Image adjusting method based on XR glasses, XR glasses, electronic device and medium

Abstract

The invention relates to an image adjusting method based on XR glasses, the XR glasses, an electronic device and a medium, the XR glasses comprise a first display screen and a second display screen, the pupil distance of a user, the lens spacing of the XR glasses, the distance of a virtual target and the focal length of the virtual target are obtained; calculating convergence angles according to the interpupillary distance, the lens spacing, the distance of the virtual target and the focal length of the virtual target; adjusting the depth of field and the position of the virtual target in the XR glasses according to the convergence angles; and the convergence conflicts in the convergence adjustment process are relieved, and the visual fatigue of the user is relieved.

Description

Technical Field

[0001] The present application relates to the field of XR glasses, and in particular to an image adjustment method based on XR glasses, XR glasses, an electronic device and a medium. Background Art

[0002] Myopia is a common vision problem worldwide, caused by over-accommodation of the eyeball. Long-term close-up use can lead to excessive tension in the eye muscles and over-accommodation, which can cause axial length enlargement and ultimately myopia. Currently, the prevention and control of myopia primarily relies on methods such as wearing glasses, orthokeratology lenses, and supplementary measures such as outdoor activities and eye exercises, but these methods are limited in effectiveness.

[0003] With the rapid development of augmented reality technology in recent years, research on using it to prevent and control myopia has also made progress. Currently, XR glasses that support virtual image adjustment have appeared on the market, enabling naked-eye 3D training and, to a certain extent, achieving parallax fusion. However, such devices can easily cause eye fatigue in users and worsen myopia.

[0004] At present, there is no effective solution to the problem of XR glasses in related technologies causing visual fatigue in users. Summary of the Invention

[0005] Based on this, it is necessary to provide an image adjustment method based on XR glasses, XR glasses, electronic device and medium that can alleviate user visual fatigue in response to the above technical problems.

[0006] In a first aspect, the present application provides an image adjustment method based on XR glasses, wherein the XR glasses include a first display screen and a second display screen, and the method includes:

[0007] Obtain the user's pupil distance, the distance between the lenses of the XR glasses, the distance of the virtual target, and the focal length of the virtual target;

[0008] Calculating a convergence angle according to the pupil distance, the lens distance, the distance of the virtual target, and the focal length of the virtual target;

[0009] The depth of field and position of the virtual target in the XR glasses are adjusted according to the convergence angle.

[0010] In one embodiment, the convergence angle is calculated based on the user's pupil distance, the lens spacing of the XR glasses, the distance of the virtual target, and the focal length of the virtual target, including:

[0011] adjusting the distance of the virtual target based on the lens spacing, and using the adjusted distance of the virtual target as the opposite side of a right triangle;

[0012] adjusting the pupil distance based on the focal length of the virtual target, and using the adjusted pupil distance as an adjacent side of the right triangle;

[0013] The angle between the opposite side and the adjacent side is calculated to obtain the convergence angle.

[0014] In one embodiment, calculating the angle between the opposite side and the adjacent side to obtain the convergence angle includes:

[0015] α=arctan((d×T) / (2×I×f)); wherein α represents the convergence angle, d represents the distance of the virtual target, T represents the lens spacing, I represents the pupil distance, and f represents the focal length of the virtual target.

[0016] In one embodiment, adjusting the depth of field and position of the virtual target in the XR glasses according to the convergence angle includes:

[0017] Calculating a target depth of field value of the virtual target in the XR glasses according to the convergence angle and the distance of the virtual target, and adjusting the focal length of the virtual target according to the target depth of field value;

[0018] A horizontal position offset is calculated according to the convergence angle, the pupil distance, and the lens distance, and the virtual objects in the first display screen and the second display screen are horizontally offset according to the horizontal position offset.

[0019] In one embodiment, adjusting the focal length of the virtual target according to the target depth of field value includes:

[0020] Detecting the current distance of the virtual target and determining whether there is a difference between the current distance of the virtual target and the target depth of field value;

[0021] If it is determined that there is a difference between the current distance to the virtual target and the target depth of field value, Gaussian blur processing is applied to the virtual target.

[0022] In one embodiment, after adjusting the depth of field and position of the virtual target in the XR glasses according to the convergence angle, the method further includes:

[0023] Acquiring historical training data and visual fatigue feedback data of the user; wherein the historical training data includes: virtual target depth of field adjustment data and virtual target position adjustment data; the visual fatigue feedback data includes: user's physiological index data and subjective feedback data;

[0024] Using the historical training data and the visual fatigue feedback data as a training set, training a machine learning model; wherein the input of the machine learning model includes the physiological indicator data and subjective feedback data of the user, and the output of the machine learning model includes adjustment parameters of depth of field and position;

[0025] The current physiological indicator data and subjective feedback data of the user are input into the trained machine learning model as prediction variables to predict the current adjustment parameters, and the response speed and amplitude of the depth of field and position adjustment of the virtual target in the XR glasses are adjusted according to the current adjustment parameters.

[0026] In the second aspect, the present application also provides an XR glasses, comprising: a sensor module, a processing module and a display module; wherein the sensor module is used to collect the user's pupil distance; the processing module is used to execute the method described in the first aspect above; the display module includes a first display screen and a second display screen, and the first display screen and the second display screen are used to display the same virtual target at different distances.

[0027] In one embodiment, the sensor module includes a pupil distance sensor and an eye tracking sensor.

[0028] In a third aspect, the present application further provides an electronic device comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the method described in the first aspect when executing the computer program.

[0029] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, which implements the steps of the method described in the first aspect when the computer program is executed by a processor.

[0030] The above-mentioned image adjustment method based on XR glasses, XR glasses, electronic devices and media, when calculating the convergence angle, XR glasses not only consider the user's pupil distance and the distance of the virtual target, but also consider the lens spacing of the glasses and the focal length of the virtual target, thereby linking the individual differences of XR glasses and the display method of the virtual target in actual applications to improve the accuracy of the convergence angle. It will be more reasonable to adjust the depth of field and position of the virtual target according to the convergence angle, thereby alleviating the convergence conflict existing in the convergence adjustment process, thereby solving the problem of visual fatigue, and being more conducive to myopia prevention and control. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 FIG1 is a hardware structure block diagram of a terminal of an image adjustment method in one embodiment;

[0032] Figure 2 is a structural block diagram of XR glasses in one embodiment;

[0033] Figure 3 1 is a flow chart of an image adjustment method based on XR glasses in one embodiment;

[0034] Figure 4 is a structural block diagram of XR glasses in another embodiment;

[0035] Figure 5 FIG1 is a schematic diagram of a convergence adjustment process based on XR glasses in one embodiment;

[0036] Figure 6 1. A schematic diagram of a convergence accommodation feedback training process based on XR glasses in one embodiment;

[0037] Figure 7 Schematic diagram of the eye training process based on XR glasses in one embodiment. DETAILED DESCRIPTION

[0038] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0039] Unless otherwise defined, the technical terms or scientific terms involved in this application should have the general meaning understood by people with ordinary skills in the technical field to which this application belongs. The words "one", "an", "a", "the", "these" and the like in this application do not indicate quantitative restrictions, and they can be singular or plural. The terms "include", "comprise", "have" and any variants thereof involved in this application are intended to cover non-exclusive inclusions; for example, a process, method and system, product or device comprising a series of steps or modules (units) is not limited to the listed steps or modules (units), but may include unlisted steps or modules (units), or may include other steps or modules (units) inherent to these processes, methods, products or devices. The words "connect", "connected", "coupled" and the like involved in this application are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. The "plurality" involved in this application refers to two or more. "And / or" describes the relationship between related objects, indicating that three possible relationships exist. For example, "A and / or B" can represent: A exists alone, A and B exist simultaneously, and B exists alone. Generally, the character " / " indicates that the related objects are in an "or" relationship. The terms "first," "second," "third," etc. used in this application are only used to distinguish similar objects and do not represent a specific ordering of the objects.

[0040] The method embodiment provided in this embodiment can be executed in an electronic device, which can be a terminal, a computer or a similar computing device. For example, running on a terminal, Figure 1 FIG. 1 is a block diagram of the hardware structure of a terminal of an image adjustment method according to an embodiment of the present application. Figure 1 As shown, the terminal may include one or more ( Figure 1 Only one is shown) processor 101 and memory 102 for storing data, wherein processor 101 may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA. The above terminal may also include a transmission device 103 and an input / output device 104 for communication functions. It will be understood by those skilled in the art that Figure 1 The structure shown is only for illustration and does not limit the structure of the above terminal. Figure 1 More or fewer components than shown, or with Figure 1 Different configurations shown.

[0041] The memory 102 can be used to store computer programs, for example, software programs and modules of application software, such as the computer program corresponding to the image adjustment method based on XR glasses in this embodiment. The processor 101 executes various functional applications and data processing by running the computer program stored in the memory 102, that is, implementing the above method. The memory 102 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 102 may further include a memory remotely located relative to the processor 101, and these remote memories may be connected to the terminal via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and a combination thereof.

[0042] The transmission device 103 is used to receive or send data via a network. The network may include a wireless network provided by the terminal's telecommunications provider. In one embodiment, the transmission device 103 includes a network interface controller (NIC), which can be connected to other network devices via a base station to enable communication with the Internet. In another embodiment, the transmission device 103 may be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0043] Parallax refers to the difference in spatial position of the same object under different viewing angles. Dual-screen split vision uses the principle of parallax to project images of the same scene from different perspectives to the left and right eyes respectively, achieving the effect of simulating real scenes of objects near and far. Specifically, the left and right display screens of XR glasses respectively display left and right perspective images of the same scene, and there is a certain parallax angle α between the two images. When a user wears XR glasses, the left and right eyes receive images from the left and right display screens respectively. Due to the existence of the parallax angle, the user's brain will synthesize the two images into a three-dimensional image, thereby producing a sense of depth. The relationship between the parallax angle, object distance d, and viewing angle change Δθ is as follows:

[0044] α=Δθ×d

[0045] The larger the parallax angle α is, the stronger the sense of depth is.

[0046] After a certain parallax is formed by the dichroic images, when the user observes an object, their eyes automatically turn inward so that the visual axes of the two eyes intersect on the target object, forming a process of convergence accommodation. This allows the two eyes to obtain different perspectives of the same object, which are then fused in the brain to form a complete stereoscopic image, thereby improving visual clarity and three-dimensional perception. For myopic patients, due to changes in the refractive power of the eyeball, distant objects cannot be focused on the retina, thus affecting visual clarity. Convergence accommodation can help myopic patients focus their vision on the target object and improve visual clarity.

[0047] Generally, the angle at which the eyes need to turn inward can be calculated based on the distance between the user's pupils and the distance between the virtual target. This is also known as the convergence angle. The following is the formula for calculating the convergence angle of augmented reality glasses, virtual reality glasses, or other similar devices that achieve binocular vision:

[0048] α=arctan(d / I)

[0049] Where α represents the convergence angle in degrees; d represents the distance of the virtual target in meters; and I represents the user's interpupillary distance in meters.

[0050] The distance d to the virtual target serves as the opposite side of a right triangle, the user's interpupillary distance I serves as the adjacent side of the right triangle, and the angle of convergence α is the angle between the opposite and adjacent sides. As the virtual target gets farther away, the larger the value of d and the smaller the value of α, the smaller the inward rotation angle. Conversely, as the virtual target gets closer, the smaller the value of d and the larger the value of α, the larger the inward rotation angle.

[0051] Dual-screen split vision can cause a vergence–accommodation conflict (VAC). When a viewer is watching a binocular image with horizontal parallax, the viewer's line of sight is focused on the imaging plane (e.g., the screen), while the three-dimensional virtual image perceived by the viewer based on the binocular image with horizontal parallax is located in front of or behind the imaging plane. When the viewer's line of sight is focused on the imaging plane, the viewer's eye's refractive power is the actual refractive power. When the viewer's line of sight is focused on the perceived three-dimensional virtual image, the viewer's eye's refractive power is the equivalent refractive power. The difference between the equivalent refractive power and the actual refractive power is called the vergence conflict. Although the naked-eye 3D training of the related art achieves parallax fusion, it requires the user to be in a fixed position, which inevitably causes forward and backward offsets, and cannot form a complete visual fusion point, which will aggravate the vergence conflict. Therefore, it is easy to cause visual fatigue in users, aggravate myopia, and even cause dizziness or other physical discomfort.

[0052] Based on the above analysis, this embodiment provides XR (Extended Reality) glasses that can stimulate the coordinated movement of the user's extraocular muscles by changing parallax. Through periodic training, these glasses can improve extraocular muscle coordination and enhance accommodation. During training, these glasses can resolve convergence conflict, alleviate visual fatigue, and are suitable for myopia prevention and control. Figure 2 This is a structural block diagram of the XR glasses, which includes: a sensor module 1, a processing module 2 and a display module 3; wherein the sensor module 1 is used to collect the user's pupil distance; the processing module 2 is used to perform image adjustment; the display module 3 includes a first display screen 31 and a second display screen 32, and the first display screen 31 and the second display screen 32 can display the same virtual target at different distances. Specifically, the processing module 2 is responsible for receiving the sensor data collected by the sensor module 1, and performing image processing and picture rendering operations based on the sensor data, and then adjusting the display parameters of the display module 3 to achieve image adjustment, and the image adjustment includes convergence adjustment. Optionally, image adjustment can also include zooming out the screen distance and pupil distance correction. In this embodiment, the XR glasses can be AR (Augmented Reality) glasses, VR (Virtual Reality) glasses or MR (Mixed Reality) glasses, which are not limited in this embodiment.

[0053] Figure 3 This is the image adjustment method based on XR glasses in this embodiment. The process includes the following steps:

[0054] Step S101: Obtain the user's pupil distance, the lens spacing of the XR glasses, the distance of the virtual target, and the focal length of the virtual target.

[0055] When a user puts on the XR glasses and starts them up, sensor module 1 collects the user's interpupillary distance (IPD), which is the distance between the centers of a person's pupils. The lens spacing of XR glasses refers to the distance between the centers of the two lenses in the XR glasses. The distance to the virtual target refers to the distance between the perceived position of the virtual target in the user's field of view and the user's eyes. The focal length of the virtual target refers to the distance at which the user's eyes focus on the virtual target.

[0056] Step S102 : Calculate the convergence angle according to the pupil distance, the lens distance, the distance of the virtual target, and the focal length of the virtual target.

[0057] Processing module 2 adjusts the distance of the virtual target based on the lens spacing and uses the adjusted distance of the virtual target as the opposite side of the right triangle; adjusts the pupil distance based on the focal length of the virtual target and uses the adjusted pupil distance as the adjacent side of the right triangle; and calculates the angle between the opposite side and the adjacent side to obtain the convergence angle. The specific calculation formula is as follows:

[0058] α=arctan((d×T) / (2×I×f))

[0059] Where α represents the angle of convergence in degrees; d represents the distance to the virtual target in meters; T represents the lens spacing in meters; I represents the pupil distance in meters; and f represents the focal length of the virtual target in meters.

[0060] Step S103: Adjust the depth of field and position of the virtual target in the XR glasses according to the convergence angle.

[0061] In this step, adjustment parameters for the depth and position of the virtual target can be determined based on the convergence angle, including a target depth value and a horizontal position offset. The perceived depth of the virtual target can be adjusted based on the target depth value, and the parallax offset between the left and right eyes with respect to the virtual target can be adjusted based on the horizontal position offset.

[0062] In the above steps S101 to S103, when calculating the convergence angle, the XR glasses not only consider the user's pupil distance and the distance of the virtual target, but also consider the lens spacing of the glasses and the focal length of the virtual target, thereby linking the individual differences of the XR glasses and the display method of the virtual target in actual applications to improve the accuracy of the convergence angle. It will be more reasonable to adjust the depth of field and position of the virtual target according to the convergence angle, thereby alleviating the convergence conflict in the convergence adjustment process, thereby solving the problem of visual fatigue and being more conducive to myopia prevention and control.

[0063] In one embodiment, Figure 4A block diagram of another XR glasses structure is provided, in which the sensor module 1 includes an interpupillary distance sensor 11 and an eye tracking sensor 12. The interpupillary distance sensor 11 is used to detect the user's interpupillary distance, and the eye tracking sensor 22 is used to collect information about the user's eye movements. Furthermore, the XR glasses also include a control module 4 for controlling the operation of the XR glasses and interacting with the user.

[0064] In one implementation, Figure 5 A flow chart of convergence adjustment based on XR glasses is provided. The method can be run on Figure 4 XR glasses, such as Figure 5 As shown, the process includes the following steps:

[0065] In step S201 , a target depth of field value of the virtual target in the XR glasses is calculated according to the convergence angle and the distance of the virtual target, and the focal length of the virtual target is adjusted according to the target depth of field value.

[0066] The target depth of field value D' can be calculated by using the convergence angle α and the distance d of the virtual target through the first mapping relationship, as follows:

[0067] D′=d×cos(α)

[0068] After calculating the target depth of field value D', the virtual object's focal length f is adjusted to match the target depth of field value D' to adjust the perceived depth of the virtual object. In practical applications, the rendering parameters of the two display screens in display module 3 can be dynamically adjusted to ensure that the focus of the virtual object falls at the calculated depth of field position.

[0069] In some embodiments, the current distance of the virtual target can also be detected in real time, and it can be determined whether there is a difference between the current distance of the virtual target and the target depth of field value; if it is determined that there is a difference between the current distance to the virtual target and the target depth of field value, Gaussian blur processing is applied to the virtual target to simulate the natural blur gradient when the human eye focuses, thereby ensuring the consistency of visual perception when the user's eyes are focused.

[0070] Step S202 : Calculate a horizontal position offset according to the convergence angle, the pupil distance, and the lens distance, and horizontally offset the virtual objects on the first display screen and the second display screen respectively according to the horizontal position offset.

[0071] The horizontal position offset Δx can be calculated using the second mapping relationship using the convergence angle α, the user's pupil distance I, and the lens spacing T. The calculation is as follows:

[0072] Δx=(I×tan(α)) / 2

[0073] After calculating the horizontal position offset Δx, the virtual objects on the first and second displays 31 are horizontally offset by ±Δx to match the parallax requirements corresponding to the convergence angle α, thereby achieving parallax offset between the left and right eye images. In practical applications, the horizontal position offset can be dynamically calibrated in conjunction with real-time data collected by the eye tracking sensor 12 to ensure the virtual object's position remains stable in the user's line of sight and avoid visual misalignment caused by minor head movements.

[0074] In some embodiments, after adjusting the depth of field and position of the virtual target in the XR glasses according to the convergence angle, the user's convergence state can also be monitored by the eye tracking sensor 12, and it can be determined whether the deviation between the current convergence angle and the target value exceeds a threshold; if it is determined that the deviation between the current convergence angle and the target value exceeds the threshold, the depth of field and position of the virtual target in the XR glasses are recalculated and adjusted.

[0075] In the above steps S201 to S202, the XR glasses can accurately adapt to the user's physiological characteristics and the display requirements of the virtual target, dynamically optimize the depth of field and position, effectively alleviate the conflict in the convergence adjustment process, thereby reducing visual fatigue and improving the effect of myopia control.

[0076] In some embodiments, Figure 6 A vergence accommodation feedback training method based on XR glasses is provided. Figure 6 As shown, after adjusting the depth of field and position of the virtual target in the XR glasses according to the convergence angle, the method further includes the following steps:

[0077] Step S301: Obtain the user's historical training data and visual fatigue feedback data.

[0078] Among them, historical training data includes: virtual target depth of field adjustment data, virtual target position adjustment data; visual fatigue feedback data includes: user's physiological index data and subjective feedback data;

[0079] Step S302: Use the historical training data and visual fatigue feedback data as training sets to train the machine learning model.

[0080] Among them, the input of the machine learning model includes the user's physiological indicator data and subjective feedback data, and the output of the machine learning model includes adjustment parameters of depth of field and position.

[0081] In step S303, the physiological indicator data and subjective feedback data of the current user are input into the trained machine learning model as prediction variables to predict the current adjustment parameters, and the response speed and amplitude of the depth of field and position adjustment of the virtual target in the XR glasses are adjusted according to the current adjustment parameters.

[0082] In this embodiment, the response speed and amplitude of depth of field and position adjustment are adaptively optimized based on the user's historical training data and visual fatigue feedback data, which helps to improve the user's comfort in long-term use of XR glasses.

[0083] In one embodiment, in addition to supporting dual-screen split vision training and convergence accommodation training, XR glasses also support distance vision training and pupil distance correction training.

[0084] Among them, dual-screen split-view training refers to using the dual-screen split-view function to simulate real scenes of far and near objects, effectively exercising the eye's adjustment function and improving the elasticity and coordination of the eye muscles.

[0085] Vergence accommodation training refers to training the eyes' convergence accommodation function simultaneously through the dual-screen split-viewing function, that is, adjusting both eyes to focus on the target object at the same time, which is closer to the actual visual experience.

[0086] Farsightedness training involves increasing the distance of the image. By adjusting the focal length of the virtual target, the virtual target can be projected to the target location, which should be no less than 5 meters. During training, users can use the dual-screen split-view function to simultaneously view the real scene in the distance, avoiding staring at the virtual image for long periods of time and effectively protecting their eyesight. Perspective projection maps points in three-dimensional space onto a two-dimensional plane. The formula is as follows:

[0087] x'=x×f / (z+f)

[0088] y'=y×f / (z+f)

[0089] Where (x, y, z) is the coordinates of a point in three-dimensional space, (x', y') is the coordinates of a point on a two-dimensional plane, and f is the focal length. By adjusting the focal length f, you can change the projected position of the image on the two-dimensional plane, thereby achieving the effect of increasing the distance between the images.

[0090] Interpupillary distance correction training refers to the ability to automatically adjust the depth of field and screen position of the virtual image according to the user's interpupillary distance, ensuring that users with different interpupillary distances can obtain the best visual experience and improve the training effect. The calculation formula for interpupillary distance correction is as follows:

[0091] d'=d×(I+T) / (2×I)

[0092] Where d' is the optimal depth of field of the virtual image, d is the actual distance of the target object, I is the user's interpupillary distance, and T is the distance between the lenses of the XR glasses. The XR glasses automatically adjust the depth of field and image position of the virtual image based on this formula to ensure a clear stereoscopic viewing experience for users with different interpupillary distances, thereby improving training effectiveness.

[0093] In one embodiment, XR glasses can adjust the training program in real time based on the user's eye condition, training effect and other data to improve training efficiency and efficacy. Figure 7 An eye training method based on XR glasses is provided, the method comprising the following steps:

[0094] Step S401: The user wears XR glasses and starts the system.

[0095] In step S402 , the XR glasses identify the user's pupil distance and automatically adjust the depth of field and screen position of the virtual image based on the pupil distance information.

[0096] In step S403, the XR glasses adjust the screen distance in real time according to the user's eye movement and system preset parameters, and perform far and near adjustment training through the dual-screen split-view function.

[0097] In step S404, the user performs corresponding visual training according to the system prompts, such as identifying objects at different distances and performing visual discrimination.

[0098] In step S405, the system adjusts the training plan according to the user's training effect, such as increasing the training difficulty, extending the training time, etc., until the expected control effect is achieved.

[0099] This implementation achieves the purpose of controlling myopia by using XR glasses to view distant virtual images and utilizing the dual-screen split-view function to perform parallax and convergence adjustment training.

[0100] In addition, in conjunction with the image adjustment method based on XR glasses provided in the above embodiments, this embodiment may also provide a storage medium for implementation. The storage medium stores a computer program; when the computer program is executed by a processor, it implements any of the image adjustment methods based on XR glasses in the above embodiments.

[0101] In one embodiment, the computer program, when executed by a processor, performs the following steps:

[0102] Obtain the user's pupil distance, the distance between the lenses of the XR glasses, the distance of the virtual target, and the focal length of the virtual target;

[0103] Calculate the convergence angle based on the pupil distance, lens spacing, distance of the virtual target, and focal length of the virtual target;

[0104] Adjust the depth of field and position of the virtual target in the XR glasses according to the convergence angle.

[0105] In one embodiment, the computer program, when executed by a processor, performs the following steps:

[0106] Adjusting the distance of the virtual target based on the lens spacing, and using the adjusted distance of the virtual target as the opposite side of the right triangle;

[0107] Adjusting the interpupillary distance based on the focal length of the virtual target, and using the adjusted interpupillary distance as the adjacent side of the right triangle;

[0108] Calculate the angle between the opposite and adjacent sides to get the angle of convergence.

[0109] In one embodiment, the computer program, when executed by a processor, performs the following steps:

[0110] Calculate the target depth of field of the virtual target in the XR glasses according to the convergence angle and the distance of the virtual target, and adjust the focal length of the virtual target according to the target depth of field;

[0111] A horizontal position offset is calculated according to the convergence angle, the pupil distance, and the lens spacing, and the virtual objects in the first display screen and the second display screen are horizontally offset according to the horizontal position offset.

[0112] In one embodiment, the computer program, when executed by a processor, performs the following steps:

[0113] Detecting the current distance of the virtual target and determining whether there is a difference between the current distance of the virtual target and the target depth of field value;

[0114] If it is determined that there is a difference between the current distance to the virtual target and the target depth of field value, Gaussian blur processing is applied to the virtual target.

[0115] In one embodiment, the computer program, when executed by a processor, performs the following steps:

[0116] Obtaining the user's historical training data and visual fatigue feedback data; wherein the historical training data includes: virtual target depth of field adjustment data, virtual target position adjustment data; visual fatigue feedback data includes: user's physiological index data and subjective feedback data;

[0117] The historical training data and visual fatigue feedback data are used as training sets to train a machine learning model. The input of the machine learning model includes the user's physiological indicator data and subjective feedback data, and the output of the machine learning model includes adjustment parameters for depth of field and position.

[0118] The current user's physiological indicator data and subjective feedback data are input into the trained machine learning model as predictive variables to predict the current adjustment parameters. The response speed and amplitude of the depth of field and position adjustment of the virtual target in the XR glasses are adjusted according to the current adjustment parameters.

[0119] In one embodiment, the computer program, when executed by a processor, performs the following steps:

[0120] Adjust the focal length of the virtual target and project the virtual target to the target position, which should be no less than 5 meters.

[0121] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0122] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, database or other media used in the embodiments provided in this application may include at least one of non-volatile and volatile memory. Non-volatile memory may include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory may include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, distributed databases based on blockchains. The processor involved in the various embodiments provided herein may be, but are not limited to, a general-purpose processor, a central processing unit, a graphics processing unit, a digital signal processor, a programmable logic unit, a data processing logic unit based on quantum computing, and the like.

[0123] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0124] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present application. It should be noted that a person of ordinary skill in the art may make various modifications and improvements without departing from the spirit of the present application, and these modifications and improvements fall within the scope of protection of the present application. Therefore, the scope of protection of the present application shall be determined by the appended claims.

Claims

1. An image adjustment method based on XR glasses, characterized in that: The XR glasses include a first display screen and a second display screen, and the method includes: Obtain the user's pupil distance, the distance between the lenses of the XR glasses, the distance of the virtual target, and the focal length of the virtual target; Calculating a convergence angle according to the pupil distance, the lens distance, the distance of the virtual target, and the focal length of the virtual target; The depth of field and position of the virtual target in the XR glasses are adjusted according to the convergence angle.

2. The image adjustment method based on XR glasses according to claim 1, characterized in that: Calculating the convergence angle according to the user's pupil distance, the lens spacing of the XR glasses, the distance of the virtual target, and the focal length of the virtual target includes: adjusting the distance of the virtual target based on the lens spacing, and using the adjusted distance of the virtual target as the opposite side of a right triangle; adjusting the pupil distance based on the focal length of the virtual target, and using the adjusted pupil distance as an adjacent side of the right triangle; The angle between the opposite side and the adjacent side is calculated to obtain the convergence angle.

3. The image adjustment method based on XR glasses according to claim 2, characterized in that: Calculating the angle between the opposite side and the adjacent side to obtain the convergence angle includes: α=arctan((d×T) / (2×I×f)); wherein α represents the convergence angle, d represents the distance of the virtual target, T represents the lens spacing, I represents the pupil distance, and f represents the focal length of the virtual target.

4. The image adjustment method based on XR glasses according to claim 1, characterized in that: Adjusting the depth of field and the position of the virtual target in the XR glasses according to the convergence angle includes: Calculating a target depth of field value of the virtual target in the XR glasses according to the convergence angle and the distance of the virtual target, and adjusting the focal length of the virtual target according to the target depth of field value; A horizontal position offset is calculated according to the convergence angle, the pupil distance, and the lens distance, and the virtual objects in the first display screen and the second display screen are horizontally offset according to the horizontal position offset.

5. The image adjustment method based on XR glasses according to claim 4, characterized in that: Adjusting the focal length of the virtual target according to the target depth of field value includes: Detecting the current distance of the virtual target and determining whether there is a difference between the current distance of the virtual target and the target depth of field value; If it is determined that there is a difference between the current distance to the virtual target and the target depth of field value, Gaussian blur processing is applied to the virtual target.

6. The image adjustment method based on XR glasses according to claim 1, characterized in that: After adjusting the depth of field and the position of the virtual target in the XR glasses according to the convergence angle, the method further includes: Acquiring historical training data and visual fatigue feedback data of the user; wherein the historical training data includes: virtual target depth of field adjustment data and virtual target position adjustment data; the visual fatigue feedback data includes: user's physiological index data and subjective feedback data; Using the historical training data and the visual fatigue feedback data as a training set, training a machine learning model; wherein the input of the machine learning model includes the physiological indicator data and subjective feedback data of the user, and the output of the machine learning model includes adjustment parameters of depth of field and position; The current physiological indicator data and subjective feedback data of the user are input into the trained machine learning model as prediction variables to predict the current adjustment parameters, and the response speed and amplitude of the depth of field and position adjustment of the virtual target in the XR glasses are adjusted according to the current adjustment parameters.

7. An XR glasses, characterized in that: include: A sensor module, a processing module and a display module; wherein the sensor module is used to collect the user's pupil distance; the processing module is used to execute the method described in any one of claims 1 to 6; the display module includes a first display screen and a second display screen, and the first display screen and the second display screen are used to display the same virtual target at different distances.

8. The XR glasses according to claim 7, wherein: The sensor module includes a pupil distance sensor and an eye tracking sensor.

9. An electronic device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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