Method for adjusting image on the basis of eye distance and electronic device

Abstract

The present application relates to the technical field of terminals. Provided are a method for adjusting an image on the basis of an eye distance and an electronic device, which can achieve a more precise and effective eye protection display effect and alleviate myopia progression of a user. The method comprises: an electronic device displays an interface of a target application, the interface comprising an image; when an eye distance is a first distance, the electronic device displays the image at a first degree of blurring; and, when the eye distance is a second distance, the electronic device displays the image at a second degree of blurring. The eye distance is the distance from an eye to a display screen, the first distance is different from the second distance, and the first degree of blurring is different from the second degree of blurring.

Description

A method and electronic device for adjusting images based on human eye distance Technical Field

[0001] This application relates to the field of terminal technology, and in particular to a method and electronic device for adjusting images based on human eye distance. Background Technology

[0002] Myopia is an extremely common eye disease. In recent years, due to the widespread use of consumer electronic devices, the myopia rate among children and teenagers has been rising year by year. According to relevant data, the trend of myopia onset at younger ages has been very obvious in recent years.

[0003] To effectively prevent and control myopia, some electronic devices (such as mobile phones and tablets) offer eye-protection technologies. However, current eye-protection technologies can only prevent myopia and cannot meet the needs of myopic users for effective eye protection, thus affecting the effectiveness of myopia prevention and control. Therefore, for myopic users, how to achieve more precise and effective eye-protection display effects and alleviate the worsening of myopia is a pressing problem that needs to be solved.

[0004] Summary of the Invention

[0005] This application provides a method and electronic device for adjusting images based on human eye distance, which can achieve a more accurate and effective eye-protection display effect and alleviate the aggravation of myopia in users.

[0006] To achieve the above objectives, the embodiments of this application adopt the following technical solutions:

[0007] In a first aspect, a method for adjusting an image based on human eye distance is provided. The method is applied in an electronic device, the electronic device including a display screen. The method includes: the electronic device displaying an interface of a target application, the interface including an image; the electronic device displaying the image with a first degree of blur when the human eye distance is a first distance; and the electronic device displaying the image with a second degree of blur when the human eye distance is a second distance; wherein the human eye distance is the distance between the human eye and the display screen, the first distance and the second distance are different, and the first degree of blur is different from the second degree of blur.

[0008] Based on the first aspect, by displaying images with different degrees of blur at different eye distances, a more accurate and effective eye-protection display effect can be achieved, alleviating the aggravation of users' myopia.

[0009] The image can be from a video or a photograph. The images displayed by the electronic device at a first level of blur and a second level of blur can be the same or different. For example, in a reading scenario, when the electronic device displays the same image, the images displayed at the first and second levels of blur will be the same when the viewer's distance changes from a first distance to a second distance. However, in a video scenario, when the electronic device displays different images, the images displayed at the first and second levels of blur will be different when the viewer's distance changes from a first distance to a second distance.

[0010] In one implementation of the first aspect, the first distance is smaller than the second distance, and the first degree of blur is lower than the second degree of blur. In other words, the closer the human eye is, the lower the degree of blur; correspondingly, the farther the human eye is, the higher the degree of blur. In this way, the degree of blur can be dynamically adjusted by changing the human eye distance to achieve a more accurate and effective eye-protection display effect and alleviate the aggravation of the user's myopia.

[0011] In one implementation of the first aspect, a first distance is in a first distance interval, and a second distance is in a second distance interval; wherein the maximum value of the first distance interval is less than the minimum value of the second distance interval, and the first ambiguity is lower than the second ambiguity.

[0012] In this way, by setting distance ranges, the blur level can be dynamically adjusted according to different distance ranges, which can avoid the problem of increased power consumption caused by frequent adjustment of blur level.

[0013] In one implementation of the first aspect, the target application type includes a first application type and a second application type. When the distance between the viewer's eye and the display screen is fixed, the image corresponding to the target application of the first application type has a higher degree of blur than the image corresponding to the target application of the second application type. In other words, besides dynamically adjusting the image blur based on the viewer's eye distance, the image blur can also be dynamically adjusted in conjunction with the target application type, which can improve the accuracy of blur adjustment and achieve a more precise and effective eye-protection display effect.

[0014] In one implementation of the first aspect, the first application type is a video application, and the second application type is a reading application.

[0015] In one implementation of the first aspect, when the distance between the viewer's eyes and the display screen is fixed, the higher the ambient light level, the lower the image blur. In other words, besides dynamically adjusting the image blur based on the viewer's eyes, the image blur can also be adjusted in conjunction with ambient light level, which can improve the accuracy of blur adjustment and achieve a more precise and effective eye-protection display effect.

[0016] In one implementation of the first aspect, when the distance between the viewer's eyes and the display screen is fixed, if the ambient light intensity is greater than a preset illuminance threshold, the image blur level is zero. Thus, when the ambient light intensity is too strong, adjusting the image blur level has little effect on alleviating the user's myopia. Therefore, when the ambient light intensity is greater than the preset illuminance threshold, the image blur level can be left unchanged to reduce power consumption.

[0017] In one implementation of the first aspect, the method further includes: when a triggering condition is met, the electronic device acquires human eye feature data; the electronic device detects the human eye distance based on the human eye feature data; wherein the triggering condition includes one or more of the following: the defocus vision relief function is enabled, the distance between the user and the electronic device is greater than a preset distance, the ambient light intensity is within a preset range, the first interface is the interface of the target application of the electronic device, and the usage time of the electronic device after power-on is greater than a preset time. Thus, the electronic device only detects the human eye distance when the triggering condition is met, which avoids the problem of high power consumption caused by frequent detection of human eye distance.

[0018] In one implementation of the first aspect, when a triggering condition is met, human eye feature data is acquired, including: periodically acquiring a grayscale image of a face when the triggering condition is met; wherein the color of each pixel in the grayscale image of the face is represented by a single grayscale value; and the electronic device acquiring human eye feature data based on the grayscale image of the face. Thus, by acquiring human eye feature data from a grayscale image of the face, the power consumption caused by image computation can be reduced.

[0019] In one implementation of the first aspect, the electronic device includes a Sensorhub and an application processor (AP); when a triggering condition is met, acquiring human eye feature data includes: when the AP determines that the triggering condition is met, it sends a human eye detection command to the Sensorhub; in response to the human eye detection command, the Sensorhub acquires the human eye feature data; wherein, based on the human eye feature data, detecting the human eye distance includes: the Sensorhub reporting the human eye feature data to the AP; and the AP detecting the human eye distance based on the human eye feature data and Time-of-Flight (TOF) data.

[0020] In one implementation of the first aspect, the AP deploys a local service layer, which includes an intelligent sensing framework (ISF). The AP detects the distance to the human eye based on human eye feature data and TOF data, including: the AP detects the distance to the human eye through the ISF included in the native layer, based on human eye feature data and TOF data.

[0021] In one implementation of the first aspect, the AP also deploys an application layer, and the method further includes: the electronic device reporting the human eye distance to the application layer through the ISF included in the Native layer; and the AP's application layer adjusting the blur level of the image based on the human eye distance.

[0022] In a second aspect, an electronic device is provided, which has the functions described in any one of the first aspects above. These functions can be implemented by hardware or by hardware executing corresponding software. The hardware or software includes one or more modules corresponding to the aforementioned functions.

[0023] Thirdly, an electronic device is provided, comprising: a display screen, a memory, and one or more processors; the display screen is used to display images; the memory stores computer program code, the computer program code including computer instructions; when the computer instructions are executed by the processor, the electronic device performs the method described in the first aspect or any one of the first aspects.

[0024] Fourthly, a chip system is provided for use in an electronic device, the electronic device including one or more cameras; the chip system includes: at least one processor and an interface for receiving instructions and transmitting them to the at least one processor; the at least one processor executes instructions to cause the electronic device to perform the method described in any one of the first aspects.

[0025] Fifthly, a computer-readable storage medium is provided that stores instructions which, when executed on a computer, cause the computer to perform the method described in any one of the first aspects.

[0026] In a sixth aspect, a computer program product containing instructions is provided, which, when run on a computer, enables the computer to perform the method described in any one of the first aspects above.

[0027] The technical effects of any of the implementation methods in aspects two through six can be referenced from the technical effects of different implementation methods in aspect one, and will not be elaborated here. Attached Figure Description

[0028] Figure 1 is a schematic diagram of the defocusing principle provided in an embodiment of this application;

[0029] Figure 2 is a comparative schematic diagram of normal axial length and myopic axial length provided in an embodiment of this application;

[0030] Figure 3 is a schematic diagram illustrating the principle of myopia exacerbation provided in an embodiment of this application;

[0031] Figure 4 is a schematic diagram illustrating the principle of myopia defocusing provided in an embodiment of this application;

[0032] Figure 5 is a schematic diagram of a color difference principle provided in an embodiment of this application;

[0033] Figure 6 is a schematic diagram illustrating the principle of image edge blurring provided in an embodiment of this application;

[0034] Figure 7 is a schematic diagram illustrating the relationship between human eye distance and image blur level according to an embodiment of this application;

[0035] Figure 8 is a schematic diagram of the hardware structure of an electronic device provided in an embodiment of this application;

[0036] Figure 9 is a schematic diagram of the software framework of an electronic device provided in an embodiment of this application;

[0037] Figure 10 is a schematic diagram of an image adjustment process based on human eye distance provided in an embodiment of this application;

[0038] Figure 11 is a schematic diagram of another process for adjusting images based on human eye distance provided in an embodiment of this application;

[0039] Figure 12 is a schematic diagram of an interface for defocus vision relief provided in an embodiment of this application;

[0040] Figure 13 is a schematic diagram of another interface for defocus vision relief provided in an embodiment of this application;

[0041] Figure 14 is a schematic diagram of another interface for defocus vision relief provided in an embodiment of this application;

[0042] Figure 15 is a schematic diagram of another process for adjusting an image based on human eye distance provided in an embodiment of this application;

[0043] Figure 16 is a schematic diagram of human eye feature points provided in an embodiment of this application;

[0044] Figure 17 is a schematic diagram illustrating the principle of calculating human eye distance according to an embodiment of this application;

[0045] Figure 18 is a schematic diagram of a chip system provided in an embodiment of this application. Detailed Implementation

[0046] The technical solutions of the embodiments of this application are described below with reference to the accompanying drawings. In the description of the embodiments of this application, the terminology used in the following embodiments is for the purpose of describing specific embodiments only and is not intended to be a limitation of this application. As used in the specification and appended claims of this application, the singular expressions "a," "the," "the," "the," and "this" are intended to also include expressions such as "one or more," unless the context clearly indicates otherwise. It should also be understood that in the following embodiments of this application, "at least one" and "one or more" refer to one or more (including two). The term "and / or" is used to describe the relationship between related objects, indicating that three relationships can exist; for example, A and / or B can represent: A alone, A and B simultaneously, or B alone, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship.

[0047] References to "one embodiment" or "some embodiments" in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The term "connection" includes direct connections and indirect connections, unless otherwise stated. "First" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated.

[0048] In the embodiments of this application, the words "exemplarily" or "for example" are used to indicate examples, illustrations, or explanations. Any embodiment or design described as "exemplarily" or "for example" in the embodiments of this application should not be construed as being preferred or superior to other embodiments or designs. Specifically, the use of the words "exemplarily" or "for example" is intended to present the relevant concepts in a specific manner.

[0049] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the relevant principles involved in the embodiments of this application will be explained below with reference to the accompanying drawings.

[0050] As we understand it, when the human eye focuses on an image, the light reflected from the image passes through the eye's refractive system and forms an image on the retina. Normally, this reflected light focuses on a single point (called the imaging point). Under normal circumstances, this imaging point focuses on the retina, resulting in a clear image. Defocus occurs when the reflected light does not focus precisely on the retina, leading to a blurred image. This can be categorized into myopic defocus and hyperopic defocus. Myopic defocus occurs when the imaging point is located in front of the retina, while hyperopic defocus occurs when the imaging point is located behind the retina.

[0051] Referring to Figure 1, this is a schematic diagram illustrating the principle of defocusing according to an embodiment of this application. As shown in Figure 1, if the imaging point is focused in front of the retina, it is called myopic defocus. If the imaging point is focused behind the retina, it is called hyperopic defocus. Studies have shown that hyperopic defocus is a major cause of myopia progression. This is because the human eye has a self-regulating mechanism; if the imaging point is focused behind the retina for a long time, the human eye will "perceive" that the length of the axial length of the eye is insufficient to meet the user's daily visual needs, thereby stimulating the eyeball to grow laterally, making the eyeball longer. Referring to Figure 2, this is a schematic diagram comparing a normal eyeball and a myopic eyeball according to an embodiment of this application. As shown in Figure 2, the axial length of a normal eyeball is generally 24 millimeters (mm), while the axial length of a myopic eyeball is greater than 24 mm.

[0052] As shown in Figure 3, due to the elongation of the axial length of the eye, light reflected from the central area of ​​the image focuses in front of the retina after passing through the eye's refractive system (e.g., image point A). However, light reflected from the peripheral area of ​​the image (which can be understood as the image edge) focuses behind the retina due to the curvature of the eyeball, resulting in peripheral hyperopic defocus (e.g., image point B). Studies have shown that peripheral hyperopic defocus further stimulates axial growth, leading to increased axial length, which in turn worsens myopia.

[0053] It should be noted that image edges refer to the discontinuity of local characteristics in an image, that is, the boundary between adjacent regions. For example, if an image includes a "person" and a "background," the image edge refers to the boundary between the outline of the "person" and the "background." Similarly, if an image includes a "mountain" and a "lake / sea," the image edge refers to the boundary between the outline of the "mountain" and the outline of the "lake / sea." Based on this, the "image edge blurring" involved in the embodiments of this application refers to the relatively blurred boundary between adjacent regions of various elements in an image. Different degrees of image edge blurring will result in different degrees of overall image blurring; that is, blurred image edges will also blur the overall image. This will be explained uniformly here and will not be elaborated further below.

[0054] Based on this, this application provides an artificial intelligence (AI) defocusing technology that can alleviate the aggravation of myopia in users. Specifically, as shown in Figure 4, AI defocusing technology refers to changing the display effect of an image through an algorithm to simulate the principle of myopia defocusing. This causes the light reflected from the central area of ​​the image to focus on the retina after passing through the eye's refractive system, while the light from the peripheral area of ​​the image is focused in front of the retina after passing through the eye's refractive system. This avoids further elongation of the axial length of the eye caused by hyperopia defocusing in the peripheral area, thereby alleviating the aggravation of myopia in users.

[0055] In short, AI defocus technology images light reflected from the central area of ​​an image onto the retina normally, while imageing light reflected from the peripheral area of ​​the image in front of the retina, creating myopia defocus. By sensing this myopia defocus through retinal imaging, corresponding visual induction signals are generated to inhibit (or alleviate) axial elongation, thereby controlling the progression of myopia.

[0056] In this embodiment, the image edges can be blurred so that light from the peripheral areas of the image (i.e., the image edges) is focused in front of the retina after passing through the eye's refractive system. Myopia, as we understand it, refers to the symptom where a user cannot see distant objects clearly but can see near objects clearly. This is because, under static refractive conditions, distant objects cannot focus on the retina but focus in front of it, causing visual distortion and resulting in blurred distant objects. Based on this principle, and through reverse reasoning, by blurring the image edges, the user can see the central area of ​​the image clearly but not the peripheral areas, creating a visual experience similar to "looking into the distance." This utilizes the principle of myopia defocus; by blurring the image edges, light reflected from the peripheral areas of the image is focused in front of the retina. The retina, sensing the myopia defocus, generates corresponding visual induction signals to inhibit axial growth, thereby alleviating the progression of myopia without affecting the user's visual experience, and further achieving eye protection.

[0057] As an example, image edges can be blurred in the following two ways:

[0058] Method 1: Utilizing the principle of color difference

[0059] Chromatic aberration, also known as color difference, occurs when light of different wavelengths has different refractive indices as it passes through a lens. This causes the reflected light to appear as a color spot (i.e., diffusion) on the imaging surface after passing through the lens, resulting in a decrease in image quality, manifested as image blurring.

[0060] It is understood that in this embodiment, the refractive system of the eye is similar to a lens. Therefore, according to the principle of chromatic aberration, different wavelengths of light, after passing through the eye's refractive system, focus at different positions on the retina. For example, among red, yellow, green, and blue light, the wavelength of red light > the wavelength of yellow light > the wavelength of blue light > the wavelength of green light; conversely, the refractive index of red light < the refractive index of yellow light < the refractive index of blue light < the refractive index of green light. This results in red light focusing after the focal points of yellow, green, and blue light after passing through the eye's refractive system. For example, as shown in Figure 5, assuming the red light focuses exactly on the retina, then the yellow, green, and blue light focus in front of the retina, satisfying the principle of defocus in myopia.

[0061] In this embodiment, based on the principle of chromatic aberration, by presenting color changes at the image edges (such as blue-yellow, yellow-green, blue-green, or yellow-green-blue changes), the light reflected from the image edges, after passing through the eye's refractive system, will focus in front of the retina, resulting in blurred or distinct color edges at the image edges. In other words, by presenting color changes at the image edges using the chromatic aberration principle of method 1 described above, blurring of the image edges can be achieved.

[0062] Method 2: Image Blur Algorithm

[0063] Image blurring algorithms include, but are not limited to: Gaussian blur, box blur, bokeh bluer, iris blur, grainy blur, radial blur, and directional blur.

[0064] Taking Gaussian blur as an example, the blur radius can be adjusted to control the blurring effect at the edges of an image. The blur radius is a key parameter affecting the blurring effect, determining the degree of blurring at the image edges. In image processing, adjusting the blur radius value can increase or decrease the intensity of the blurring. For example, a larger blur radius produces a stronger blurring effect, while a smaller blur radius produces a weaker blurring effect. For instance, after image blurring processing, as shown in Figure 6, the light from the peripheral areas of the image, after passing through the eye's refractive system, can focus in front of the retina, satisfying the principle of defocusing in myopia.

[0065] In practical applications, by adjusting the blur radius, image edges can be quickly blurred. Furthermore, in image processing software, by adjusting the blur radius and selecting different modes (such as normal, edge-only, edge overlay, etc.), various blur effects can be achieved to meet different image display needs. Therefore, in this embodiment, method 2 can be used, for example, by adjusting the blur radius to flexibly adjust the degree of blurring at image edges to adapt to different user eye needs and alleviate the aggravation of myopia.

[0066] It should be noted that the distance at which the light reflected from an image focuses on the retina after passing through the eye's refractive system is inversely proportional to the distance between the eyes. In other words, the closer the eyes are, the more the reflected light will focus behind the retina, resulting in hyperopic defocus. As mentioned above, hyperopic defocus promotes axial elongation, thus increasing the likelihood of myopia or worsening existing myopia when the eyes are close together. In this embodiment, eye distance refers to the distance between the user's eyes and the image displayed on the screen (or, more specifically, the distance between the eyes and the screen). Specifically, eye distance can be the distance between the eyes and the time-of-flight (TOF) camera of the mobile phone, which will not be elaborated further below. For a description of the ASC camera, please refer to the following embodiments, which will not be repeated here.

[0067] Based on this, this application provides a method for adjusting an image based on human eye distance. This method dynamically adjusts the blurring degree of image edges according to the human eye distance, achieving a more precise and effective eye-protection display effect and alleviating the aggravation of myopia in users. Specifically, when the human eye distance is a first distance, the image edges exhibit a first degree of blurring; when the human eye distance is a second distance, the image edges exhibit a second degree of blurring. The first distance and the second distance are different, and the first degree of blurring is different from the second degree of blurring.

[0068] Optionally, the closer the viewer is, the less blurred the image edges; the farther the viewer is, the more blurred the image edges. In other words, the distance to the viewer is directly proportional to the blurriness of the image edges. In real-world scenarios, the closer the viewer is, the clearer the vision; conversely, the farther the viewer is, the more blurred the vision. Therefore, by making the distance to the viewer proportional to the blurriness of the image edges, the closer the viewer is, the less blurred the image becomes. Users will not noticeably perceive image blurriness, thus, without affecting the user's visual experience, at close range, by adaptively adjusting the blurriness of the image edges, the light reflected from the image edges is focused in front of the retina, thus mitigating the worsening of myopia. Similarly, the farther the viewer is, the more blurred the image becomes, which is consistent with the user's actual visual experience (in reality, the farther the viewer is, the more blurred the vision). Therefore, without affecting the user's visual experience, at far range, by enhancing the blurriness of the image edges, more light reflected from the image edges is focused in front of the retina, mitigating the worsening of myopia. In this way, the blurring of image edges can be adjusted according to different human eye distances, thereby meeting the visual needs of users at different eye distances and achieving a more accurate and effective eye-protection display effect, thus alleviating the aggravation of myopia.

[0069] It's important to note that in real-world scenarios, the image seen by the human eye is formed by reflected light entering the retina. However, for images displayed on a screen, the image seen by the human eye is formed by light emitted from the screen itself entering the retina. Therefore, when the viewer is at a distance, enhancing the blurring of image edges can cause more of the emitted light from the image edges to focus in front of the retina, thus mitigating the worsening of myopia. This explanation is provided here and will not be repeated below.

[0070] The following section provides a detailed description of the technical solution provided in this application, using the example of adjusting the blur radius of the image edge to control the blur level of the icon edge.

[0071] In this embodiment, the closer the human eye is, the smaller the blur radius of the image edge, and the lower the degree of blurring at the image edge. Conversely, the farther the human eye is, the larger the blur radius of the image edge, and the higher the degree of blurring at the image edge. For example, when the human eye is 20 centimeters (cm), the blur radius of the image edge can be 6 (unit: pixels); when the human eye is 21cm, the blur radius of the image edge can be 5.9, etc. (unit: pixels), etc., without limitation here. It can be seen that as the human eye distance increases, the blur radius of the image edge decreases accordingly. However, frequently adjusting the blur radius of the image edge will further increase the device power consumption.

[0072] To reduce device power consumption, alternatively, different distance intervals can be set, each corresponding to a blur radius. The rules for setting different distance intervals are not limited and should be based on actual needs. For example, different distance intervals may include a first distance interval and a second distance interval. For instance, when the human eye distance is in the first distance interval, the blur radius of the image edge is the first radius, and the image edge exhibits a first degree of blur. When the human eye distance is in the second distance interval, the blur radius of the image edge is the second radius, and the image edge exhibits a second degree of blur. The maximum value in the first distance interval is less than the minimum value in the second distance interval; that is, the distance value in the first distance interval is less than the distance value in the second distance interval. Therefore, the first radius is less than the second radius, and the first degree of blur is less than the second degree of blur.

[0073] Optionally, different distance intervals can also include a third distance interval. For example, when the human eye distance is within the third distance interval, the blur radius of the image edge is the third radius, and the image edge exhibits a third degree of blur. The minimum value of the third distance interval is greater than or equal to the maximum value of the second distance interval, meaning the distance value of the third distance interval is greater than the distance value of the second distance interval; therefore, the third radius is greater than the second radius, and the third degree of blur is higher than the third degree of blur.

[0074] For example, as shown in Figure 7, when the distance between the human eye and the image is L1 (a distance value in the first distance interval), the blur radius of the image edge is R1 (i.e., the first radius). When the distance between the human eye and the image is L2 (a distance value in the second distance interval), the blur radius of the image edge is R2 (i.e., the second radius). When the distance between the human eye and the image is L3 (a distance value in the third distance interval), the blur radius of the image edge is R3 (i.e., the third radius). Wherein, L1 < L2 < L3, and R1 < R2 < R3. It can be seen that the closer the distance between the human eye and the image edge, the smaller the blur radius; the farther the distance between the human eye and the image edge, the larger the blur radius. For example, the image shown in Figure 7 includes a "bridge" and a "background". In this embodiment, the blur radius of the image edge is represented by the thickness of the "lines" in Figure 7, which is only an example of this application and does not constitute a limitation of this application. The specific display effect is subject to actual conditions and is not listed here.

[0075] It should be noted that the first, second, and third distance intervals mentioned above can be set according to actual needs, and the number of times is not limited. As long as the size relationship of the corresponding distance values ​​of the different intervals can be satisfied, they all fall within the protection scope of this application embodiment. For example, the first distance interval can be (0, 20] cm, the second distance interval can be (20, 50] cm, and the third distance interval can be 50 cm or more.

[0076] In the above embodiments, the blur radius of the image edges is dynamically adjusted based on the distance to the user's eyes. In some optional embodiments of this application, the blur radius of the image edges can also be dynamically adjusted according to the application scenario. Optionally, the application scenario can include video scenarios and reading scenarios. Since users have higher visual demands in video and reading scenarios, which are highly immersive scenarios, dynamically adjusting the blur radius of the image edges in video and reading scenarios, compared to adjusting the blur radius of the image edges in all scenarios, can not only adapt to the user's visual needs and achieve more precise and effective eye protection requirements, alleviating the aggravation of myopia, but also reduce power consumption.

[0077] Optionally, for the same distance range, the blur radius of image edges in video scenarios is larger than that in reading scenarios. This is because in video scenarios, users' eye strain is more likely to exacerbate myopia. Therefore, in video scenarios, the blur radius of image edges can be set larger, thereby achieving a more accurate and effective eye-protection display effect and alleviating the aggravation of users' myopia.

[0078] It should be noted that the main reasons why video-based scenarios are more likely to exacerbate myopia include the following three factors:

[0079] 1. When watching videos, the distance between the eyes and the screen is closer: When watching videos, especially short videos, users often unconsciously bring their eyes closer to the screen to obtain a clearer visual effect. This close-range viewing habit increases the burden on the eyes, leading to excessive fatigue of the eye muscles, thereby increasing the risk of myopia.

[0080] 2. Extended viewing time: Video content is generally more engaging than reading; its vibrant colors and dynamic visuals are more likely to capture users' attention, leading to longer viewing times. Prolonged screen time keeps the eyes under constant strain, increasing the risk of nearsightedness.

[0081] 3. Eye habits: Compared to reading, users often adopt a more relaxed posture when watching videos, which may not be conducive to eye relaxation and rest. In addition, the rapid switching of video content may also put extra strain on the eyes.

[0082] Optionally, the image described above can be the image displayed after the electronic device launches the target application. Based on this, the application scenario can be distinguished according to the application type of the target application. For example, if the target application type is video, then the application scenario can be a video scenario. If the target application type is reading, then the application scenario can be a reading scenario. That is, for the same distance interval, the blur radius of the image edge corresponding to the video application type is greater than the blur radius of the image edge corresponding to the reading application type.

[0083] It should be noted that the video applications installed on electronic devices can include various types, and similarly, the reading applications installed on electronic devices can also include various types. This application does not limit the application names of video applications or reading applications; these applications can be system applications or third-party applications, depending on the actual application, and will not be listed here.

[0084] In some alternative embodiments of this application, the blur radius of the image edges can be dynamically adjusted according to the ambient light level. For example, for the same distance range, the lower the ambient light level, the larger the blur radius of the image edges, and the higher the degree of blurring. Conversely, the higher the ambient light level, the smaller the blur radius of the image edges, and the lower the degree of blurring. This is because different ambient light levels affect the degree of pupil opening in the human eye, indirectly affecting the human eye's perception of image blur.

[0085] For example, the lower the ambient light, the larger the pupil, the more light enters the eye, and the stronger the perception of the image effect. Therefore, for the same distance range, when the ambient light is lower, because the pupil is larger, the blur radius of the image edge can be adjusted to be larger. This allows more light reflected from the image edge to enter the eye and focus in front of the retina, thereby further mitigating the aggravation of myopia.

[0086] Correspondingly, the higher the ambient light level, the smaller the pupil, the less light enters the eye, and the lower the perceived image quality. Therefore, for the same distance range, when the ambient light level is higher, the smaller the pupil, the smaller the blur radius of the image edges can be adjusted. This can protect the eye from excessive stimulation while mitigating the worsening of myopia.

[0087] In environments with strong ambient light, the human pupil constricts rapidly. This is a natural physiological response designed to reduce the amount of light entering the eye, thus protecting it from damage. In practice, users may squint or close their eyes in bright light. This significantly reduces the likelihood of eye strain, so in this scenario, the blur radius of the image edges can be left unchanged to reduce power consumption.

[0088] For example, within any distance interval, when the ambient light intensity is greater than a preset illuminance threshold, the blur radius of the image edge is zero, meaning the blurriness of the image edge is zero. It should be noted that the specific value of the preset illuminance threshold is not limited; it is determined by the actual setting. For instance, the preset illuminance threshold can be greater than or equal to 1000 lux, such as 1000 lux, 1500 lux, 2000 lux, etc., and is not limited here.

[0089] It should be noted that, in this embodiment, in addition to dynamically adjusting the blur radius of the image edge based on the distance to the human eye, the blur radius of the image edge can also be dynamically adjusted based on other factors besides the application scenario and ambient light intensity to adapt to different user eye needs. For example, the blur radius of the image edge can also be dynamically adjusted based on the duration of eye use and eye posture, etc., which will not be listed here.

[0090] In summary, the solution adopted in this application can dynamically adjust the blur radius of image edges based on the user's eye distance to present different degrees of blur at the image edges. This achieves a more precise and effective eye-protection display effect, alleviating the aggravation of myopia in users. Furthermore, based on the user's eye distance, factors such as application scenarios and ambient light levels can also be combined to dynamically adjust the blur radius of image edges to meet different user eye needs. This not only protects the eyes from strong light stimulation and reduces power consumption, but also achieves a more precise and effective eye-protection effect, further alleviating the aggravation of myopia in users.

[0091] In the embodiments of this application, the specific implementation method for dynamically adjusting the blur radius of image edges based on factors such as eye distance, application scenario, and ambient light intensity can be set according to actual needs. As long as the above adjustment scheme can be satisfied, it falls within the protection scope of the embodiments of this application. As an optional embodiment of this application, the following provides a relationship between factors such as eye distance, application scenario, and ambient light intensity and the blur radius of image edges. This relationship can be stored in an electronic device in the form of a table or array. The following is a simple example of this relationship in tabular form. For example, the relationship can be as shown in Table 1 below.

[0092] Table 1

[0093] As shown in Table 1 above, the closer the human eye is, the smaller the blur radius of the image edge. The farther the human eye is, the larger the blur radius of the image edge. When the ambient light level is greater than 1000 lux, the blur radius of the image edge is 0 for both video and reading scenarios at different human eye distances. Optionally, as shown in Table 1, when the ambient light level is between 500 and 1000 lux, the blur radius of the image edge is the same for different human eye distances in reading scenarios, which is 1. Since the image displayed on the screen is generally static in reading scenarios, i.e., there are no rapid image transitions, the blur radius of the image edge can be appropriately adjusted when the ambient light level is between 500 and 1000 lux. This can alleviate the aggravation of myopia without affecting the user's visual experience.

[0094] The above embodiments mainly introduce some optional schemes for dynamically adjusting the blur radius of image edges, and do not constitute a limitation on the embodiments of this application. In practical applications, the above schemes can be appropriately adjusted according to specific circumstances, which will not be listed one by one here.

[0095] The following detailed description of the specific implementation of the technical solution provided in this application, using schematic diagrams of the hardware and software structures of the electronic device, is provided in conjunction with these diagrams.

[0096] For example, the aforementioned electronic devices can be mobile phones, tablets, laptops, ultra-mobile personal computers (UMPCs), handheld computers, netbooks, personal digital assistants (PDAs), wearable electronic devices, in-vehicle devices (also known as vehicle infotainment systems), virtual reality devices, etc. This application embodiment does not impose any limitations on these. For instance, the aforementioned electronic device can specifically be a mobile phone. The mobile phone may have the function of detecting the distance to the human eye, implementing the image adjustment method based on the distance to the human eye provided in this application embodiment.

[0097] Figure 8 shows a specific structural form of the mobile phone 100 provided in an embodiment of this application.

[0098] The mobile phone 100 may include a processor 110, an external memory interface 120, an internal memory 121, a universal serial bus (USB) interface 130, a charging management module 140, a power management module 141, a battery 142, an antenna 1, an antenna 2, a mobile communication module 150, a wireless communication module 160, an audio module 171, a speaker 170A, a receiver 170B, a microphone 170C, a headphone jack 170D, a sensor module 180, buttons 190, a motor 191, an indicator 192, a camera 193, a display screen 194, and a subscriber identification module (SIM) card interface 195, etc.

[0099] Processor 110 may be a general-purpose central processing unit (CPU), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits used to control the execution of the program according to the present application. In a specific implementation, as one embodiment, processor 110 may also include multiple CPUs, and processor 110 may be a single-core processor or a multi-core processor. Here, processor may refer to one or more devices, circuits, or processing cores used to process data (e.g., computer program instructions).

[0100] Processor 110 may include one or more processing units, such as: application processor (AP), sensorhub, graphics processing unit (GPU), image signal processor (ISP), controller, memory, video codec, digital signal processor (DSP), baseband processor, and / or neural network processing unit (NPU), etc. Different processing units may be independent devices or integrated into one or more processors.

[0101] In this embodiment, the AP can be used to detect the distance to the human eye and dynamically adjust the blur radius of the image edge based on the distance to the human eye. The Sensorhub can be used to detect human eye feature information and transmit the human eye feature information to the application processor so that the AP can detect the distance to the human eye based on the human eye feature information.

[0102] Sensorhubs have different names depending on the chip platform they are used on. For example, a sensorhub can also be called a smart sensor hub, a system coprocessor, etc., and this is not limited here. Optionally, in the embodiments of this application, the sensorhub can be located in an application digital signal processor (ADSP), that is, the sensorhub processor is placed in a separate ADSP. In this way, when the ADSP processes audio data, it can also process the sensorhub data, thereby enabling the processing of corresponding data while the main processor (such as the CPU) is in sleep mode, thus reducing power consumption.

[0103] The communication between the ADSP and Sensorhub relies on the QUALCOMM messaging interface (QMI) technology. QMI is a multi-core communication technology developed based on a shared memory mechanism, used for communication between the ADSP and the application processor. This communication mechanism allows the ADSP to communicate with the application processor, enabling efficient data exchange and instruction transfer between them.

[0104] In this embodiment, detecting human eye feature information via Sensorhub allows for detection even when the application processor is in sleep mode, thus reducing power consumption. It should be noted that this embodiment can also detect human eye feature information via an access point (AP), for example, by having the AP activate the main camera to capture RGB images and then detecting human eye feature information based on those images. Since the main camera captures RGB images, which contain a lot of color information, the power consumption during eye feature detection would be higher. Therefore, this embodiment utilizes Sensorhub to activate the main camera to capture RGB images and then detects human eye feature information based on those images, effectively reducing power consumption.

[0105] The controller can serve as the central nervous system and command center of the mobile phone 100. Based on the instruction operation code and timing signals, the controller generates operation control signals to control the fetching and execution of instructions.

[0106] The processor 110 may also include a memory for storing instructions and data. In some embodiments, the memory in the processor 110 is a cache memory. This memory can store instructions or data that the processor 110 has just used or that are used repeatedly. If the processor 110 needs to use the instruction or data again, it can retrieve it directly from the memory. This avoids repeated accesses, reduces the waiting time of the processor 110, and thus improves the efficiency of the system.

[0107] In some embodiments, the processor 110 may include one or more interfaces. Interfaces may include an inter-integrated circuit (I2C) interface, an inter-integrated circuit sound (I2S) interface, a pulse code modulation (PCM) interface, a universal asynchronous receiver / transmitter (UART) interface, a mobile industry processor interface (MIPI), a general-purpose input / output (GPIO) interface, a subscriber identity module (SIM) interface, and / or a universal serial bus (USB) interface, etc.

[0108] It is understood that the interface connection relationships between the modules illustrated in the embodiments of this application are merely illustrative and do not constitute a structural limitation on the mobile phone 100. In other embodiments, the mobile phone 100 may also adopt different interface connection methods or combinations of multiple interface connection methods as described in the above embodiments.

[0109] Antennas 1 and 2 are used to transmit and receive electromagnetic wave signals. Each antenna in mobile phone 100 can be used to cover one or more communication frequency bands. Different antennas can also be reused to improve antenna utilization. For example, antenna 1 can be reused as a diversity antenna for a wireless local area network. In other embodiments, the antennas can be used in conjunction with a tuning switch.

[0110] The mobile communication module 150 can provide solutions for wireless communication applications including 2G / 3G / 4G / 5G on the mobile phone 100. The mobile communication module 150 may include at least one filter, switch, power amplifier, low noise amplifier (LNA), etc. The mobile communication module 150 can receive electromagnetic waves via the antenna 1, and perform filtering, amplification, and other processing on the received electromagnetic waves before transmitting them to the modem processor for demodulation. The mobile communication module 150 can also amplify the signal modulated by the modem processor and convert it into electromagnetic waves for radiation via the antenna 1. In some embodiments, at least some functional modules of the mobile communication module 150 may be housed in the processor 110. In some embodiments, at least some functional modules of the mobile communication module 150 and at least some modules of the processor 110 may be housed in the same device.

[0111] The wireless communication module 160 can provide solutions for wireless communication applications on the mobile phone 100, including wireless local area networks (WLAN) (such as wireless fidelity (Wi-Fi) networks), Bluetooth (BT), global navigation satellite system (GNSS), frequency modulation (FM), near field communication (NFC), and infrared (IR) technologies. The wireless communication module 160 can be one or more devices integrating at least one communication processing module. The wireless communication module 160 receives electromagnetic waves via antenna 2, performs frequency modulation and filtering of the electromagnetic wave signals, and sends the processed signal to processor 110. The wireless communication module 160 can also receive signals to be transmitted from processor 110, perform frequency modulation and amplification, and convert them into electromagnetic waves for radiation via antenna 2.

[0112] The external storage interface 120 can be used to connect an external storage card, such as a Micro SD card, to expand the storage capacity of the mobile phone 100. The external storage card communicates with the processor 110 through the external storage interface 120 to perform data storage functions. For example, music, video, and other files can be saved on the external storage card.

[0113] The internal memory 121 can be used to store computer executable program code, which includes instructions. The processor 110 executes various functional applications and data processing of the mobile phone 100 by running the instructions stored in the internal memory 121. The internal memory 121 may include a program storage area and a data storage area. The program storage area may store the operating system, at least one application program required for a function (such as sound playback, image playback, etc.), etc. The data storage area may store data created during the use of the mobile phone 100 (such as audio data, phonebook, etc.). Furthermore, the internal memory 121 may include high-speed random access memory and may also include non-volatile memory, such as at least one disk storage device, flash memory device, universal flash storage (UFS), etc.

[0114] The mobile phone 100 implements display functions through a GPU, a display screen, and an application processor. The GPU is a microprocessor for image processing, connected to the display screen 194 and the application processor. The GPU is used to perform mathematical and geometric calculations and for graphics rendering. The processor 110 may include one or more GPUs, which execute program instructions to generate or modify display information.

[0115] Display screen 194 is used to display images, videos, etc. Display screen 194 includes a display panel. The display panel can be a liquid crystal display (LCD), an organic light-emitting diode (OLED), an active-matrix organic light-emitting diode (AMOLED), a flexible light-emitting diode (FLED), a Mini-LED, a Micro-OLED, a quantum dot light-emitting diode (QLED), etc.

[0116] The mobile phone 100 can achieve shooting functions through ISP, camera 193, video codec, GPU, display 194 and application processor.

[0117] The ISP (Image Signal Processor) is used to process data fed back from the camera 193. For example, when taking a picture, the shutter is opened, and light passes through the lens and is transmitted to the camera's photosensitive element. The light signal is converted into an electrical signal, and the camera's photosensitive element transmits the electrical signal to the ISP for processing, transforming it into an image visible to the naked eye. The ISP can also perform algorithmic optimization on image noise, brightness, color, etc. The ISP can also optimize parameters such as exposure and color temperature of the shooting scene. In some embodiments, the ISP can be set in the camera 193.

[0118] Camera 193 is used to capture still images or videos. An object is projected onto a photosensitive element by generating an optical image through the lens. The photosensitive element can be a charge-coupled device (CCD) or a complementary metal-oxide-semiconductor (CMOS) phototransistor. The photosensitive element converts the light signal into an electrical signal, which is then passed to an ISP for conversion into a digital image signal. The ISP outputs the digital image signal to a DSP for processing. The DSP converts the digital image signal into image signals in standard RGB, YUV, or other formats. In some embodiments, mobile phone 100 may include one or N cameras 193, where N is a positive integer greater than 1.

[0119] The electronic device may include multiple cameras; for example, the multiple cameras may include a front-facing camera and a rear-facing camera. The front-facing camera is used to capture images of the user, while the rear-facing camera is used to capture images of the subject being photographed. Optionally, in this embodiment, the front-facing camera may include an always-sensing camera (ASC). The ASC camera is mainly used to capture grayscale images of the face and transmit the captured grayscale images to Sensorhub, where Sensorhub detects eye feature information based on the grayscale images. A grayscale image is an image that contains only brightness information and no color information, with its brightness continuously changing from dark to bright. Compared to the original color image, a grayscale image does not contain color information, thus greatly reducing the amount of information in the grayscale image and the computational load of image processing, facilitating subsequent calculations. Specific implementation methods for the ASC camera to capture grayscale images can be found in the relevant descriptions in the following embodiments, and will not be repeated here.

[0120] Optionally, the ASC camera is mainly used to acquire grayscale images. Grayscale images contain less information, which reduces the computational load for image processing, thus enabling low-power image processing. In this embodiment, functions such as smart code recognition, air gestures, face-sensing screen rotation, eye tracking, and gaze-based screen-off can also be implemented based on the grayscale images acquired by the ASC camera.

[0121] It is understood that the structures illustrated in the embodiments of the present invention do not constitute a specific limitation on the mobile phone 100. In other embodiments of this application, the mobile phone 100 may include more or fewer components than illustrated, or combine some components, or split some components, or have different component arrangements. The illustrated components may be implemented in hardware, software, or a combination of software and hardware.

[0122] The methods described in the following embodiments can all be implemented in a mobile phone 100 having the above-described hardware structure.

[0123] The software system of the aforementioned mobile phone 100 can adopt a layered architecture, event-driven architecture, microkernel architecture, microservice architecture, or cloud architecture. The following embodiments of this application use a layered architecture as an example to exemplify the software structure of the mobile phone 100.

[0124] Figure 9 is a software structure block diagram of the mobile phone 100 provided in the embodiment of this application.

[0125] A layered architecture divides software into several layers, each with a clear role and function. Layers communicate with each other through software interfaces. In some embodiments, the software system of mobile phone 100 is divided from top to bottom into: Application Layer, Application Framework Layer, Native Layer, Hardware Abstraction Layer (HAL), Sensorhub, etc. It should be understood that the layered architecture shown in Figure 9 is only an example; in actual implementation, the layered architecture may include more or fewer layers. For example, system libraries may be included between the Application Framework Layer and the Hardware Abstraction Layer. For ease of description, the software structure diagram shown in Figure 9 also includes the hardware of mobile phone 100, such as an ASCII camera.

[0126] In this embodiment of the application, as shown in FIG9, the application layer, application framework layer, local service layer and hardware abstraction layer can be deployed on the AP side of the mobile phone 100, and the AP runs relevant instructions to perform the functions required by the above layers.

[0127] The application layer can include a user interface layer and a logic layer. The user interface layer includes various applications (APPs) installed on the phone. For example, the user interface layer can include system applications such as camera, gallery, calendar, call, map, navigation, Bluetooth, music, and SMS. Of course, the user interface layer can also include frequently used third-party applications, such as video applications and reading applications, which will not be elaborated here. The user interface layer is not shown in Figure 9; the actual application will be the referenced reference.

[0128] The logic layer may include a series of application packages (APKs). For example, as shown in Figure 9, the logic layer may include a display engine, which is used to implement image rendering and display. Exemplarily, in this embodiment, as shown in Figure 9, the display engine may include a condition detection module and an image display module. The condition detection module is used to detect the triggering conditions for initiating human eye distance detection, thereby starting / stopping human eye distance detection. The image display module is used to dynamically adjust the blur radius of the image edges based on the human eye distance reported from the underlying layer (such as the local service layer), so that the image edges present different blur effects, alleviating the aggravation of the user's myopia.

[0129] Optionally, the condition detection module is also used to add an eye distance fence (EDF) to the underlying layer (such as through the application framework layer, local service layer, or hardware abstraction layer) to Sensorhub when a trigger condition is detected, to instruct eye distance detection to be performed. In this embodiment, the eye distance fence can be understood as an instruction to instruct eye distance detection, and therefore the eye distance fence can also be called an eye distance detection instruction.

[0130] Correspondingly, the condition detection module is also used to delete the added eye distance fence when the triggering condition is not met.

[0131] The application framework layer provides the application programming interface (API) and programming framework for the application layer. The application framework layer includes some predefined functions.

[0132] Optionally, the application framework layer may include a perception platform (or intelligent platform). The perception platform may employ an awareness mechanism to implement the functions required by the application framework layer in this embodiment. Here, awareness refers to a design pattern or concept used to improve the flexibility and scalability of an application. Awareness allows applications or framework components to perceive certain states or conditions and take corresponding actions based on these states or conditions. In this embodiment, the perception platform connects the upper layer (such as the display engine) and the lower layer (such as the local service layer), providing the meta-capability for human eye distance detection, sending instructions to the lower layer to add / delete human eye distance fences, and reporting human eye distance to the upper layer so that the upper layer (such as the display engine) can dynamically adjust the blur radius of image edges based on the human eye distance.

[0133] For example, as shown in Figure 9, the perception platform in the application framework layer includes a perception framework and an eye distance fence plugin. The perception framework provides the perception capability for eye distance fences. The perception framework can connect to / disconnect from the intelligent sensor fusion (ISF) in the local service layer via a software development kit (SDK). Once the perception framework is successfully connected to the ISF, it can call preset SDK interfaces to add / remove eye distance fences to the ISF.

[0134] The eye-distance fence plugin provides eye-distance fence capabilities, supporting eye-distance fence lifecycle management, client management, and eye-distance reporting.

[0135] The local service layer is a code layer written in C / C++, located below the application framework layer. The local service layer can directly use C / C++ code and interact directly with lower layers (such as the hardware abstraction layer), thereby achieving higher performance and lower resource consumption.

[0136] Optionally, the local service layer includes the ISF (Integrated Service Provider). The ISF establishes communication connections with the application framework layer and the AO (Always-on-Service) service to provide functions such as adding / deleting eye distance fences, activating the time-of-flight (TOF) camera, and detecting eye distance based on eye feature data and TOF data output by the TOF camera. For example, as shown in Figure 9, the ISF includes an eye distance fence management module, a TOF camera management module, and an eye distance detection module. The eye distance fence management module manages eye distance fences, such as adding / deleting them. The TOF camera management module activates the TOF camera to output TOF data. The eye distance detection module detects eye distance based on the eye feature data reported from the underlying layer and the TOF data output by the TOF camera.

[0137] It should be noted that in this embodiment, the ASC camera and the TOF camera are different cameras. The ASC camera is used to acquire grayscale images of the face, while the TOF camera is used to measure the depth information of the image. The TOF camera can include a direct time-of-flight (dTOF) camera and an indirect time-of-flight (iTOF) camera. Optionally, the TOF camera can be an iTOF camera, and the TOF data can be iTOF data.

[0138] The AO service provides a data interface for communication between the Hardware Abstraction Layer (HAL) and the ISF. For example, the AO service provides an interface for adding / removing eye distance fences to the HAL; and it also provides an interface for reporting eye feature data to the ISF.

[0139] The Hardware Abstraction Layer (HAL) provides a unified interface for upper-layer applications, shielding them from the specific implementation details of the hardware drivers in Sensorhub. Upper-layer applications can implement corresponding functions by calling the interfaces provided by the HAL without needing to know the specific implementation of the Sensorhub hardware drivers. In other words, the HAL is the interface layer between Sensorhub and the hardware, used to abstract the hardware. For example, as shown in Figure 9, the HAL includes the Eye Distance Service (HAL). The HAL interacts with Sensorhub to add / remove eye distance fences. The HAL also interacts with upper layers (such as the local service layer) to report eye feature data.

[0140] Sensorhub resides below the Hardware Abstraction Layer (HAL), acting as a layer between hardware and software. For example, as shown in Figure 9, Sensorhub includes an eye distance driver (also known as a hiaon driver). This driver resides within Sensorhub, which is part of the ADSP; therefore, it can be understood that the eye distance driver is located within the ADSP. The eye distance driver is used to manage eye distance fences and detect eye feature data. For example, the eye distance driver in Sensorhub includes an eye distance fence framework and an eye feature detection module. Upon receiving an eye distance fence, the eye distance fence framework adds the fence to itself and notifies the eye feature detection module. For example, Sensorhub also includes an ASC camera driver, used to drive the ASC camera to periodically acquire grayscale images. For instance, the eye feature detection module initiates the ASC camera driver. After the ASC camera driver starts, it drives the ASC camera to periodically acquire grayscale images and report the grayscale images to the human eye distance detection module, which then detects human eye feature data based on the grayscale images.

[0141] In this embodiment, the software block diagram shown in Figure 9 can be applied to different chip platforms. Different chip platforms and different levels (or modules) can call different software interfaces to achieve communication and interaction. This embodiment does not limit this. The following description, in conjunction with the software block diagram shown in Figure 9, illustrates the interaction interfaces for communication and interaction between different levels and modules, as shown in Figure 10. It should be understood that the interface names shown in Figure 10 are merely examples and do not constitute a limitation of this application. Of course, in practical applications, the interfaces can be adapted to the actual scenario (such as the actual chip platform used), or other suitable interfaces can be used to achieve communication and interaction between different levels.

[0142] For example, as shown in Figure 10, the display engine can communicate and interact with the perception platform through a preset SDK interface (e.g., the awareness_SDK interface). The perception platform can communicate and interact with the ISF through a preset ISF interface (e.g., the ISF_JNI interface). The ISF can communicate and interact with the AO service through the Android Interface Definition Language (AIDL). The AO service can communicate and interact with the human eye distance service HAL through a preset HAL interface. The human eye distance service HAL can communicate and interact with the human eye distance driver through the QMI interface. The human eye distance driver can communicate with the ASC camera driver through the QMI interface.

[0143] It should be noted that Figure 10 only shows one example of the interaction interface between the various layers in the above software block diagram. The communication and interaction between the modules in each layer can be based on the interaction interface provided by each layer. For example, the condition detection module and image display module of the display engine in the application layer can communicate and interact using the preset APK interface provided by the application layer. Correspondingly, the perception framework and human eye distance fence plugin of the perception platform in the application framework layer can communicate and interact using the preset API interface provided by the application framework layer. The specific interaction method depends on the actual situation and will not be elaborated here.

[0144] As an example, referring to the software block diagram shown in Figure 9 and the interactive interface shown in Figure 10, the general process of the technical solution provided in this application embodiment will be described. For instance, the display engine can call a preset SDK interface to send an eye distance fence to the perception platform. This eye distance fence can be understood as an instruction (or a message) to instruct the detection of eye distance. For example, the condition detection module in the display engine sends an eye distance fence to the perception platform when it detects that a trigger condition is met. A description of the trigger condition can be found in the following embodiments, and will not be repeated here.

[0145] The perception framework of the perception platform is used to detect eye distance fences. After the perception framework detects an eye distance fence, it notifies the eye distance fence plugin. On one hand, the eye distance fence plugin supports the lifecycle management of the eye distance fence and distributes the eye distance fence to the underlying layer. For example, the eye distance fence plugin calls a preset ISF interface to distribute the eye distance fence to the local service layer. On the other hand, after receiving the eye distance information, the eye distance fence plugin reports the eye distance to the upper layer. For example, the eye distance fence plugin calls a preset SDK interface to report the eye distance to the image display module of the display engine, so that the image display module can dynamically adjust the blur radius of the image edges based on the eye distance.

[0146] Accordingly, after receiving the eye distance fence, the local service layer performs two main functions: First, it manages the eye distance fence using its ISF (In-Service Frame). Second, it activates the TOF (Time-of-Flight) camera to output TOF data. For example, the eye distance fence management within the ISF can be used to manage the eye distance fence. Based on the received eye distance fence, it determines whether eye distance detection can be initiated. Therefore, eye distance fence management can be managed through the TOF camera, activating the TOF camera and outputting TOF data. Third, the local service layer's ISF is also used to combine TOF data and eye feature data to detect eye distance. The eye feature data is reported by the underlying layer (e.g., Sensorhub), as detailed in the following embodiments, which will not be elaborated upon here.

[0147] Correspondingly, after receiving the eye distance fence, the local service layer can also use the AO service to call AIDL to send the eye distance fence to the eye distance service HAL. Upon receiving the eye distance fence, the eye distance service HAL calls the QMI interface to send the eye distance fence to Sensorhub. Then, after receiving the eye distance fence, Sensorhub uses it for both management of the eye distance fence and detection of eye feature data. For example, the eye distance driver in Sensorhub includes an eye distance fence framework and an eye feature detection module. The eye distance fence framework, upon receiving the eye distance fence, adds it to the framework and notifies the eye feature detection module. Then, the eye feature detection module calls the QMI interface to start the ASC camera driver. After starting, the ASC camera driver periodically acquires grayscale images and reports them to the eye distance detection module. For example, grayscale images captured by the ASC camera are reported to the human eye distance detection module by calling the QMI interface through the ASC camera driver.

[0148] Correspondingly, the eye distance detection module detects eye feature data based on the grayscale image and reports this data to the eye distance service HAL via the QMI interface. Upon receiving the eye feature data, the eye distance service HAL calls a preset HAL interface to report the data to the local service layer's ISF via the local service layer's AO service. Then, the ISF's eye distance detection module combines the TOF data and the eye feature data to detect the eye distance. After obtaining the eye distance, the ISF's eye distance detection module calls a preset ISF interface to report it to the eye distance fence plugin in the perception platform. The perception platform's eye distance fence plugin calls a preset SDK interface to report the eye distance to the image display module in the display engine. Upon receiving the eye distance, the image display module dynamically adjusts the blur radius of the image edges based on the eye distance.

[0149] In the following embodiments, the communication process between the various modules of the technical solution of this application is described with reference to the software block diagram shown in Figure 9 above. For example, as shown in Figure 11, the communication process between the various modules may include the following steps.

[0150] Step 1: The phone's display engine periodically adds eye distance fences.

[0151] For example, the phone's display engine periodically adds eye distance fences to the eye distance driver. This can be achieved through the perception platform, ISF, AO service, and HAL (Hand Eye Distance Service).

[0152] Optionally, when the trigger conditions are met, the phone's display engine periodically adds an eye distance fence. The trigger conditions include one or more of the following effects:

[0153] a: The defocus vision relief function is on.

[0154] Among them, the defocus vision relief function is a screen eye protection feature. This function uses AI defocus eye protection technology to simulate the defocus principle of myopia, automatically adjusting the image to relieve the user's eye strain caused by refractive errors. For example, on the one hand, it can intelligently adjust the details of the image based on the user's screen time, making the image edges show color changes. On the other hand, it can dynamically adjust the blur radius of the image edges based on the distance of the user's eyes, making the image edges show different degrees of blur.

[0155] Optionally, in some scenarios, this function is enabled by default after the phone is turned on. Based on this, the image display effect can be adjusted in real time according to the user's screen time and / or eye distance, so as to alleviate the aggravation of myopia and protect the eyes.

[0156] To avoid disturbing users, save power, or protect user privacy, a "Defocus Vision Soothing" toggle could be added to the phone's settings. The phone could then respond to the user's input, turning the defocus vision soothing function on / off, improving the user experience. Alternatively, the toggle could be displayed via a smart capsule interface for easy user access. Of course, other methods could also be used, such as floating windows, floating controls, or notification messages; these are not limited here.

[0157] The following lists three ways to set the on / off switch for the defocus vision relief function.

[0158] The first method: Add a switch in the settings interface.

[0159] For example, as shown in Figure 12(a), in response to the user's operation of launching the settings application, as shown in Figure 12(b), the phone displays interface 101, which includes multiple settings items, such as: WLAN, Bluetooth, mobile network, display and brightness, sound, notification and status bar settings (other settings items can be referred to in the actual situation, and will not be listed here). Optionally, interface 101 also includes an Oasis Eye Protection setting item 102. In response to the user's operation on the Oasis Eye Protection setting item 102 (such as a click operation, a swipe operation, etc., the following takes a click operation as an example), as shown in Figure 12(c), the phone displays interface 103, which includes a defocus vision relief switch 104. Optionally, interface 103 may also include a sleep aid display switch, an eye protection mode switch, etc., which are not limited here. In response to the user's click operation on the defocus vision relief switch 104, the phone activates the defocus vision relief function. As shown in Figure 12(c), the defocus vision relief switch 104 is in the on state.

[0160] The second method uses a "Dynamic Capsule" display to provide users with an on / off switch for the defocus vision relief function. The Dynamic Capsule is located at the top of the screen, displayed in a capsule shape, showing the ongoing task for easy viewing of real-time status, quick actions, or rapid access to applications. The Dynamic Capsule can collapse into a "spherical" shape and then expand back into a Dynamic Capsule after a period of time until the task ends. The Dynamic Capsule can also expand to a larger form to display dynamic notifications. The timing, duration, and interaction methods of the Dynamic Capsule display vary depending on the task type.

[0161] For example, after the phone is powered on, the "Smart Capsule" can be displayed periodically to prompt the user to activate the defocus vision relief function. For example, as shown in Figure 13, the Smart Capsule 105 includes text information and icon information. The text information could be, for example, "Myopia-Friendly," and the icon information could be, for example, "Glasses." For example, in response to the user clicking the Smart Capsule, the phone unfolds and displays the Smart Capsule's information; for example, after unfolding the Smart Capsule, card 106 is displayed. Card 106 includes icon information, text information, and a switch. The icon information could be, for example, "Glasses," and the text information could be, for example, "Myopia-Friendly, making the screen image more consistent with retinal perception characteristics, similar to the visual experience of looking into the distance." Based on this, the user can click the switch to activate the defocus vision relief function. For example, in response to the user clicking the switch, the switch is in the "on" state, and the phone activates the defocus vision relief function. Optionally, after the switch has been on for a preset duration, the phone retracts the displayed card 106 and re-displays the Smart Capsule 105.

[0162] The third method: notification message method.

[0163] For example, after the phone is powered on, it can periodically display notification messages to prompt the user to activate the defocus vision relief function. For example, as shown in Figure 14, the phone displays notification message 108 in the notification bar interface 107. This notification message includes icon information, text information, and a switch. The icon information could be, for example, "glasses," and the text information could be, for example, "Myopia-friendly, making the screen image more consistent with retinal perception characteristics, similar to the visual experience of looking into the distance." Based on this, the user can click the switch to activate the defocus vision relief function. For example, in response to the user's click on the switch, the switch is turned on, and the phone activates the defocus vision relief function. Optionally, after the switch is turned on, the notification message remains permanently displayed in the notification bar interface, and the user cannot delete the notification message.

[0164] In the aforementioned trigger condition a, the mobile phone can determine whether to detect the distance to the user's eyes by judging whether the defocus vision relief function is turned on. This can prevent the detection of the distance to the user's eyes without their knowledge, thus preventing disturbance to the user and protecting the user's privacy and security.

[0165] b: The distance between the user and the mobile phone is greater than the preset distance.

[0166] It is understood that in this embodiment, the distance to the user's eyes is detected based on the grayscale image captured by the ASC camera. When the phone is obstructed, it is impossible to capture a grayscale image using the ASC camera, or the captured grayscale image cannot be used to detect the distance to the user's eyes. Therefore, the phone can determine whether it is obstructed (e.g., the phone is placed in the user's pocket, or the user is making a call) by judging the distance between the user and the phone.

[0167] Optionally, if the distance between the user and the phone is greater than a preset distance, it can be determined that the phone is not obstructed. If the distance between the user and the phone is less than or equal to the preset distance, it can be determined that the phone is obstructed. For example, the phone may have a built-in proximity sensor used to detect the distance between the user and the phone.

[0168] The preset distance can be, for example, 5cm, 10cm, etc., and is not limited here. Of course, this preset distance can also be set by those skilled in the art according to actual needs, which will not be listed here.

[0169] In the aforementioned trigger condition b, the phone determines whether it is obstructed by detecting the distance between the user and the phone. If the phone is not obstructed, it further detects the distance to the user's eyes; if the phone is obstructed, it can stop detecting the distance to the user's eyes, thereby improving the reliability of the distance detection and reducing power consumption.

[0170] c: Ambient light intensity is within the preset range.

[0171] It should be noted that both excessively bright and excessively dark ambient light can lead to uneven (or unclear) grayscale images captured by the ACS camera. For example, excessively bright ambient light (i.e., high ambient illumination) will result in overexposed grayscale images; excessively dark ambient light (i.e., low ambient illumination) will result in unclear grayscale images. Therefore, when the ambient illumination is within a preset range, it can ensure that the image information of the grayscale image captured by the ACS camera is relatively complete, which is beneficial for subsequent detection of human eye distance.

[0172] Optionally, the preset range can be, for example, 100 lux to 1000 lux. This application does not specifically limit the preset range; the actual setting shall prevail.

[0173] In the aforementioned triggering condition c, the mobile phone can determine whether the ambient light intensity is within a preset range to ensure that the grayscale image acquired by ASC is clear, thereby ensuring the accuracy of the mobile phone in detecting the distance to the human eye.

[0174] d: The image displayed on the screen is the image shown after the phone launches the target application.

[0175] The target application can be a video application or a reading application. Since users have higher visual demands in video or reading scenarios, creating a highly immersive experience, the eye-distance detection scheme in this embodiment is preferentially adapted to these highly immersive scenarios. Compared to using an ASC camera to capture grayscale images in all scenarios, this reduces power consumption.

[0176] e: The phone's usage time after powering on exceeds the preset time.

[0177] It should be noted that if the scheme of detecting eye distance is executed every time the phone is powered on, it may affect the normal operation of other software. Especially if the user frequently performs the power-on operation (such as restarting) within a certain period, detecting eye distance every time can lead to abnormal phone operation. Therefore, in this embodiment, the usage time after the phone is powered on can be determined. The eye distance detection scheme is only executed when the usage time exceeds a preset time, ensuring the reliability of the scheme and avoiding impact on the phone's operating capabilities.

[0178] For example, the preset duration could be 5 minutes, 10 minutes, or other durations, which are not limited here. Of course, the preset duration can also be set according to actual needs, which will not be listed here.

[0179] Optionally, the phone's display engine can determine whether the phone meets any of the above trigger conditions ae. If the phone meets any of the trigger conditions ae, the phone's display engine can add an eye distance fence to perform eye distance detection.

[0180] Optionally, the phone's display engine can determine whether the phone meets the trigger condition ae. If the phone meets the trigger condition ae, the display engine can add an eye distance fence to perform eye distance detection. In this way, detecting the eye distance only when the phone simultaneously meets the aforementioned trigger condition ae can ensure the reliability of the solution.

[0181] As an example, taking the mobile phone's determination of whether the above triggering condition ae is met as shown in Figure 15, an optional determination process is provided below. It should be noted that the process shown in Figure 15 is merely an example and does not constitute a limitation of this application. In practical applications, more or fewer processes than those shown in Figure 15 may be included, or multiple processes may be combined or split. Furthermore, the order of the determination process shown in Figure 15 is merely an example and cannot be considered a limitation of this application. In practical applications, other orders may also be used to determine whether the triggering condition is met.

[0182] Referring to Figure 15, the mobile phone determines whether the triggering condition is met through the following steps:

[0183] Step a: The phone determines whether the defocus vision relief function is turned on.

[0184] For example, referring to Figures 12-14 above, the mobile phone can determine whether the off-focus vision relief function is turned on. If the switch is turned on, the off-focus vision relief function is determined to be in the on state; if the switch is not turned on, the off-focus vision relief function is determined to be in the off state.

[0185] Optionally, if the defocus vision relief function is enabled, the phone continues with the following steps, as in step b. If the defocus vision relief function is disabled, the phone terminates the process. Consequently, the phone's display engine will not add an eye distance fence, and the phone will not execute the eye distance detection scheme.

[0186] Step b: The phone determines whether the distance between the user and the phone is greater than a preset distance.

[0187] Optionally, the phone can detect the distance between the user and the phone using a proximity sensor. If the distance between the user and the phone is greater than a preset distance, it means the phone is not obstructed, and the phone continues to execute the following steps, such as step c. If the distance between the user and the phone is less than or equal to the preset distance, it means the phone is obstructed, and the phone ends the process.

[0188] Step c: The phone determines whether the ambient light level is within the preset range.

[0189] Optionally, if the ambient light level is within a preset range, the phone continues with the following steps, such as step d. If the ambient light level is not within the preset range, the phone terminates the process.

[0190] Step d: The phone determines whether the image displayed on the screen is an image relevant to the target application scenario.

[0191] Optionally, the phone can determine the application type of the target application to ascertain whether the image displayed on the screen is an image within the target application scenario. For example, if the application type of the target application is video or reading, it means that the image displayed on the screen is an image within the target application scenario (i.e., a video scenario or a reading scenario).

[0192] Optionally, if the image displayed on the screen is relevant to the target application scenario, the phone continues with the following steps, such as step e. If the image displayed on the screen is not relevant to the target application scenario, the phone terminates the process.

[0193] Step e: The phone determines whether the usage time after the phone is turned on is greater than the preset time.

[0194] Optionally, if the usage time after the phone is powered on exceeds a preset time, the phone will detect the distance between the user's eyes. If the usage time after the phone is powered on is less than or equal to the preset time, the phone will terminate the process.

[0195] In summary, the mobile phone can execute steps a-e above to determine whether the triggering conditions are met. If the triggering conditions are met, the mobile phone can execute step 1 above. After the mobile phone completes step 1, its display engine can periodically add eye distance fences to achieve periodic detection of eye distance. For example, the mobile phone can add an eye distance fence every 10 seconds to achieve eye distance detection every 10 seconds. Of course, the mobile phone can also use other intervals (such as every 15 seconds, 20 seconds, etc.) to add eye distance fences, depending on the actual settings, which are not limited here.

[0196] Understandably, the phone's display engine periodically adds eye distance fences to Sensorhub's eye distance driver, with the eye distance fences being managed by the phone's eye distance sensor. Therefore, after the phone completes step 1 above, it can continue with the following steps to detect the eye distance.

[0197] Step 2: Use the phone's eye distance driver to acquire grayscale images.

[0198] For example, referring to Figure 9 above, the phone's display engine adds an eye distance fence to the eye distance driver. Then, upon receiving the eye distance fence, the phone's eye distance driver notifies the ASC camera driver, which in turn drives the ASC camera to capture a grayscale image. Subsequently, the ASC camera transmits the captured grayscale image to the phone's eye distance driver via the ASC camera driver, enabling the eye distance driver to acquire the grayscale image.

[0199] Step 3: The phone's eye distance driver detects human eye feature data based on the grayscale image.

[0200] Optionally, the mobile phone's eye distance driver can detect human eye feature data based on multiple consecutive frames (e.g., 10 frames) of grayscale images to improve the accuracy of human eye detection.

[0201] For example, human eye feature data may include feature data of the user's two eyes (such as the left and right eyes), such as the coordinates of key points in the user's eyes, such as the corners of the eyes and eye positions, as well as the distances between these key points. Optionally, the phone's eye distance driver can also detect data of other key points on the user's face based on the grayscale image. For example, it can detect data of key points such as the user's nose, mouth, eyebrows, and ears. In this case, the data of these key points can also be referred to as facial feature data. For ease of understanding, the following embodiment uses the detection of human eye feature data as an example for illustration.

[0202] For example, the mobile phone's eye distance driver can obtain eye feature data by performing eye detection and pupil localization on a grayscale image. This eye feature data can also be referred to as the pupil distance information in a face image, i.e., the distance between the pupils of both eyes. For instance, as shown in Figure 16, the mobile phone's eye distance driver can obtain the coordinates p1 of the user's left eye corner, p2 of the left eye tail, p3 of the right eye corner, p4 of the right eye tail, and the distances between these coordinates by performing eye detection and pupil localization on a grayscale image. This allows the acquisition of eye feature data, i.e., the distance between the pupils of both eyes (hereinafter referred to as pupil distance information).

[0203] Step 4: The mobile phone's eye distance driver reports human eye feature data to the ISF.

[0204] For example, as shown in Figures 12-14 above, the mobile phone's eye distance driver can report eye feature data to the ISF through eye distance service HAL, AO service, etc. The specific interaction process can be found in the above embodiments, and will not be repeated here.

[0205] Step 5: The phone's ISF sends a request message to the AO service to request TOF data.

[0206] Optionally, the mobile phone's ISF can send a request message to the AO service to request TOF data after receiving human eye feature data. Optionally, the mobile phone's ISF can also send a request message to the AO service to request TOF data after receiving human eye distance fence data; this embodiment of the application does not limit this.

[0207] For example, after receiving a request message, the phone's AO service activates the TOF camera and detects TOF data. For example, the TOF data includes focal length and depth information; that is, the TOF camera can obtain the aforementioned focal length and depth information by detecting the focal length and depth.

[0208] Step 6: The phone's AO service returns TOF data to the ISF.

[0209] Step 7: The phone's ISF detects the distance to the human eye based on human eye feature data and TOF data.

[0210] Optionally, the mobile phone's ISF can use TOF data to calibrate human eye feature data (i.e., interpupillary distance information) to ensure the accuracy of the interpupillary distance information, thereby making the detected eye distance more accurate. In this case, the TOF data calibrated by interpupillary distance information can also be called TOF calibration data (or TOF fusion data).

[0211] For example, the mobile phone's ISF can combine interpupillary distance information and the focal length of the TOF camera to calculate the distance from the human eye to the display screen using the geometric similarity method in monocular ranging. For instance, Figure 17 illustrates the imaging principle of a TOF camera. Referring to Figure 17, the light reflected from the user's pupils passes through the lens (similar to a lens) of the TOF camera, resulting in images at points a and b on the imaging plane. The distance between points a and b is the focal length, denoted as X1. The distance between the imaging plane and the lens is the depth information, denoted as d1. Again, as shown in Figure 7, the distance between the user's pupils is the interpupillary distance information, denoted as X2; the distance between the user and the lens is the distance to the human eye that needs to be calculated, denoted as d2.

[0212] Referring to Figure 17, using the geometric similarity method, X1 / d1=X2 / d2; therefore, d2=(d1*X2) / X1.

[0213] Step 8: The phone's ISF reports the distance to the human eye to the display engine.

[0214] For example, the mobile phone's ISF can report the human eye distance to the display engine through a perception platform. The specific implementation process can be found in the above embodiments and is not limited here.

[0215] Step 9: The phone's display engine dynamically adjusts the blurring of image edges based on the distance to the viewer's eyes.

[0216] For the specific implementation method of dynamically adjusting the blur level of image edges according to the distance of human eyes, please refer to the above embodiments, which will not be repeated here.

[0217] It is understandable that the phone's display engine periodically adds eye-field boundaries. For example, the phone's display engine can add an eye-field boundary every 10 seconds, meaning it detects an eye distance every 10 seconds. In practical applications, the time it takes for a phone to complete one eye-field distance detection is approximately 5 seconds. Therefore, in this embodiment, the phone initiates a 5-second eye-field distance detection every 10 seconds. Based on this, the phone can delete the previously added eye-field boundary after completing one eye-field distance detection. For example, the phone's display engine can delete the previously added eye-field boundary after receiving the eye distance. For instance, the phone's display engine can send a command to the underlying layer (such as Sensorhub) to delete the eye-field boundary, instructing Sensorhub's eye-field distance driver to delete the eye-field boundary.

[0218] In summary, the solution adopted in this application, when the triggering conditions are met, adds an eye distance fence to the underlying layer (such as Sensorhub) by the mobile phone's display engine. The Sensorhub's eye distance driver can drive the ASC camera to acquire grayscale images of the face, detect eye feature data, and report the eye feature data to the ISF. The ISF combines the eye feature data and TOF data to calculate the eye distance and reports the eye distance to the display engine. This allows the display engine to dynamically adjust the blurring degree of image edges according to the eye distance, giving the user a visual experience similar to "looking into the distance," alleviating the aggravation of myopia, and achieving the purpose of eye protection.

[0219] It should be noted that the contents described in the various embodiments of this application can explain the technical solutions in other embodiments of this application. The technical features described in each embodiment can also be applied in other embodiments and combined with the technical features in other embodiments to form new solutions. This application only provides an exemplary list of several embodiments for illustration and does not mean that this application is limited thereto.

[0220] This application provides an electronic device, which can be the mobile phone 100 described above. The electronic device may include a memory and one or more processors; the memory stores computer program code, which includes computer instructions. When the computer instructions are executed by the processor, the electronic device performs various functions or steps performed in the mobile phone. The structure of this electronic device can be referred to the structure of the mobile phone 100 shown in FIG8.

[0221] This application also provides a chip system applied in the aforementioned electronic device, which can be the aforementioned mobile phone 100. As shown in FIG18, the chip system 1100 includes at least one processor 1101 (e.g., an application processor AP and a Sensorhub) and at least one interface circuit 1102. The processor 1101 can be the processor 110 shown in FIG8 of the above embodiment. The interface circuit 1102 can be, for example, an interface circuit between the processor 110 and external memory; or an interface circuit between the processor 110 and internal memory 121.

[0222] The processor 1101 and interface circuit 1102 described above can be interconnected via lines. For example, interface circuit 1102 can be used to receive signals from other devices (e.g., the memory of electronic device 400). As another example, interface circuit 1102 can be used to send signals to other devices (e.g., processor 1101). Exemplarily, interface circuit 1102 can read instructions stored in memory and send those instructions to processor 1101. When the instructions are executed by processor 1101, the electronic device can perform the various functions or steps performed in the mobile phone in the above embodiments. Of course, the chip system may also include other discrete components, and this application embodiment does not specifically limit this.

[0223] This application also provides a computer-readable storage medium including computer instructions that, when executed on an electronic device, cause the electronic device to perform various functions or steps performed in the mobile phone described in the above method embodiments.

[0224] This application also provides a computer program product that, when run on a computer, causes the computer to perform various functions or steps performed in the mobile phone in the above method embodiments.

[0225] Through the above description of the embodiments, those skilled in the art can clearly understand that, for the sake of convenience and brevity, only the division of the above functional modules is used as an example. In practical applications, the above functions can be assigned to different functional modules according to the system, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0226] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another device, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0227] The units described as separate components may or may not be physically separate. A component shown as a unit can be one or more physical units; that is, it can be located in one place or distributed in multiple different locations. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0228] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit described above can be implemented in hardware or as a software functional unit.

[0229] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a readable storage medium. Based on this understanding, the technical solutions of the embodiments of this application, essentially or in other words, the parts that contribute to the prior art, or all or part of the technical solutions, can be embodied in the form of a software product. This software product is stored in a storage medium and includes several instructions to cause a device (which may be a microcontroller, chip, etc.) or processor to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0230] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions within the technical scope disclosed in this application should be included 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

1. A method for adjusting an image based on human eye distance, characterized in that, Applied to an electronic device, the electronic device including a display screen, the method includes: Display the interface of the target application, the interface including images; The image is displayed with a first degree of blur when the distance to the human eye is a first distance. When the distance to the human eye is the second distance, the image is displayed with the second degree of blur. Wherein, the human eye distance is the distance between the human eye and the display screen; the first distance is different from the second distance, and the first degree of blur is different from the second degree of blur.

2. The method according to claim 1, characterized in that, The first distance is less than the second distance, and the first degree of blur is less than the second degree of blur.

3. The method according to claim 1 or 2, characterized in that, The target application type includes a first application type and a second application type; When the distance between the human eye and the display screen is fixed, the blurriness of the image corresponding to the target application of the first application type is higher than that of the image corresponding to the target application of the second application type.

4. The method according to claim 3, characterized in that, The first application type is a video application, and the second application type is a reading application.

5. The method according to any one of claims 1-4, characterized in that, When the distance between the human eye and the display screen is fixed, the higher the ambient light level, the lower the blurriness of the image.

6. The method according to claim 5, characterized in that, When the distance between the human eye and the display screen is fixed, if the ambient light intensity is greater than a preset illuminance threshold, the blurriness of the image is zero.

7. The method according to any one of claims 1-6, characterized in that, The method further includes: When the triggering condition is met, acquire human eye feature data; The distance to the human eye is detected based on the aforementioned human eye feature data; The triggering conditions include one or more of the following: The defocus vision relief function is enabled, the distance between the user and the electronic device is greater than a preset distance, the ambient light intensity is within a preset range, the interface is the interface of the target application of the electronic device, and the usage time of the electronic device after powering on is greater than a preset time.

8. The method according to claim 7, characterized in that, The step of acquiring human eye feature data when the triggering condition is met includes: When the triggering condition is met, grayscale images of the face are periodically acquired; wherein the color of each pixel in the grayscale image of the face is represented by a single grayscale value. Based on the grayscale image of the face, obtain the human eye feature data.

9. The method according to claim 7 or 8, characterized in that, The electronic device includes a Sensorhub and an application processor (AP); The step of acquiring human eye feature data when the triggering condition is met includes: When the AP determines that the triggering condition is met, it sends a human eye detection command to the Sensorhub. In response to the human eye detection command, the Sensorhub acquires the human eye feature data; The step of detecting the eye distance based on the eye feature data includes: The Sensorhub reports the human eye feature data to the AP; The AP detects the distance to the human eye based on the human eye feature data and the time-of-flight (TOF) data.

10. The method according to claim 9, characterized in that, The AP is deployed with a local service layer, which includes the intelligent sensing framework ISF; The AP detects the human eye distance based on the human eye feature data and TOF data, including: The AP detects the human eye distance based on the human eye feature data and the TOF data through the ISF included in the Native layer.

11. The method according to claim 10, characterized in that, The AP also deploys an application layer, and the method further includes: The human eye distance is reported to the application layer through the ISF included in the Native layer; The application layer of the AP adjusts the blur level of the image based on the human eye distance.

12. An electronic device, characterized in that, include: Display screen, memory, and one or more processors; The display screen is used to display images; The memory stores computer program code, which includes computer instructions; when the computer instructions are executed by the processor, the electronic device performs the method as described in any one of claims 1-11.

13. A chip system, characterized in that, The chip system, used in electronic devices, includes: At least one processor and an interface; The interface is used to receive instructions and transmit them to the at least one processor; the at least one processor executes the instructions to cause the electronic device to perform the method as described in any one of claims 1-11.

14. A computer-readable storage medium, characterized in that, include: Computer instructions; When the computer instructions are executed on an electronic device, the electronic device causes the electronic device to perform the method as described in any one of claims 1-11.

15. A computer program product, characterized in that, When the computer program product is run on a computer, it causes the computer to perform the method as described in any one of claims 1-11.

Images