

[0098] In the embodiment of the present application, by collecting the image data of the detection object, the covered eye of the detection object can be automatically recognized, so that the vision detection result of the target eye can be associated with the position information of the target eye. In this way, by associating the vision detection result of the target eye with the position information of the target eye, all the vision detection results of the eye can be obtained through the position information of the eye, thereby improving the efficiency of obtaining data.

[0099] In some embodiments, such as Figure 7 shown, the above vision detection method can also be implemented through step S701 and step S702:

[0100] Step S701, when the current vision detection type is a corrected vision detection type, obtain the degree information of the current vision correction device of the detection object.

[0101] In the embodiments of the present application, when the current vision detection type is a corrected vision detection type, it can be determined that the user wears a vision correction device. The robot can first obtain historical vision detection information from the database based on the identity information of the detection object, and obtain the degree information of the historical vision correction device from the historical vision detection information, and can use the degree information of the historical vision correction device as the degree information of the current vision correction device of the detection object.

[0102] In some embodiments, if the historical vision detection information does not have the degree information of the historical vision correction device, a prompt information for prompting the detection object to place the current vision correction device at a specified position can be output. The robot, in response to detecting that there is a current vision correction device at the specified position, controls the degree detection device (such as a refractometer) to detect the degree information of the current vision correction device.

[0103] Step S702, when it is determined based on the vision detection result that the degree information of the current vision correction device does not match the vision detection result, determine the degree adjustment information of the current vision correction device.

[0104] It can be understood that, generally, by wearing a vision correction device, the user's vision needs to be corrected to a predetermined vision, such as corrected to 4.9. Therefore, the robot can compare the current corrected vision (i.e., the vision detection result) of the detection object with the predetermined vision. If the comparison result indicates that the gap between the degree information of the current vision correction device and the vision detection result is large, the degree adjustment information of the current vision correction device can be determined based on the vision detection result. Among them, the degree adjustment information can include the type information and / or degree information of the glasses. Exemplarily, the type information of the glasses can include myopia, hyperopia, and astigmatism. Among them, if the comparison result is greater than the comparison threshold, the comparison result indicates that the gap between the degree information of the current vision correction device and the vision detection result is large.

[0105] In the embodiments of the present application, when the degree information of the current vision correction device does not match the vision detection result, the robot can output a prompt message for instructing the detection object to remove the vision correction device, and then perform a vision detection on the detection object to obtain the naked-eye vision of the detection object, determine the updated degree information of the vision correction device based on the naked-eye vision of the detection object; based on the updated degree information and the degree information of the current vision correction device, determine the degree adjustment information of the current vision correction device.

[0106] In some embodiments, if the comparison result indicates that the gap between the degree information of the current vision correction device and the vision detection result is small, it is determined that the current vision correction device can continue to be used. Among them, if the comparison result is less than or equal to the comparison threshold, the comparison result indicates that the gap between the degree information of the current vision correction device and the vision detection result is small.

[0107] In the embodiments of the present application, it is possible to determine whether the degree information of the current vision correction device matches the vision detection result by correcting the vision, and in the case of non-matching, determine the degree adjustment information of the current vision correction device. In this way, while detecting the user's vision, a glasses degree adjustment strategy can be automatically provided for the user, thereby improving the user experience when detecting vision.

[0108] In some embodiments, the above vision detection method can also be implemented through steps S801 to S803:

[0109] Step S801, when the camera of the robot captures that the subject enters the hearing test environment, guide the subject to enter the designated position.

[0110] In the embodiments of the present application, the robot can display a smiling expression through the head display screen and control the limb parts to greet the detection object.

[0111] Step S802, the robot controls the arm component to point to the display screen showing a single letter "E" and outputs voice data representing the vision test method.

[0112] Step S803, determine the vision detection result of the subject.

[0113] In the embodiments of the present application, step S803 may include: dynamically adjusting the size of the "E" according to the position of the subject until the vision detection result of the subject is determined.

[0114] In some embodiments, step S803 may further include: the size of the "E" in the display screen of the robot remains unchanged, and the robot is continuously moved to change the distance between the robot and the subject until the vision detection result of the subject is determined.

[0115] In some embodiments, the robot can output a prompt message for indicating that the subject covers their eyes, and then determine the position information of the covered eye by collecting the image data of the subject. After determining the vision test result of the covered eye, the vision test result can be mapped to the position information of the covered eye. Then, the robot outputs a prompt message again for indicating that the subject changes the covered eye.

[0116] In some embodiments, if the subject undergoes a vision test for the first time, the display content of the vision chart during the test of the other eye can be adjusted based on the first set of vision parameters; if the subject is not undergoing a vision test for the first time, the display content of the vision chart is adjusted based on the subject's previous test result.

[0117] Exemplarily, for a subject using it for the first time: after testing the vision of the left eye, when testing the vision of the right eye, the display content of the vision chart corresponding to the left eye vision can be shown first. For a subject not using it for the first time: the previous vision test result can be obtained first, and then the display content of the vision chart is adjusted based on the previous vision test result.

[0118] In some embodiments, for a user wearing glasses, the robot can automatically identify whether the detected vision is the naked-eye vision or the corrected vision through machine vision, and prompt the user whether to remove the glasses for testing according to the detection requirements.

[0119] In some embodiments, when the device supports it, after the vision test is completed, the robot can place the glasses at the designated position of the optometer, and the device will automatically measure and upload the glasses prescription to the background.

[0120] In some embodiments, the robot can also detect the user's color blindness and color weakness by picking up a card or displaying it on the chest display screen.

[0121] In some embodiments, the robot generates a vision test report based on the above-mentioned vision, color blindness, and color weakness detection results, generates / updates the user profile, and provides vision correction suggestions based on the actual situation of the user.

[0122] In some embodiments, when the vision test ends, the robot gives a voice prompt that the test is over, the head LED screen displays a smiling expression, waves goodbye to the subject, and guides the subject to leave.

[0123] Figure 8 It is a schematic diagram of the composition structure of a robot provided by an embodiment of the present application, as Figure 8 shown, the robot 800 includes: a controller 801 and an image acquisition unit 802, where:

[0124] The image acquisition unit 802 is configured to acquire first image data of a detection object;

[0125] The controller 801 is configured to determine a current visual acuity detection type of the detection object based on first image data of the detection object; the current visual acuity detection type is used to indicate whether the detection object wears a vision correction device; determine a visual acuity detection strategy for the detection object based on the current visual acuity detection type of the detection object; and perform a visual acuity detection on the detection object by using the visual acuity detection strategy to obtain a visual acuity detection result of the detection object.

[0126] In some embodiments, the visual acuity detection strategy includes size information of an initial visual acuity identifier; the controller 801 is configured to determine that the size information of the initial visual acuity identifier is first size information when the current visual acuity detection type is a corrected visual acuity detection type; and determine that the size information of the initial visual acuity identifier is second size information when the current visual acuity detection type is an uncorrected visual acuity detection type; wherein the first size information is smaller than the second size information.

[0127] In some embodiments, the controller 801 is configured to determine a historical visual acuity detection type of the detection object based on historical visual acuity detection information of the detection object; and determine a visual acuity detection strategy for the detection object based on the historical visual acuity detection type, the current visual acuity detection type, and the historical visual acuity detection information.

[0128] In some embodiments, the visual acuity detection strategy includes size information of an initial visual acuity identifier; the controller 801 is configured to determine the size information of the initial visual acuity identifier based on the size information of a visual acuity identifier corresponding to a historical visual acuity test result in the historical visual acuity detection information when the historical visual acuity detection type is consistent with the current visual acuity detection type; and determine a visual acuity detection strategy for the detection object based on the historical visual acuity detection information when the historical visual acuity detection type is inconsistent with the current visual acuity detection type.

[0129] In some embodiments, when the historical visual acuity detection type is a corrected visual acuity detection type and the current visual acuity detection type is an uncorrected visual acuity detection type, the controller 801 is configured to obtain diopter information of a historical vision correction device of the detection object from the historical visual acuity detection information; determine predicted visual acuity information of the detection object based on the diopter information of the historical vision correction device and the historical visual acuity test result; and determine the size information of the visual acuity identifier corresponding to the predicted visual acuity information as the size information of the initial visual acuity identifier.

[0130] In some embodiments, the robot includes a display, or there is a display device externally connected to the robot, and the robot further includes an arm component; the controller 801 is configured to control the display screen or the display device to display an initial vision identifier; and control the arm component to point to the initial vision identifier to prompt the detection object to perform a vision test.

[0131] In some embodiments, the robot further includes a moving component; the controller 801 is configured to obtain feedback information fed back by the detection object for the initial vision identifier; based on the feedback information, control the moving component to change the distance between the robot and the detection object, and each time the distance is changed, prompt the detection object to perform a vision test through the arm component.

[0132] In some embodiments, the controller 801 is configured to output a prompt message for prompting the detection object to cover the eyes; determine the position information of the target eye of the detection object based on the second image data of the detection object; associate the vision test result with the position information of the target eye to obtain first association information, and store the first association information.

[0133] In some embodiments, when the current vision test type is a corrected vision test type, the controller 801 is configured to obtain the degree information of the current vision correction appliance of the detection object; and when it is determined based on the vision test result that the degree information of the current vision correction appliance does not match the vision test result, determine the degree adjustment information of the current vision correction appliance.

[0134] The description of the above device embodiments is similar to the description of the above method embodiments and has similar beneficial effects to the method embodiments. In some embodiments, the functions or modules included in the device provided in the embodiments of the present application can be used to execute the methods described in the above method embodiments. For the technical details not disclosed in the device embodiments of the present application, please refer to the description of the method embodiments of the present application for understanding.

[0135] It should be noted that in the embodiments of the present application, if the above data processing method is implemented in the form of software function modules and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiments of the present application, in essence, or the part that contributes to the related technology, can be embodied in the form of a software product. The software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the methods of the various embodiments of the present application. The foregoing storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memory (ROM), magnetic disks, or optical discs that can store program codes. In this way, the embodiments of the present application are not limited to any specific hardware, software, or firmware, or any combination among hardware, software, and firmware.

[0136] The embodiments of the present application provide a computer device, including a memory and a processor. The memory stores a computer program that can run on the processor, and when the processor executes the program, it implements some or all of the steps in the above method.

[0137] The embodiments of the present application provide a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by the processor, it implements some or all of the steps in the above method. The computer-readable storage medium can be transient or non-transient.

[0138] The embodiments of the present application provide a computer program, including computer-readable code. When the computer-readable code runs in a computer device, the processor in the computer device executes to implement some or all of the steps in the above method.

[0139] The embodiments of the present application provide a computer program product. The computer program product includes a non-transient computer-readable storage medium storing a computer program. When the computer program is read and executed by a computer, it implements some or all of the steps in the above method. The computer program product can be specifically implemented in the form of hardware, software, or a combination thereof. In some embodiments, the computer program product is specifically embodied as a computer storage medium, and in other embodiments, the computer program product is specifically embodied as a software product, such as a software development kit (SDK), etc.

[0140] It should be noted here that: the above descriptions of the various embodiments tend to emphasize the differences between the various embodiments, and their similarities can be referred to each other. The descriptions of the above embodiments of the device, storage medium, computer program, and computer program product are similar to the descriptions of the above method embodiments and have beneficial effects similar to those of the method embodiments. For the technical details not disclosed in the embodiments of the device, storage medium, computer program, and computer program product of the present application, please refer to the descriptions of the method embodiments of the present application for understanding.

[0141] Figure 9 is a schematic structural diagram of a computer device provided by an embodiment of the present application. As Figure 9 shown, the computer device 900 includes: a memory 910 and a processor 920; wherein, the memory 910 stores a computer program that can run on the processor 920; when the processor 920 executes the computer program, it implements the vision detection method provided in the above embodiment.

[0142] The memory 910 stores a computer program that can run on the processor. The memory 910 is configured to store instructions and applications executable by the processor 920, and can also cache data to be processed or already processed by the processor 920 and each module in the control device 900 (for example, image data, audio data, voice communication data, and video communication data), and can be implemented by flash memory (FLASH) or random access memory (Random Access Memory, RAM).

[0143] When the processor 920 executes the program, it implements the steps of any of the above control methods. The processor 920 generally controls the overall operation of the computer device 900.

[0144] The embodiment of the present application provides a computer storage medium. The computer storage medium stores one or more programs, and the one or more programs can be executed by one or more processors to implement the steps of the vision detection method in any of the above embodiments.

[0145] It should be noted here that: the above descriptions of the storage medium and device embodiments are similar to the descriptions of the above method embodiments and have beneficial effects similar to those of the method embodiments. For the technical details not disclosed in the storage medium and device embodiments of the present application, please refer to the descriptions of the method embodiments of the present application for understanding.

[0146] The above-mentioned processor may be at least one of an Application Specific Integrated Circuit (ASIC), a Digital Signal Processor (DSP), a Digital Signal Processing Device (DSPD), a Programmable Logic Device (PLD), a Field Programmable Gate Array (FPGA), a Central Processing Unit (CPU), a controller, a microcontroller, and a microprocessor. It can be understood that the electronic device implementing the functions of the above-mentioned processor may also be others, which are not specifically limited in the embodiments of the present application.

[0147] The above-mentioned computer storage medium / memory may be a Read Only Memory (ROM), a Programmable Read-Only Memory (PROM), an Erasable Programmable Read-Only Memory (EPROM), an Electrically Erasable Programmable Read-Only Memory (EEPROM), a Ferromagnetic Random Access Memory (FRAM), a Flash Memory, a magnetic surface memory, an optical disc, or a Compact Disc Read-Only Memory (CD-ROM), etc.; it may also be various terminals including one or any combination of the above-mentioned memories, such as a mobile phone, a computer, a tablet device, a personal digital assistant, etc.

[0148] It should be understood that the "one embodiment" or "an embodiment" mentioned throughout the specification means that the specific features, structures or characteristics related to the embodiment are included in at least one embodiment of the present application. Therefore, the "in one embodiment" or "in an embodiment" that appears throughout the specification does not necessarily refer to the same embodiment. In addition, these specific features, structures or characteristics can be combined in one or more embodiments in any suitable manner. It should be understood that in various embodiments of the present application, the magnitude of the serial numbers of the above steps / processes does not mean the order of execution. The order of execution of each step / process should be determined by its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present application. The serial numbers of the embodiments of the present application above are only for description and do not represent the advantages or disadvantages of the embodiments.

[0149] It should be noted that in this text, the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not expressly listed, or further includes elements inherent to such process, method, article or device. Without further limitation, an element defined by the phrase "including one..." does not exclude the presence of additional identical elements in the process, method, article or device including such element.

[0150] As described above, it is only the implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present application can easily think of changes or substitutions, which should be covered within the protection scope of the present application.

Claims

1. A method for visual acuity detection, characterized in that: The method is applied to a robot; the method comprises: Acquire first image data of the detection object; Determine the current vision detection type of the detection object based on the first image data of the detection object; the current vision detection type is used to indicate whether the detection object wears a vision correction device; Determining a vision detection strategy for the detection subject based on a current vision detection type of the detection subject; The vision detection strategy is adopted to perform a vision detection on the detection object to obtain the vision detection result of the detection object.

2. The method according to claim 1, characterized in that The vision detection strategy includes size information of the initial vision mark; the vision detection strategy of the detection object is determined based on the current vision detection type of the detection object, including at least one of the following: When the current vision detection type is a corrected vision detection type, the size information of the initial vision mark is determined to be the first size information; when the current vision detection type is a naked eye vision detection type, the size information of the initial vision mark is determined to be the second size information; wherein the first size information is smaller than the second size information; Based on the historical vision test information of the test object, determine the historical vision test type of the test object; based on the historical vision test type, the current vision test type and the historical vision test information, determine the vision test strategy of the test object.

3. The method according to claim 2, characterized in that The vision detection strategy includes size information of the initial vision mark; the vision detection strategy of the detection object determined based on the historical vision detection type, the current vision detection type and the historical vision detection information includes: In a case where the historical vision test type is consistent with the current vision test type, determining the size information of the initial vision identifier based on the size information of the vision identifier corresponding to the historical vision test result in the historical vision test information; In the case that the historical vision test type is inconsistent with the current vision test type, a vision test strategy for the test subject is determined based on the historical vision test information.

4. The method according to claim 3, characterized in that When the historical vision test type is inconsistent with the current vision test type, determining the vision test strategy of the test object based on the historical vision test information includes: When the historical vision test type is a corrected vision test type, and the current vision test type is a naked eye vision test type, obtaining the degree information of the historical vision correction device of the test subject from the historical vision test information; Determining predicted vision information of the test subject based on the historical vision correction device degree information and the historical vision test results; The size information of the vision mark corresponding to the predicted vision information is determined as the size information of the initial vision mark.

5. The method according to any one of claims 1 to 4, characterized in that: The robot includes a display, or the robot has an external display device, and the robot also includes an arm component; the vision detection strategy is used to perform vision detection on the detection object, including: Controlling the display screen or the display device to display an initial vision mark; The arm component is controlled to point to the initial vision mark to prompt the test subject to perform a vision test.

6. The method according to claim 5, characterized in that The robot further comprises a moving part; and the method further comprises: Obtaining feedback information from the test subject regarding the initial vision identification; Based on the feedback information, the moving component is controlled to change the distance between the robot and the detection object, and each time the distance is changed, the detection object is prompted to perform a vision test through the arm component.

7. The method according to claims 1 to 6, characterized in that The method further comprises: Outputting prompt information for prompting the detected object to cover its eyes; Determining position information of a target eye of the detection object based on the second image data of the detection object; The vision detection result is associated with the position information of the target eye to obtain first associated information, and the first associated information is stored.

8. The method according to claims 1 to 7, characterized in that The method further comprises: In the case where the current vision detection type is a corrective vision detection type, obtaining the degree information of the current vision correction device of the detection object; When it is determined based on the vision test result that the degree information of the current vision correction device does not match the vision test result, the degree adjustment information of the current vision correction device is determined.

9. A robot, characterized in that: The robot includes a controller and an image acquisition unit; wherein, The image acquisition unit is used to acquire first image data of the detection object; The controller is used to determine the current vision detection type of the detection object based on the first image data of the detection object; the current vision detection type is used to characterize whether the detection object wears a vision correction device; based on the current vision detection type of the detection object, determine the vision detection strategy of the detection object; adopt the vision detection strategy to perform a vision test on the detection object to obtain the vision detection result of the detection object.

10. A computer device, wherein: include: A memory for storing executable instructions; A processor, configured to implement the method according to any one of claims 1 to 8 when executing the executable instructions stored in the memory.

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