Convergence distance adjustment method and apparatus for smart wearable device, device, and medium

Abstract

The present application provides a convergence distance adjustment method and apparatus for a smart wearable device, a device, and a medium. The method comprises: calculating a first convergence distance on the basis of a first interpupillary distance of a target user to achieve customized convergence distance calculation; calculating a convergence distance adjustment amount on the basis of a current scene depth, a current parallax of the target user, and a second interpupillary distance; and performing a convergence distance adjustment on the smart wearable device, such that a display position of a target display object matches a viewing distance of the target user.

Description

Methods, devices, equipment and media for adjusting the merging distance of smart wearable devices

[0001] This application claims priority to Chinese Patent Application No. 2024114047948, filed on October 9, 2024, entitled “Method, Apparatus, Device and Medium for Adjusting the Image Convergence Distance of Smart Wearable Devices”, the entire contents of which are incorporated herein by reference. Technical Field

[0002] This application relates to the field of intelligent display technology, and in particular to a method, apparatus, device and medium for adjusting the image-to-image distance of an intelligent wearable device. Background Technology

[0003] Augmented reality (AR) technology is a technique that overlays virtual images onto the real world. It is widely used in smart wearable devices, such as AR devices and VR devices. Currently, augmented reality technology has been widely applied in fields such as gaming, education, healthcare, and architecture.

[0004] In current smart wearable devices, the merging distance is usually fixed. However, a fixed merging distance makes it difficult to adapt to differences in interpupillary distance among users, and it cannot be dynamically adjusted according to the scenario during actual use. This fixed merging distance can easily lead to user eye strain, inaccurate positioning of virtual objects, and other problems, negatively impacting the user experience.

[0005] Therefore, improving the flexibility of adjusting the merging distance of smart wearable devices has become an urgent technical problem to be solved. Summary of the Invention

[0006] This application provides a method, apparatus, device, and medium for adjusting the alignment distance of a smart wearable device, aiming to improve the flexibility of adjusting the alignment distance of the smart wearable device.

[0007] In a first aspect, this application provides a method for adjusting the image-merging distance of a smart wearable device, the method comprising:

[0008] Calculate the first convergence distance of the smart wearable device based on the first interpupillary distance of the target user;

[0009] Based on the current scene depth, the current parallax of the target user, and the second interpupillary distance of the target user, calculate the first adjustment amount of the merging distance;

[0010] The target alignment distance is calculated based on the first alignment distance and the first adjustment amount of the alignment distance;

[0011] Based on the target alignment distance, the alignment distance of the smart wearable device is adjusted so that the display position of the target object matches the viewing distance of the target user.

[0012] Secondly, this application also provides a alignment distance adjustment device for a smart wearable device, the alignment distance adjustment device for the smart wearable device comprising:

[0013] The first merging distance calculation module is used to calculate the first merging distance of the smart wearable device based on the first interpupillary distance of the target user.

[0014] The first adjustment calculation module is used to calculate the first adjustment amount of the image-merging distance based on the current scene depth, the current disparity of the target user, and the second interpupillary distance of the target user.

[0015] The target alignment distance module is used to calculate the target alignment distance based on the first alignment distance and the first adjustment amount of the alignment distance;

[0016] The image merging distance adjustment module is used to adjust the image merging distance of the smart wearable device based on the target image merging distance, so that the display position of the target object matches the viewing distance of the target user.

[0017] Thirdly, this application also provides a smart wearable device, which includes a processor, a memory, and a computer program stored in the memory and executable by the processor, wherein when the computer program is executed by the processor, it implements the steps of the above-described method for adjusting the merging distance of the smart wearable device.

[0018] Fourthly, this application also provides a computer-readable storage medium storing a computer program, wherein when the computer program is executed by a processor, it implements the steps of the above-described method for adjusting the merging distance of a smart wearable device.

[0019] This application provides a method, apparatus, device, and medium for adjusting the merging distance of a smart wearable device. The method calculates a first merging distance based on the target user's first interpupillary distance, enabling customized merging distance calculation for the target user and improving the applicability of the smart wearable device. Based on the current scene depth, the target user's current parallax, and second interpupillary distance, an adjustment amount for the merging distance is calculated. The merging distance of the smart wearable device is then adjusted according to this adjustment amount, ensuring that the display position of the target object matches the target user's viewing distance. This allows the merging distance to dynamically change according to the actual usage environment, improving the flexibility of adjusting the merging distance and the accuracy of positioning the target object. This enhances the adaptability and flexibility of the device's display, thereby reducing user visual fatigue and improving user visual comfort. Attached Figure Description

[0020] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 is a flowchart illustrating a first embodiment of a method for adjusting the merging distance of a smart wearable device according to an embodiment of this application.

[0022] Figure 2 is a flowchart illustrating a second embodiment of a method for adjusting the merging distance of a smart wearable device according to an embodiment of this application.

[0023] Figure 3 is a schematic diagram of the structure of a first embodiment of a merging distance adjustment device for a smart wearable device provided in this application;

[0024] Figure 4 is a schematic block diagram of the structure of a smart wearable device provided in an embodiment of this application.

[0025] The realization of the purpose, functional features and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0026] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0027] The flowchart shown in the attached diagram is for illustrative purposes only and does not necessarily include all content and operations / steps, nor does it necessarily have to be performed in the described order. For example, some operations / steps can be broken down, combined, or partially merged, so the actual execution order may change depending on the actual situation.

[0028] The following detailed description of some embodiments of this application is provided in conjunction with the accompanying drawings. Unless otherwise specified, the following embodiments and features can be combined with each other.

[0029] Please refer to Figure 1, which is a flowchart illustrating the first embodiment of a method for adjusting the image distance of a smart wearable device according to an embodiment of this application.

[0030] As shown in Figure 1, the method for adjusting the merging distance of the smart wearable device includes steps S101 to S104.

[0031] S101. Calculate the first convergence distance of the smart wearable device based on the first interpupillary distance of the target user;

[0032] In one embodiment, the first interpupillary distance of the target user can be collected by a sensor device built into the smart wearable device, or the target user can actively input the first interpupillary distance data into the smart wearable device (such as AR glasses).

[0033] In one embodiment, the sensor device may be an image sensor, such as a CCD (Charge Coupled Device) or a CMOS (Complementary Metal Oxide Semiconductor).

[0034] In one embodiment, the first pupillary distance (PD) may be the PD data measured when the target user first wears the smart wearable device; the first PD may also be the PD data collected last time when the target user last wore the smart wearable device; or the first PD may be the PD data collected for the first time when the target user is currently wearing the smart wearable device.

[0035] In one embodiment, the target user can be a user wearing the smart wearable device for the first time; the target user can also be a user who has worn the smart wearable device before; or the target user can also be a user currently wearing the smart wearable device.

[0036] Generally, interpupillary distance (IPD) refers to the distance between the center points of the two eyes. Accurate IPD data is crucial for adjusting the image display pose of smart wearable devices, avoiding image distortion and visual fatigue, and improving the user experience when wearing smart wearable devices.

[0037] In one embodiment, the smart wearable device is pre-set with a standard interpupillary distance (IPD) before leaving the factory, and then a preset convergence distance is set based on this preset standard IPD. For example, the IPD of an average adult male is between 60 mm and 73 mm, while that of a female is between 53 mm and 68 mm. The standard IPD data for the smart wearable device can be determined based on empirical values ​​or by collecting large amounts of IPD detection data.

[0038] In one embodiment, when wearing a smart wearable device, the target user can actively input a first interpupillary distance (IPD), or the IPD can be acquired by the image sensor built into the smart wearable device. Based on the data difference between the first IPD and the preset IPD of the smart wearable device, a matching merging distance adapted to the target user is calculated. The preset merging distance is then adjusted so that the display content of the smart wearable device is displayed at the adjusted merging distance, thereby improving the display quality of the smart wearable device and enhancing the user experience.

[0039] For example, the second adjustment amount of the merging distance is determined based on the interpupillary distance difference between the first interpupillary distance and the preset interpupillary distance.

[0040] In one embodiment, when determining the second adjustment amount of the merging distance based on the first interpupillary distance and the preset interpupillary distance, the following steps can be used for calculation:

[0041] Determine the difference: First, calculate the difference between the first pupillary distance and the preset pupillary distance: Difference = Preset pupillary distance - First pupillary distance

[0042] Calculate the adjustment amount: Calculate the second adjustment amount of the image-merging distance based on the interpupillary distance difference and specific parameters of the optical system (such as magnification, focal length, etc.).

[0043] For example, the calculation method for the second adjustment amount of the image merging distance can be:

[0044] Among them, magnification refers to the proportional relationship between the size of the image formed by the imaging system and the actual size of the object, that is, the magnification factor of the display content of the smart wearable device.

[0045] Then, based on the preset merging distance and the second adjustment amount of the merging distance, the first merging distance is calculated.

[0046] The formula for calculating the first coincidence distance can be: D1=D0+ΔD1

[0047] Where D1 represents the first merging distance, ΔD1 represents the second adjustment amount of the merging distance, and D0 represents the preset merging distance.

[0048] In one embodiment, ΔD1 can be determined by an empirical formula or calibration process, typically based on the difference between a first pupillary distance and a preset pupillary distance.

[0049] Further, the preset interpupillary distance and preset merging distance of the smart wearable device are obtained; based on the interpupillary distance difference between the first interpupillary distance and the preset interpupillary distance, a second adjustment amount of the merging distance is determined; based on the preset merging distance and the second adjustment amount of the merging distance, the first merging distance is determined.

[0050] For example, the correspondence between pupil distance and merging distance can be collected through big data, or the correspondence between the pupil distance difference between the first pupil distance and the preset pupil distance and the merging distance adjustment amount can be learned based on the preset pupil distance and its corresponding preset merging distance. An empirical formula can be constructed based on this correspondence as the basis for calculating the second adjustment amount ΔD1 of the merging distance.

[0051] For example, the empirical formula for the second adjustment amount ΔD1 of the image combination distance can be expressed as: ΔD1=λ0·(d1-d0)

[0052] Where d1 represents the first interpupillary distance of the target user, d0 represents the preset interpupillary distance of the smart wearable device, and λ0 represents the conversion coefficient between the interpupillary distance difference and the adjustment amount of the merging distance.

[0053] It is understood that the empirical formulas provided in the embodiments of this application are merely illustrative and do not represent actual use. The correspondence between the interpupillary distance difference and the merging distance adjustment amount (i.e., the calculation method of the merging distance adjustment amount) can be determined according to the actual application of the smart wearable device.

[0054] In one embodiment, when a user wears a smart wearable device, the merging distance needs to be dynamically adjusted as the user's interpupillary distance, viewing angle, and scene depth change, in order to reduce visual fatigue caused by prolonged use, improve the positioning accuracy of virtual object display positions, and enhance the user's user experience.

[0055] Further, an eye image of the target user is acquired; based on a feature point detection model, pupil localization detection is performed on the eye image to obtain the left and right pupil coordinates of the target user; based on the left and right pupil coordinates, the second interpupillary distance of the target user is calculated.

[0056] In one embodiment, when a target user wears a smart wearable device, an image of the target user's eye can be captured by a sensor device (such as an image sensor) built into the smart wearable device. Understandably, the eye image needs to clearly show the target user's pupil.

[0057] In one embodiment, a binocular vision system can be used to acquire images of the target user's eyes in order to obtain the precise coordinates of the target user's pupils.

[0058] In one embodiment, the acquired eye images can be preprocessed, including grayscale conversion, denoising, and enhancement, to improve image quality and prepare for feature point detection. A feature point detection model, such as a deep learning-based method, is used to detect pupil location in the eye images, determining the precise position of the pupils in the image, thereby obtaining the coordinates of the left and right pupils. Based on the detected left and right pupil coordinates, the distance between them, i.e., the second interpupillary distance, is calculated.

[0059] For example, if the coordinates of the left pupil are (100, 150) and the coordinates of the right pupil are (120, 150), then the second pupillary distance can be calculated using the following formula:

[0060] In one embodiment, the unit of interpupillary distance can be converted according to the image resolution and the actual measurement unit.

[0061] Furthermore, based on the feature point detection model, the pupil contour features in the eye image are detected; based on the pupil localization algorithm, the coordinates of the pupil center point are calculated to obtain the coordinates of the left and right pupils of the target user.

[0062] Feature point detection models can employ feature point detection algorithms such as Harris corner detection, SIFT (Scale-Invariant Feature Transform), SURF (Speeded Up Robust Features), or ORB (Oriented FAST and Rotated BRIEF) to identify key points in eye images.

[0063] In one embodiment, based on feature point detection, a pupil localization algorithm, such as a cascaded classifier based on Haar features or a pupil detection model based on deep learning, is further used to identify the pupil region. After detecting the pupil region, the precise contour of the pupil is extracted using a pupil localization algorithm, such as morphological operations, edge detection, and thresholding.

[0064] In one embodiment, the pupil contour features can be fitted to an ellipse using methods such as least squares or subpixel edge detection. The variance of the distance between the ellipse center and the edge is then calculated, and the point with the smallest variance is taken as the pupil center. The pupil coordinates are then determined based on the coordinates of this pupil center in the camera coordinate system of the image sensor.

[0065] In one embodiment, the pupil center can also be located and its coordinates calculated based on gradients, corneal reflection, or other methods. For example, the gradient-based method calculates the gradient of each pixel in the image and finds the point where the lines intersect most frequently along the gradient direction as the pupil center. The corneal reflection-based method assists in locating the pupil center by detecting reflected light spots on the cornea, which can reduce the image processing area to some extent and improve real-time performance and the recognition rate of reflected light spots. In practical applications, appropriate pupil localization algorithms can be used to collect the pupil coordinates (including the left and right eye pupil coordinates) of the target user according to the actual application requirements.

[0066] It is understood that the above-mentioned pupil localization algorithm is a related technology already disclosed in this field, and the embodiments of this application will not be described in detail here.

[0067] S102. Calculate the first adjustment amount of the image merging distance based on the current scene depth, the current parallax of the target user, and the second interpupillary distance of the target user;

[0068] In one embodiment, current parallax refers to the parallax between the target user's left and right eyes, that is, the directional difference produced when the target user observes the same target displayed object with both eyes. The angle between two points viewed from the target displayed object is taken as the parallax angle of the current parallax.

[0069] In one embodiment, the current scene depth refers to the depth information of the scene observed by the target user.

[0070] In one embodiment, the formula for calculating the first adjustment amount of the image-merging distance can be expressed as: ΔD2=f(IPD,current parallax,scene depth)

[0071] Here, f is a function used to dynamically adjust the merging distance by combining the target user's interpupillary distance (IPD), parallax, and the scene depth of the smart wearable device.

[0072] In one embodiment, the first adjustment amount of the merging distance can be adjusted in real time, that is, data such as the current scene depth, the current parallax of the target user, and the second interpupillary distance of the target user are collected in real time, the first adjustment amount of the merging distance is calculated, and the merging distance of the smart wearable device is adjusted accordingly.

[0073] In another embodiment, real-time adjustment of the merging distance may result in excessive data computation. Therefore, triggering conditions for merging distance adjustment can be set according to the user's actual needs. The need for merging distance adjustment can be determined by detecting specific data, such as significant changes in scene depth or noticeable changes in the user's interpupillary distance. By monitoring data that significantly affects the current display effect of the smart wearable device, the basis for determining whether merging distance adjustment is necessary is used, thereby reducing the computational load.

[0074] In one embodiment, at least one set of target monitoring data is acquired, wherein the target monitoring data includes one or more of scene depth, user parallax, and user interpupillary distance; the data difference between the target monitoring data and the corresponding preset reference data is calculated; when any data difference between the target monitoring data and the corresponding preset reference data is greater than or equal to a preset difference threshold, the current scene depth, the current parallax of the target user, and the second interpupillary distance of the target user are acquired based on a preset data acquisition method.

[0075] In one embodiment, when the data difference between all target monitoring data and the corresponding preset benchmark data is less than a preset difference threshold, no image merging distance adjustment calculation and operation are performed, and target monitoring data continues to be collected and detected.

[0076] In one embodiment, the target monitoring data may also be other data that affects the above data, such as user identity information, user age or years of use, user movement status, etc.

[0077] Interpupillary distance (IPD) varies among users. When multiple users wear the same smart wearable device at different times, their IPD needs to be collected based on their identity information to adjust the focusing distance. For adolescents with rapid physical development, their IPD may change significantly over time. Therefore, for users in rapid development, their IPD data can be updated periodically, and the focusing distance of the smart wearable device adjusted accordingly. Furthermore, when users are in motion, the scene depth may change significantly. Therefore, the focusing distance needs to be adjusted based on the scene depth to ensure that virtual objects adapt to the display requirements of different scenarios.

[0078] In one embodiment, triggering conditions for adjusting the merging distance can be set. When the smart wearable device detects that certain data (such as scene depth, user parallax, etc.) meets the triggering condition, it collects the current scene depth, the current parallax of the target user, and the second interpupillary distance of the target user, and calculates the first adjustment amount of the merging distance.

[0079] In one embodiment, the second pupillary distance of the target user can be tracked and calculated in real time during the pupillary distance calculation process described above. A pupillary distance change threshold can be set. When the pupillary distance data changes significantly, such as when the difference between the second pupillary distance and the first pupillary distance (or the preset pupillary distance) is greater than the pupillary distance change threshold, the calculation of the first adjustment amount of the merging distance is triggered. Based on the calculation result, the current merging distance of the smart wearable device (such as the first merging distance or the preset merging distance) is adjusted to adapt to the optimal viewing distance corresponding to the second pupillary distance.

[0080] In one embodiment, the scene depth of the smart wearable device can also be monitored in real time. When the current scene depth of the smart wearable device changes significantly, such as when the change in scene depth exceeds a preset scene depth change threshold, a calculation of the second interpupillary distance of the target user is triggered. Then, based on the current scene depth, the second interpupillary distance, and the current parallax, a first adjustment amount for the merging distance is calculated, and the merging distance of the smart wearable device is adjusted.

[0081] Among them, the scene depth corresponding to the preset merging distance or the scene depth of other known merging distances can be used as a benchmark to calculate the scene depth difference between the currently acquired scene depth and the benchmark scene depth, which is used as the scene depth change.

[0082] For example, the first interpupillary distance corresponding to the first merging distance (or the interpupillary distance corresponding to the last merging distance adjustment or a preset interpupillary distance, with the first interpupillary distance being used as an example here) can be used as a reference. The smart wearable device collects the second interpupillary distance of the target user in real time through tools such as image sensors and pupil positioning algorithms. When the interpupillary distance difference between the second interpupillary distance and the first interpupillary distance is greater than the preset interpupillary distance difference threshold, the current parallax of the target user and the current scene depth of the smart wearable device are collected, and the adjustment amount of the optimal merging distance corresponding to the second interpupillary distance relative to the first merging distance is calculated, that is, the first adjustment amount of the merging distance.

[0083] In another embodiment, the current scene depth of the smart wearable device, the current parallax of the target user, and the second interpupillary distance of the target user can be periodically collected to calculate the first adjustment amount of the merging distance for each collection cycle, and the merging distance of the smart wearable device can be adjusted accordingly. For example, the first adjustment amount of the merging distance can be calculated every minute, and the merging distance of the displayed object on the smart wearable device can be adjusted based on the first adjustment amount of the merging distance.

[0084] For example, the data collection period can be set according to the usage scenario. If the target user is in a seated state with low scene change frequency, the collection period can be set longer, such as collecting relevant data and calculating the first adjustment of the merging distance every 15 minutes, and then adjusting the merging distance once. Conversely, when the target user is in motion (such as walking, running, or cycling), the collection period can be set shorter based on the activity level. For instance, the merging distance can be adjusted every 10 seconds while walking, every 5 seconds while running, and every 3 seconds while cycling.

[0085] In one specific embodiment, the formula for calculating the first adjustment amount of the image merging distance can be expressed as: ΔD2=f(IPD, parallax, scene depth)=k1·(d2-d1)+k2·μ0+k3·ω0

[0086] Where ΔD2 represents the first adjustment amount of the image merging distance, d2 represents the second interpupillary distance, d1 represents the first interpupillary distance, μ0 represents the current parallax of the target user, ω0 represents the current scene depth of the smart wearable device, and k1, k2, and k3 represent weighting coefficients, which can be preset to fixed values ​​or adjusted according to actual needs.

[0087] S103. Calculate the target alignment distance based on the first alignment distance and the first adjustment amount of the alignment distance;

[0088] In one embodiment, the first alignment distance is added to the first alignment distance adjustment amount to obtain the target alignment distance.

[0089] In one embodiment, direction needs to be considered when calculating the first adjustment amount of the image-merging distance.

[0090] For example, in the display space of a smart wearable device, moving towards the user can be represented as negative, meaning the image distance decreases; moving away from the user can be represented as positive, meaning the image distance increases.

[0091] S104. Based on the target alignment distance, adjust the alignment distance of the smart wearable device so that the display position of the target object matches the viewing distance of the target user.

[0092] In one embodiment, the target display object is rendered based on the target merging distance. The rendering engine resets the display position of the target display object, i.e., the target merging distance. Then, based on the adjusted target merging distance, the display position and display effect of the target display object are updated so that the display position of the target display object matches the viewing distance of the target user.

[0093] The adjustment of the display effect can be determined based on the display position and the characteristics of the target object.

[0094] For example, if the image-merging distance decreases, the overall display volume of the target object can be reduced, or the display font size can be reduced, etc. If the image-merging distance increases, the overall display volume of the target object can be enlarged, or the display font size can be enlarged, etc.

[0095] This embodiment dynamically adjusts the image merging distance to adapt to different users' interpupillary distances and viewing angles, reducing eye strain from prolonged use. Through intelligent scene adaptation technology, combined with scene depth information, the image merging distance is dynamically adjusted to improve the positioning accuracy of virtual objects in the real environment. Based on the user's personalized needs (such as interpupillary distance), the image merging distance is dynamically adjusted to provide a better user experience.

[0096] This embodiment provides a method for adjusting the merging distance of a smart wearable device. This method calculates a first merging distance based on the target user's first interpupillary distance, enabling customized merging distance calculations for the target user and improving the applicability of the smart wearable device. Based on the current scene depth, the target user's current parallax, and second interpupillary distance, the merging distance adjustment amount is calculated, allowing the merging distance to dynamically change according to the actual usage environment, enhancing the adaptability and flexibility of the device display. By adjusting the merging distance of the smart wearable device to match the display position of the target object with the target user's viewing distance, the positioning accuracy of the target object is improved, thereby reducing user visual fatigue and enhancing the user's visual experience comfort.

[0097] Please refer to Figure 2, which is a flowchart illustrating a second embodiment of a method for adjusting the image distance of a smart wearable device provided in this application.

[0098] As shown in Figure 2, based on the embodiment shown in Figure 1 above, after step S103, the method further includes:

[0099] S201. Based on the preset reference matrix and the second interpupillary distance, calculate the left eye matrix and right eye matrix of the target user respectively;

[0100] In one embodiment, a reference matrix for the smart wearable device can be set.

[0101] For example, assume that the two lenses of the smart wearable device are planar lenses and are located in the same plane. A reference coordinate system is constructed using the midpoint of the line connecting the centers of the two lenses as the reference point, the line connecting the centers of the two lenses as the horizontal axis X, the direction axis perpendicular to the plane containing the two planes as the depth axis Z, and the direction axis perpendicular to both the horizontal axis X and the depth axis Z as the vertical axis Y.

[0102] For example, a reference matrix can be constructed starting from a reference point and with the Z-axis as the direction. The reference matrix can be represented as a 3×3 identity matrix, but only the Z-axis direction has non-zero elements, i.e.:

[0103] The reference matrix thus constructed represents the unit vector along the Z-axis.

[0104] It is understood that the benchmark matrix can be constructed according to actual application requirements. The benchmark matrix constructed in the embodiments of this application is only used as an example for illustration and does not constitute a specific limitation on the benchmark matrix.

[0105] Further, the current viewing angle data of the target user is obtained, wherein the current viewing angle data includes left eye viewing angle data and right eye viewing angle data; based on the current viewing angle data and the second interpupillary distance, the left eye rotation matrix of the left eye viewing angle data relative to the reference matrix and the right eye rotation matrix of the right eye viewing angle data relative to the reference matrix are calculated respectively; based on the reference matrix, the left eye rotation matrix and the right eye rotation matrix, the left eye matrix and the right eye matrix of the target user are calculated.

[0106] In one embodiment, the current viewing angle data may include pupil coordinates and line of sight, including left eye pupil coordinates and left eye line of sight, and right eye pupil coordinates and right eye line of sight.

[0107] Among them, the pupil coordinates can be obtained through the pupil positioning algorithm, and the second pupillary distance of the left and right pupils can be calculated based on the left and right pupil coordinates.

[0108] In one embodiment, the direction of gaze can be achieved using eye-tracking technology. Examples include pupil-corneal reflection, retinal image localization, structured light tracking, waveguide eye tracking, and laser-based eye-tracking sensors.

[0109] For example, the pupillary-corneal reflex method determines the direction of vision by tracking the light reflected from the cornea. When an infrared light source shines on the eye, the cornea reflects these light rays. These reflected light points are captured by an infrared camera, and the direction of vision is calculated.

[0110] For example, optical waveguide eye tracking uses optical waveguide technology combined with eye tracking to capture image data of the eye through multiple infrared LEDs and cameras, supporting real-time eye tracking and gaze point rendering.

[0111] In one embodiment, the rotation angle of the left / right eye matrix relative to the reference matrix is ​​calculated based on the target user's second interpupillary distance and the device parameters of the smart wearable device.

[0112] In one embodiment, the rotation angle can be calculated using trigonometric functions. Assuming the interpupillary distance offset is d, the rotation angle θ of the left and right eyes can be calculated using the following formula:

[0113] Where f is the focal length, typically determined by the optical design of smart wearable devices. d represents the interpupillary distance offset, and θ... left θ represents the angle of rotation of the left eye. right This indicates the angle of rotation of the right eye.

[0114] The formula for calculating the interpupillary distance offset between the left and right eyes can be expressed as:

[0115] Where d represents the interpupillary distance offset, d2 represents the second interpupillary distance, and d0 represents the preset interpupillary distance of the smart wearable device.

[0116] In one embodiment, a rotation matrix is ​​constructed based on the rotation angle. The calculated rotation angles are used to construct the rotation matrices for the left and right eyes:

[0117] Among them, R left Let R represent the left rotation matrix. right This represents a right rotation matrix.

[0118] In one embodiment, it is assumed that the reference matrix is ​​represented as M base Multiply the rotation matrices of the left and right eyes by the reference matrix to obtain the final left and right eye matrices: M left =M base ·R left M right =M base ·Rright

[0119] Therefore, the rotation angles of the left and right eyes relative to the reference matrix can be calculated, thus providing the necessary perspective information for the visual rendering of smart wearable devices and enabling users to obtain the best visual experience when using smart wearable devices, reducing visual fatigue and discomfort.

[0120] This embodiment can provide customized perspective adjustments for each user by acquiring the target user's current perspective data, including left-eye perspective data and right-eye perspective data, which helps to improve the personalization and comfort of the augmented reality experience.

[0121] S202. Based on the left eye matrix and the right eye matrix, determine the target display pose of the target display object at the target image-combination distance;

[0122] In one embodiment, in a smart wearable device, the rendering engine uses a right-eye matrix to determine the correct position of the target displayed object in the right-eye view; similarly, a left-eye matrix is ​​used to determine the correct position of the target displayed object in the left-eye view.

[0123] In one embodiment, in a smart wearable device, the rendering engine can determine the correct position of the target display object in the left-eye view and the right-eye view respectively based on the left-eye matrix and the right-eye matrix, so that the left-eye view and the right-eye view can overlap at the target image-matching distance, avoiding obvious parallax and improving the user's visual experience.

[0124] It is understood that the rendering engine uses techniques known in the art for rendering views, and this application does not specifically limit or describe them.

[0125] This embodiment uses the current viewing angle data and the second pupillary distance to calculate the rotation matrix of the left and right eyes, ensuring the accuracy of the view transformation. This allows virtual objects to be displayed in the user's field of vision with precise poses, improving the realism and immersion of augmented reality images.

[0126] S203. Based on the target display pose, adjust the pose of the target display object so that the display pose of the target display object matches the viewing distance of the target user.

[0127] In one embodiment, the pose of the target displayed object is adjusted according to the target display pose, including translation, rotation, and scaling operations, to ensure that the object is correctly aligned in the user's field of vision. For example, if the user moves their head, the position and orientation of the object need to be updated in real time to keep it consistent with the relative position of the user's line of sight.

[0128] The user's viewing distance refers to the straight-line distance from the user's eyes to the target object.

[0129] In one embodiment, the adjusted pose information is used by the rendering engine to ensure that the target display object is correctly displayed in the target user's field of view.

[0130] In one embodiment, the target alignment distance and pose of the target displayed object can be adjusted separately. Because the user's line of sight and head position may change continuously, changes in head pose may not necessarily affect scene depth or alter the user's interpupillary distance and parallax, but they will inevitably cause changes in the relative pose of the target displayed object and the user's head. Therefore, the smart wearable device can update the pose of the target displayed object in real time, but the alignment distance of the target displayed object can be adjusted according to the actual application scenario.

[0131] Generally, motion sensors (such as gyroscopes and image sensors) can be used to track the user's gaze and head position, and adjust the object's pose in real time. This ensures that the target object maintains its display pose relative to the target user, thus matching the user's viewing distance.

[0132] This embodiment calculates the target user's left-eye and right-eye matrices and determines the display pose of the target object at the target alignment distance based on these matrices. This optimizes the alignment distance, making the display position of the virtual object more consistent with the user's natural visual habits and reducing visual fatigue. Adjusting the target object's pose based on its display pose matches the user's viewing distance, allowing the augmented reality system to dynamically adapt to changes in the user's viewing angle. This improves the system's flexibility and responsiveness, and ensures that the user receives clear and accurate virtual object displays at different viewing angles and distances, enhancing the augmented reality experience.

[0133] Please refer to Figure 3, which is a schematic diagram of the structure of a first embodiment of a sync distance adjustment device for a smart wearable device provided in this application. The sync distance adjustment device for the smart wearable device is used to perform the aforementioned sync distance adjustment method for the smart wearable device.

[0134] As shown in Figure 3, the image merging distance adjustment device 300 of the smart wearable device includes: a first image merging distance calculation module 301, a first adjustment amount calculation module 302, a target image merging distance module 303, and an image merging distance adjustment module 304.

[0135] The first merging distance calculation module 301 is used to determine the first merging distance of the smart wearable device based on the first interpupillary distance of the target user.

[0136] The first adjustment calculation module 302 is used to determine the first adjustment amount of the merging distance based on the current scene depth, the current disparity of the target user and the second interpupillary distance of the target user.

[0137] The target alignment distance module 303 is used to determine the target alignment distance based on the first alignment distance and the first adjustment amount of the alignment distance;

[0138] The image merging distance adjustment module 304 is used to adjust the image merging distance of the smart wearable device based on the target image merging distance, so that the display position of the target display object in the display space of the smart wearable device matches the viewing distance of the target user.

[0139] In one embodiment, the alignment distance adjustment device 300 of the smart wearable device further includes a pose adjustment module, comprising:

[0140] The matrix calculation unit is used to calculate the left eye matrix and right eye matrix of the target user based on a preset reference matrix and the second interpupillary distance, respectively.

[0141] The position determination unit is used to determine the target display pose of the target display object at the target image distance based on the left eye matrix and the right eye matrix;

[0142] The pose adjustment unit is used to adjust the pose of the target display object based on the target display pose, so that the display pose of the target display object matches the viewing distance of the target user.

[0143] In one embodiment, the matrix calculation unit includes:

[0144] A perspective data acquisition subunit is used to acquire the current perspective data of the target user, wherein the current perspective data includes left eye perspective data and right eye perspective data;

[0145] The rotation matrix calculation subunit is used to calculate, based on the current viewing angle data and the second interpupillary distance, the left eye rotation matrix of the left eye viewing angle data relative to the reference matrix and the right eye rotation matrix of the right eye viewing angle data relative to the reference matrix.

[0146] A left-eye matrix calculation subunit is used to calculate the left-eye matrix based on the reference matrix and the left-eye rotation matrix;

[0147] The right eye matrix calculation subunit is used to calculate the right eye matrix based on the reference matrix and the right eye rotation matrix.

[0148] In one embodiment, the merging distance adjustment device 300 of the smart wearable device further includes a second pupillary distance acquisition module, comprising:

[0149] An eye image acquisition unit is used to acquire eye images of the target user;

[0150] The pupil coordinate acquisition unit is used to perform pupil localization detection on the eye image based on the feature point detection model, and obtain the left eye pupil coordinates and right eye pupil coordinates of the target user;

[0151] The second interpupillary distance calculation unit is used to calculate the second interpupillary distance of the target user based on the coordinates of the left pupil and the right pupil.

[0152] In one embodiment, the pupil coordinate acquisition unit includes:

[0153] The feature detection subunit is used to detect pupil contour features in the eye image based on the feature point detection model.

[0154] The pupil positioning subunit is used to calculate the coordinates of the pupil center point based on the pupil positioning algorithm, so as to obtain the left and right pupil coordinates of the target user.

[0155] In one embodiment, the first image merging distance calculation module 301 includes:

[0156] A preset data acquisition unit is used to acquire the preset interpupillary distance and preset merging distance of the smart wearable device;

[0157] The second adjustment calculation unit is used to determine the second adjustment amount of the merging distance based on the difference between the first pupillary distance and the preset pupillary distance;

[0158] The first merging distance calculation unit is used to determine the first merging distance based on the preset merging distance and the second adjustment amount of the merging distance.

[0159] In one embodiment, the alignment distance adjustment device 300 of the smart wearable device further includes an alignment distance adjustment judgment module, comprising:

[0160] A monitoring data acquisition unit is used to acquire at least one set of target monitoring data.

[0161] A data difference calculation unit is used to calculate the data difference between the target monitoring data and the corresponding preset benchmark data;

[0162] The image-merging distance adjustment judgment unit is used to collect the current scene depth, the current disparity of the target user, and the second interpupillary distance of the target user based on a preset data acquisition method when the data difference is greater than or equal to a preset difference threshold.

[0163] It should be noted that those skilled in the art will understand that, for the sake of convenience and brevity, the specific working process of the device and each module described above can be referred to the corresponding process in the aforementioned embodiment of the image-alignment distance adjustment method for smart wearable devices, and will not be repeated here.

[0164] The apparatus provided in the above embodiments can be implemented as a computer program that can run on the smart wearable device shown in FIG4.

[0165] Please refer to Figure 4, which is a schematic block diagram of a smart wearable device provided in an embodiment of this application. This smart wearable device can be a server.

[0166] Referring to Figure 4, the smart wearable device includes a processor, a memory, and a network interface connected via a system bus, wherein the memory may include non-volatile storage media and internal memory.

[0167] Non-volatile storage media can store operating systems and computer programs. These computer programs include program instructions that, when executed, cause the processor to perform any image-adjusting distance method for a smart wearable device.

[0168] The processor provides computing and control capabilities to support the operation of the entire smart wearable device.

[0169] Internal memory provides an environment for the execution of computer programs in non-volatile storage media. When executed by a processor, the computer program enables the processor to perform any method for adjusting the merging distance of a smart wearable device.

[0170] This network interface is used for network communication, such as sending assigned tasks. Those skilled in the art will understand that the structure shown in Figure 4 is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the smart wearable device to which the present application is applied. Specific smart wearable devices may include more or fewer components than shown in the figure, or combine certain components, or have different component arrangements.

[0171] It should be understood that the processor can be a Central Processing Unit (CPU), but it can also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Among these, a general-purpose processor can be a microprocessor or any conventional processor.

[0172] In one embodiment, the processor is configured to run a computer program stored in memory to perform the following steps:

[0173] Determine the first convergence distance of the smart wearable device based on the first interpupillary distance of the target user;

[0174] Based on the current scene depth, the current parallax of the target user, and the second interpupillary distance of the target user, a first adjustment amount for the merging distance is determined;

[0175] The target alignment distance is determined based on the first alignment distance and the first adjustment amount of the alignment distance;

[0176] Based on the target alignment distance, the alignment distance of the smart wearable device is adjusted so that the display position of the target object in the display space of the smart wearable device matches the viewing distance of the target user.

[0177] In one embodiment, after implementing the adjustment of the alignment distance of the smart wearable device based on the target alignment distance, the processor is further configured to implement:

[0178] Based on the preset reference matrix and the second interpupillary distance, the left eye matrix and right eye matrix of the target user are calculated;

[0179] Based on the left-eye matrix and the right-eye matrix, the target display pose of the target display object at the target image distance is determined;

[0180] Based on the target display pose, the pose of the target display object is adjusted so that the display pose of the target display object matches the viewing distance of the target user.

[0181] In one embodiment, when the processor calculates the left-eye matrix and right-eye matrix of the target user based on a preset reference matrix and the second interpupillary distance, it is configured to:

[0182] Obtain the current perspective data of the target user, wherein the current perspective data includes left eye perspective data and right eye perspective data;

[0183] Based on the current viewing angle data and the second interpupillary distance, calculate the left eye rotation matrix of the left eye viewing angle data relative to the reference matrix, and the right eye rotation matrix of the right eye viewing angle data relative to the reference matrix;

[0184] The left eye matrix is ​​calculated based on the reference matrix and the left eye rotation matrix;

[0185] The right eye matrix is ​​calculated based on the reference matrix and the right eye rotation matrix.

[0186] In one embodiment, before implementing the calculation of the first adjustment amount of the merging distance based on the current scene depth, the current disparity of the target user, and the second interpupillary distance of the target user, the processor is further configured to implement:

[0187] Acquire eye images of the target user;

[0188] Based on the feature point detection model, pupil localization detection is performed on the eye image to obtain the left and right pupil coordinates of the target user.

[0189] The second interpupillary distance of the target user is calculated based on the coordinates of the left and right pupils.

[0190] In one embodiment, when the processor implements the feature point detection model to perform pupil localization detection on the eye image and obtain the left and right pupil coordinates of the target user, it is configured to:

[0191] Based on the feature point detection model, the pupil contour features in the eye image are detected;

[0192] Based on the pupil localization algorithm, the coordinates of the pupil center point are calculated to obtain the coordinates of the left and right pupils of the target user.

[0193] In one embodiment, when the processor calculates the first convergence distance of the smart wearable device based on the first interpupillary distance of the target user, it is configured to:

[0194] Obtain the preset interpupillary distance and preset merging distance of the smart wearable device;

[0195] Based on the interpupillary distance difference between the first interpupillary distance and the preset interpupillary distance, a second adjustment amount for the merging distance is determined;

[0196] The first alignment distance is determined based on the preset alignment distance and the second adjustment amount of the alignment distance.

[0197] In one embodiment, before implementing the calculation of the first adjustment amount of the merging distance based on the current scene depth, the current disparity of the target user, and the second interpupillary distance of the target user, the processor is further configured to implement:

[0198] Obtain at least one set of target monitoring data;

[0199] Calculate the data difference between the target monitoring data and the corresponding preset benchmark data;

[0200] When the data difference is greater than or equal to a preset difference threshold, the current scene depth, the current disparity of the target user, and the second interpupillary distance of the target user are collected based on a preset data collection method.

[0201] The embodiments of this application also provide a computer-readable storage medium storing a computer program, the computer program including program instructions, and the processor executing the program instructions to implement any of the image-adjustment distance methods for smart wearable devices provided in the embodiments of this application.

[0202] The computer-readable storage medium can be an internal storage unit of the smart wearable device described in the foregoing embodiments, such as the hard drive or memory of the smart wearable device. Alternatively, the computer-readable storage medium can be an external storage device of the smart wearable device, such as a plug-in hard drive, SmartMediaCard (SMC), SecureDigital (SD) card, or FlashCard equipped on the smart wearable device.

[0203] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

A method for adjusting the image-merging distance of a smart wearable device, the method comprising: Determine the first convergence distance of the smart wearable device based on the first interpupillary distance of the target user; Based on the current scene depth, the current parallax of the target user, and the second interpupillary distance of the target user, a first adjustment amount for the merging distance is determined; The target alignment distance is determined based on the first alignment distance and the first adjustment amount of the alignment distance; Based on the target alignment distance, the alignment distance of the smart wearable device is adjusted so that the display position of the target object in the display space of the smart wearable device matches the viewing distance of the target user. According to claim 1, the method for adjusting the image merging distance of a smart wearable device, wherein, After adjusting the alignment distance of the smart wearable device based on the target alignment distance, the process further includes: Based on the preset reference matrix and the second interpupillary distance, the left eye matrix and right eye matrix of the target user are calculated; Based on the left-eye matrix and the right-eye matrix, the target display pose of the target display object at the target image-combination distance is determined; Based on the target display pose, the pose of the target display object is adjusted so that the display pose of the target display object matches the viewing distance of the target user. The method for adjusting the merging distance of a smart wearable device according to claim 2, wherein, The calculation of the target user's left-eye matrix and right-eye matrix based on a preset reference matrix and the second interpupillary distance includes: Obtain the current perspective data of the target user, wherein the current perspective data includes left eye perspective data and right eye perspective data; Based on the current viewing angle data and the second interpupillary distance, calculate the left eye rotation matrix of the left eye viewing angle data relative to the reference matrix, and the right eye rotation matrix of the right eye viewing angle data relative to the reference matrix. The left eye matrix is ​​calculated based on the reference matrix and the left eye rotation matrix; The right eye matrix is ​​calculated based on the reference matrix and the right eye rotation matrix. The method for adjusting the merging distance of a smart wearable device according to claim 3, wherein, The current viewing angle data includes pupil coordinates and line of sight direction; the left eye viewing angle data includes left eye pupil coordinates and left eye line of sight direction; and the right eye viewing angle data includes right eye pupil coordinates and right eye line of sight direction. The method for adjusting the merging distance of a smart wearable device according to claim 2, wherein, The step of calculating the left-eye rotation matrix of the left-eye view data relative to the reference matrix and the right-eye rotation matrix of the right-eye view data relative to the reference matrix based on the current view data and the second interpupillary distance includes: Based on the target user's second interpupillary distance and the device parameters of the smart wearable device, calculate the rotation angle of the left eye matrix relative to the reference matrix and the rotation angle of the right eye matrix relative to the reference matrix. Based on the rotation angle of the left eye matrix relative to the reference matrix, a left eye rotation matrix is ​​constructed for the left eye view data relative to the reference matrix; Based on the rotation angle of the right eye matrix relative to the reference matrix, a right eye rotation matrix is ​​constructed for the right eye view data relative to the reference matrix. The method for adjusting the merging distance of a smart wearable device according to claim 2, wherein, The pose adjustment includes translation, rotation, and scaling operations. According to claim 1, the method for adjusting the image merging distance of a smart wearable device, wherein, Before calculating the first adjustment amount of the merging distance based on the current scene depth, the current disparity of the target user, and the second interpupillary distance of the target user, the method further includes: Acquire eye images of the target user; Based on the feature point detection model, pupil localization detection is performed on the eye image to obtain the left and right pupil coordinates of the target user. The second interpupillary distance of the target user is calculated based on the coordinates of the left and right pupils. The method for adjusting the merging distance of a smart wearable device according to claim 7, wherein, The feature point detection model performs pupil localization detection on the eye image to obtain the left and right pupil coordinates of the target user, including: Based on the feature point detection model, the pupil contour features in the eye image are detected; Based on the pupil localization algorithm, the coordinates of the pupil center point are calculated to obtain the coordinates of the left and right pupils of the target user. The image-alignment distance adjustment method for a smart wearable device according to claim 8, wherein, The pupil localization algorithm calculates the coordinates of the pupil center point to obtain the left and right pupil coordinates of the target user, including: Based on the least squares method or sub-pixel edge detection technology, the pupil contour features are fitted with an ellipse, and the variance of the distance between the center of the ellipse and the edge is calculated. The point with the smallest variance is taken as the pupil center. The pupil coordinates are defined as the coordinates of the center of the pupil in the camera coordinate system where the image sensor is located. The pupil coordinates include the coordinates of the left eye pupil and the right eye pupil. According to claim 1, the method for adjusting the image merging distance of a smart wearable device, wherein, The calculation of the first convergence distance of the smart wearable device based on the first interpupillary distance of the target user includes: Obtain the preset interpupillary distance and preset merging distance of the smart wearable device; Based on the interpupillary distance difference between the first interpupillary distance and the preset interpupillary distance, a second adjustment amount for the merging distance is determined; The first alignment distance is determined based on the preset alignment distance and the second adjustment amount of the alignment distance. The method for adjusting the merging distance of a smart wearable device according to claim 10, wherein, The step of determining the second adjustment amount of the merging distance based on the interpupillary distance difference between the first interpupillary distance and the preset interpupillary distance includes: Calculate the interpupillary distance difference between the first interpupillary distance and the preset interpupillary distance; The second adjustment amount of the merging distance is calculated based on the interpupillary distance difference and specific parameters of the optical system of the smart wearable device. According to claim 1, the method for adjusting the image merging distance of a smart wearable device, wherein, Before calculating the first adjustment amount of the merging distance based on the current scene depth, the current disparity of the target user, and the second interpupillary distance of the target user, the method further includes: Acquire at least one set of target monitoring data, wherein the target monitoring data includes one or more of scene depth, user parallax, and user interpupillary distance; Calculate the data difference between the target monitoring data and the corresponding preset benchmark data; When the difference between any of the target monitoring data and the corresponding preset benchmark data is greater than or equal to a preset difference threshold, the current scene depth, the current parallax of the target user, and the second interpupillary distance of the target user are collected based on a preset data acquisition method. The method for adjusting the image merging distance of a smart wearable device according to claim 12, wherein, The step of collecting data based on a preset data acquisition method when the difference between any target monitoring data and the corresponding preset reference data is greater than or equal to a preset difference threshold, including collecting the current scene depth, the current disparity of the target user, and the second interpupillary distance of the target user, based on a preset data acquisition method, includes: Based on the first interpupillary distance corresponding to the first merging distance, the second interpupillary distance of the target user is collected in real time. When the interpupillary distance difference between the second interpupillary distance and the first interpupillary distance is greater than the preset interpupillary distance difference threshold, the current parallax of the target user and the current scene depth of the smart wearable device are collected. The method for adjusting the image merging distance of a smart wearable device according to claim 12, wherein, The step of collecting data based on a preset data acquisition method when the difference between any target monitoring data and the corresponding preset reference data is greater than or equal to a preset difference threshold, including collecting the current scene depth, the current disparity of the target user, and the second interpupillary distance of the target user, based on a preset data acquisition method, includes: Using the scene depth corresponding to the preset merging distance as the reference scene depth, the scene depth of the smart wearable device is monitored in real time. When the change in scene depth between the currently collected scene depth and the reference scene depth is greater than the preset scene depth change threshold, the current disparity of the target user and the second interpupillary distance of the target user are collected. According to claim 1, the method for adjusting the image merging distance of a smart wearable device, wherein, The calculation of the first adjustment amount for the merging distance based on the current scene depth, the current disparity of the target user, and the second interpupillary distance of the target user includes: The data collection period is set according to the usage scenario, and the current scene depth of the smart wearable device, the current gaze of the target user, and the second interpupillary distance of the target user are collected periodically. Based on the periodically collected foreground scene depth, the target user's current gaze, and the target user's second pupil distance, the first adjustment amount of the merging distance corresponding to each collection cycle is calculated. According to claim 1, the method for adjusting the image merging distance of a smart wearable device, wherein, The step of adjusting the alignment distance of the smart wearable device based on the target alignment distance, so that the display position of the target object matches the viewing distance of the target user, includes: Based on the target image merging distance, the target display object is rendered, and the target image merging distance of the target display object is reset; Based on the adjusted target alignment distance, the display position and display effect of the target display object are updated so that the display position of the target display object matches the viewing distance of the target user. According to claim 1, the method for adjusting the image merging distance of a smart wearable device, wherein, The first pupillary distance is the pupillary distance data measured when the target user first wears the smart wearable device; or, the first pupillary distance is the pupillary distance data collected last time when the target user last wore the smart wearable device; or, the first pupillary distance is the pupillary distance data collected for the first time when the target user is currently wearing the smart wearable device. A alignment distance adjustment device for a smart wearable device, the alignment distance adjustment device for the smart wearable device comprising: The first merging distance calculation module is used to calculate the first merging distance of the smart wearable device based on the first interpupillary distance of the target user. The first adjustment calculation module is used to calculate the first adjustment amount of the image-merging distance based on the current scene depth, the current disparity of the target user, and the second interpupillary distance of the target user. The target alignment distance module is used to calculate the target alignment distance based on the first alignment distance and the first adjustment amount of the alignment distance; The image merging distance adjustment module is used to adjust the image merging distance of the smart wearable device based on the target image merging distance, so that the display position of the target object matches the viewing distance of the target user. A smart wearable device includes a processor, a memory, and a computer program stored in the memory and executable by the processor, wherein when the computer program is executed by the processor, it implements the steps of the image-alignment distance adjustment method of the smart wearable device as described in any one of claims 1 to 17. A computer-readable storage medium storing a computer program, wherein when executed by a processor, the computer program implements the steps of the image-alignment distance adjustment method for a smart wearable device as described in any one of claims 1 to 17.

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