Display parameter determination method and device, electronic equipment, chip and storage medium

Abstract

The invention provides a display parameter determination method and device, electronic equipment, a chip and a storage medium, and relates to the technical field of terminals. Comprising the steps of determining a first probability that a target user belongs to each preset age group according to a face image and sound information of the target user; determining a second probability that the target user belongs to each preset fatigue level according to the video data corresponding to the eye region of the target user; and determining a target display parameter corresponding to the target user according to the first probability, the second probability and the first display parameter. Therefore, the display parameters of the target user can be determined according to the two dimensions of the age and the fatigue level of the target user, self-adaptive adjustment of the display parameters according to the personalized information of the user is achieved, the determined target display parameters are more suitable for the current state of the target user, and then the eyes of the user can be protected.

Description

Technical Field

[0001] The present disclosure relates to the field of terminal technology, and in particular to a method, device, electronic device, chip and storage medium for determining display parameters. Background Art

[0002] With the popularization of televisions, personal computers and smart phones, as well as the rapid development of new display technologies such as virtual display and laser display, display-related visual health issues are becoming increasingly prominent. In related technologies, if different user groups (elderly, children, etc.) use the default parameters of the screen, some users may suffer from eye fatigue or even a large number of eye diseases because the screen display is not suitable for some users.

[0003] Therefore, how to determine display parameters suitable for the user based on the user's personalized information to protect the user's eyes has become an urgent problem to be solved. Summary of the invention

[0004] The present disclosure aims to solve one of the technical problems in the related art at least to some extent.

[0005] The first embodiment of the present disclosure provides a method for determining a display parameter, including:

[0006] Determining, based on the facial image and voice information of the target user, a first probability that the target user belongs to each preset age group;

[0007] determining, according to the video data corresponding to the eye area of ​​the target user, a second probability that the target user belongs to each preset fatigue level;

[0008] The target display parameters corresponding to the target user are determined according to the first probability, the second probability and the first display parameters, wherein users of each preset age group correspond to a set of first display parameters at each preset fatigue level.

[0009] A second aspect of the present disclosure provides a device for determining a display parameter, including:

[0010] A first determination module, configured to determine a first probability that the target user belongs to each preset age group according to the facial image and voice information of the target user;

[0011] A second determination module, configured to determine, based on the video data corresponding to the eye area of ​​the target user, a second probability that the target user belongs to each preset fatigue level;

[0012] The third determination module is used to determine the target display parameters corresponding to the target user according to the first probability, the second probability and the first display parameters, wherein users of each preset age group correspond to a set of first display parameters at each preset fatigue level.

[0013] The third aspect embodiment of the present disclosure proposes an electronic device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, the method for determining display parameters proposed in the first aspect embodiment of the present disclosure is implemented.

[0014] A fourth aspect of the present disclosure provides a chip, wherein the chip includes a processing circuit, and the processing circuit is configured to execute the method for determining display parameters provided in the first aspect of the present disclosure.

[0015] The fifth aspect embodiment of the present disclosure proposes a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, the method for determining display parameters proposed in the first aspect embodiment of the present disclosure is implemented.

[0016] The display parameter determination method, device, electronic device, chip and storage medium provided by the present disclosure have the following beneficial effects:

[0017] In the embodiment of the present disclosure, the first probability that the target user belongs to each preset age group and the second probability that the target user belongs to each preset fatigue level are first determined, and finally the target display parameter corresponding to the target user is determined according to the first probability, the second probability and the first display parameter. Thus, the display parameter of the target user can be determined according to the two dimensions of the age and fatigue level of the target user, and the display parameter is adaptively adjusted according to the personalized information of the user, so that the determined target display parameter is more suitable for the current state of the target user, thereby protecting the user's eyes.

[0018] Additional aspects and advantages of the present disclosure will be given in part in the following description and in part will be obvious from the following description or learned through practice of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The above and / or additional aspects and advantages of the present disclosure will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0020] Figure 1 A flowchart of a method for determining display parameters provided by an embodiment of the present disclosure;

[0021] Figure 2 A schematic flow chart of a method for determining display parameters provided by another embodiment of the present disclosure;

[0022] Figure 3 A schematic flow chart of a method for determining display parameters provided by another embodiment of the present disclosure;

[0023] Figure 4 A schematic flow chart of a method for determining display parameters provided by another embodiment of the present disclosure;

[0024] Figure 5 A schematic diagram of the structure of a device for determining display parameters provided by another embodiment of the present disclosure;

[0025] Figure 6 A block diagram of an exemplary electronic device suitable for implementing the embodiments of the present disclosure is shown;

[0026] Figure 7 A schematic diagram of the structure of a chip proposed in an embodiment of the present disclosure. DETAILED DESCRIPTION

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

[0028] The following describes a method, device, electronic device, and storage medium for determining display parameters according to an embodiment of the present disclosure with reference to the accompanying drawings.

[0029] Figure 1 A flowchart of a method for determining display parameters provided by an embodiment of the present disclosure is provided.

[0030] The embodiment of the present disclosure takes the method for determining display parameters configured in a device for determining display parameters as an example. The device for determining display parameters can be applied to any electronic device so that the electronic device can perform the function of determining display parameters.

[0031] like Figure 1 As shown, the method for determining the display parameters may include the following steps:

[0032] Step 101, determining a first probability that the target user belongs to each preset age group based on the facial image and voice information of the target user.

[0033] Among them, since the user will not age significantly in a short period of time (such as one month or half a year), the facial image of the target user may be a recent facial image of the target user. For example, a facial image of the target user within one month or within one year. Alternatively, the facial image of the target user may be obtained by collecting the facial area of ​​the target user in real time. The present disclosure does not limit this.

[0034] Among them, since the voice of the user will not change significantly in a short period of time (such as one month or half a year), the voice information of the target user can be the recent voice information of the target user. For example, the voice information of the target user within one month or within one year. Alternatively, the voice information of the target user can also be obtained by collecting the voice of the target user in real time. This disclosure does not limit this.

[0035] The preset age group may be pre-set, for example, every 10 years or 5 years is a preset age group. Alternatively, the preset age group may be a preset age group corresponding to children, teenagers, middle-aged and young people, and the elderly. For example, the preset age group corresponding to children is 0-12 years old, the preset age group corresponding to teenagers is 12-18 years old, the preset age group corresponding to middle-aged and young people is 18-60 years old, and the preset age group corresponding to the elderly is over 60 years old.

[0036] In some embodiments, the facial image and voice information of the target user may also be input into the first artificial intelligence model to obtain the first probability that the target user belongs to each preset age group. The first artificial intelligence model is generated through training based on the sample facial image, sample voice and age label corresponding to the sample user.

[0037] In some embodiments, information can be first extracted from the target user's facial image to obtain information such as the target user's facial flatness, wrinkles, skin color, hair volume, etc., and then combined with the sound information, based on the threshold conditions corresponding to each preset age group, the first probability that the target user belongs to each preset age group can be determined.

[0038] In some embodiments, the sum of the first probabilities for all age groups is 1.

[0039] Step 102: determining a second probability that the target user belongs to each preset fatigue level according to the video data corresponding to the eye area of ​​the target user.

[0040] Among them, since the user may experience eye fatigue within a short period of time (such as one hour or half an hour), it is necessary to obtain video data of the target user's eye area in real time to determine whether the target user is fatigued.

[0041] The preset fatigue level may be divided into non-fatigue and fatigue. Alternatively, the preset fatigue level may be divided into multiple levels such as non-fatigue, mild fatigue, severe fatigue, etc., which is not limited in the present disclosure.

[0042] In some embodiments, the user's blinking frequency, distance between upper and lower eyelids, number of red bloodshot eyes, etc. can be analyzed from the video data, and then the blinking frequency, distance between upper and lower eyelids, number of red bloodshot eyes, etc. are input into the second artificial intelligence model to predict the second probability that the target user belongs to each preset fatigue level. The second artificial intelligence model is trained and generated based on the sample video data corresponding to the eye area of ​​the sample user and the fatigue level label.

[0043] In some embodiments, the second probabilities of all fatigue levels sum to 1.

[0044] Step 103, determining the target display parameters corresponding to the target user according to the first probability, the second probability and the first display parameters, wherein users of each preset age group correspond to a set of first display parameters at each preset fatigue level.

[0045] In some embodiments, the display parameters may include at least one of the following: resolution, sharpness, brightness, color, contrast, and saturation.

[0046] The first display parameters corresponding to users of each preset age group at each preset fatigue level may be obtained by conducting experiments under the same environment. For example, the display parameters may be continuously adjusted for users of the same preset age group at the same preset fatigue level until a display parameter that meets the needs of most users is found as the first display parameter.

[0047] In some embodiments, the preset age group with the highest first probability can be determined as the second age group to which the target user belongs, the preset fatigue level with the highest second probability can be determined as the second fatigue level to which the target user belongs, and the first display parameter corresponding to the user of the second age group at the second fatigue level can be determined as the target display parameter. In this way, the preset age group and preset fatigue level to which the target user belongs can be quickly determined, and then the target display parameter corresponding to the target user can be quickly found.

[0048] In some embodiments, based on the first probability that the target user belongs to each preset age group, multiple first display parameters corresponding to each preset age group under the same preset fatigue level can be fused to determine the second display parameters corresponding to the target user at each preset fatigue level. Then, based on each second probability, the second display parameters corresponding to the target user at each preset fatigue level can be fused to determine the target display parameters.

[0049] For example, the preset age groups can be divided into children, middle-aged and young people, and the elderly. The first probability corresponding to children is weight_kid, the first probability corresponding to middle-aged and young people is weight_mid, and the probability corresponding to the elderly is weight_old. The preset fatigue levels can include fatigue and non-fatigue. The second probability corresponding to fatigue is weight_fatigued, and the second probability corresponding to non-fatigue is weight_nofatigued. The first display parameters corresponding to users of each preset age group at each preset fatigue level can be shown in Table 1.

[0050] fatigue Non-fatigue child para_kid_fatigued para_kid_nofatigued Young and middle-aged para_mid_fatigued para_mid_nofatigued elderly para_old_fatigued para_old_nofatigued

[0051] Among them, the second display parameter in the fatigue state can be:

[0052] para_age_fatigued=weight_kid*para_kid_fatigued+weight_mid*para_mid_fatigued+weight_old*para_mid_fatigued

[0053] The second display parameter in the non-fatigue state can be:

[0054] para_age_nofatigued=weight_kid*para_kid_nofatigued+weight_mid*para_mid_nofatigued+weight_old*para_mid_nofatigued

[0055] The target display parameters can be:

[0056] para_final=weight_fatigued*para_age_fatigued+weight_nofatigued*para_age_nofatigued

[0057] In some embodiments, based on the second probability that the target user belongs to each preset fatigue level, multiple first display parameters corresponding to each preset fatigue level in the same preset age group can be fused to determine the fourth display parameters corresponding to the target user in each preset age group, and then based on each first probability, the fourth display parameters corresponding to the target user in each preset age group are fused to determine the target display parameters. It should be noted that this implementation method is the same as the implementation method of first determining the second display parameters corresponding to the target user in each preset fatigue level and then determining the target display parameters. It will not be described in detail here.

[0058] In some embodiments, the target weights of the target user belonging to each preset age group and fatigue level can be determined based on the first probability that the target user belongs to each preset age group and the second probability that the target user belongs to each preset fatigue level. Then, based on each target weight, all the first display parameters are fused to obtain the target display parameters.

[0059] For example, the target weight corresponding to youth fatigue can be the product of the first probability corresponding to youth and the second probability corresponding to fatigue.

[0060] Therefore, in the embodiment of the present disclosure, based on the first probability that the target user belongs to each preset age group and the second probability that the target user belongs to each preset fatigue level, all the first display parameters are integrated, fully considering the possibility that the target user belongs to each preset age group and each preset fatigue level, so that the target display parameters of the target user can be determined more accurately.

[0061] In the disclosed embodiment, the first probability that the target user belongs to each preset age group and the second probability that the target user belongs to each preset fatigue level are first determined, and then the target display parameter corresponding to the target user is determined according to the first probability, the second probability and the first display parameter. Thus, the display parameter of the target user can be determined according to the two dimensions of the age and fatigue level of the target user, and the display parameter is adaptively adjusted according to the personalized information of the user, so that the determined target display parameter is more suitable for the current state of the target user, thereby protecting the user's eyes.

[0062] Figure 2 A flow chart of a method for determining display parameters provided by an embodiment of the present disclosure is shown as follows: Figure 2 As shown, the method for determining the display parameters may include the following steps:

[0063] Step 201 : determining a first probability that the target user belongs to each preset age group based on the facial image and voice information of the target user.

[0064] Step 202: determining a second probability that the target user belongs to each preset fatigue level according to the video data corresponding to the eye area of ​​the target user.

[0065] Step 203 , based on the first probability that the target user belongs to each preset age group, multiple first display parameters corresponding to each preset age group at the same preset fatigue level are merged to determine the second display parameters corresponding to the target user at each preset fatigue level.

[0066] The specific implementation forms of steps 201 to 203 can refer to the detailed descriptions in other embodiments of the present disclosure, and will not be described in detail here.

[0067] Step 204: Determine the preset fatigue levels corresponding to the second probabilities with the second largest number as the first fatigue level, wherein the value of the second number is an integer greater than 1 and less than the total number of preset fatigue levels.

[0068] The second number may be two, three, etc., which is not limited in the present disclosure.

[0069] Step 205: Determine a second weight corresponding to each first fatigue level based on the second probability corresponding to each first fatigue level.

[0070] In some embodiments, the greater the second probability that the target user belongs to the first fatigue level, the greater the corresponding second weight.

[0071] In some embodiments, the sum of the second weights corresponding to the second number of first fatigue levels may be 1.

[0072] In some embodiments, the second probability sum of multiple first fatigue levels may be determined first, and then the ratio of the second probability of each first fatigue level to the second probability sum may be determined as the second weight corresponding to each first fatigue level.

[0073] Step 206 : Based on the second weights corresponding to the first fatigue levels, the second display parameters corresponding to the target user at the first fatigue levels are integrated to determine the target display parameters.

[0074] It should be noted that when the actual fatigue level of the target user is at the boundary of two fatigue levels, the second probability of being determined to be at the boundary of the two fatigue levels may be relatively close and have a relatively high probability according to the video data. Therefore, in the embodiment of the present disclosure, only the first display parameter corresponding to the preset fatigue level with a relatively high second probability may be considered, and the first display parameter corresponding to the preset fatigue level with a relatively low second probability may be discarded, so as to avoid the influence of the first display parameter corresponding to the preset fatigue level with a relatively low second probability on the target display parameter, thereby more accurately determining the target display parameter of the target user.

[0075] In the disclosed embodiment, based on the first probability that the target user belongs to each preset age group, multiple first display parameters corresponding to each preset age group under the same preset fatigue level can be fused to determine the second display parameters corresponding to the target user at each preset fatigue level, and the preset fatigue level corresponding to the second largest second probability is determined as the first fatigue level. Based on the second probability corresponding to each first fatigue level, the second weight corresponding to each first fatigue level is determined, and finally based on the second weight corresponding to each first fatigue level, the second display parameters corresponding to the target user at each first fatigue level are fused to determine the target display parameter. Therefore, when the multiple first display parameters corresponding to each preset age group under the same preset fatigue level are fused based on the first probability that the target user belongs to each preset age group, the possibility that the target user belongs to each preset age group is fully considered, and then when the second display parameters corresponding to the fatigue level with a larger second probability are fused to obtain the target display parameter, only the first display parameters corresponding to the preset fatigue level with a larger second probability are considered to avoid the influence of the first display parameters corresponding to the preset fatigue level with a smaller second probability on the target display parameter, so that the target display parameter of the target user can be determined more accurately.

[0076] Figure 3 A flow chart of a method for determining display parameters provided by an embodiment of the present disclosure is shown as follows: Figure 3 As shown, the method for determining the display parameters may include the following steps:

[0077] Step 301, determining a first probability that the target user belongs to each preset age group based on the facial image and voice information of the target user.

[0078] Step 302: determining a second probability that the target user belongs to each preset fatigue level according to the video data corresponding to the eye area of ​​the target user.

[0079] The specific implementation forms of step 301 to step 302 can refer to the detailed descriptions in other embodiments of the present disclosure, and will not be described in detail here.

[0080] Step 303: Determine the preset age group corresponding to the first probabilities with the largest first number as the first age group, wherein the first number is an integer greater than 1 and less than the total number of preset age groups.

[0081] The first number may be two, three, etc., which is not limited in the present disclosure.

[0082] Step 304: Determine a first weight corresponding to each first age group based on the first probability corresponding to each first age group.

[0083] In some embodiments, the greater the first probability that the target user belongs to the first age group, the greater the corresponding first weight.

[0084] In some embodiments, the sum of the first weights corresponding to the first number of first age groups may be 1.

[0085] In some embodiments, the first probability sum of multiple first age groups may be determined first, and then the ratio of the first probability of each first age group to the first probability sum may be determined as the first weight corresponding to each first age group.

[0086] Step 305 , based on the first weights corresponding to the first age groups, the first display parameters corresponding to the first age groups at the same preset fatigue level are merged to determine the second display parameters corresponding to the target user at each preset fatigue level.

[0087] It should be noted that when the real age of the target user is at the boundary of two age groups, the first probability of belonging to the two preset age groups may be relatively close and have a higher probability according to the facial image and voice information. Therefore, in the embodiment of the present disclosure, only the first display parameters corresponding to the preset age group with a higher first probability may be considered, and the first display parameters corresponding to the preset age group with a lower first probability may be discarded, so as to avoid the influence of the first display parameters corresponding to the preset age group with a lower first probability on the target display parameters, thereby more accurately determining the target display parameters of the target user.

[0088] Step 306: Based on each second probability, the second display parameters corresponding to the target user at each preset fatigue level are integrated to determine the target display parameters.

[0089] In some embodiments, the preset fatigue level corresponding to the second largest number of second probabilities can also be determined as the first fatigue level, and then the second weight corresponding to each first fatigue level can be determined based on the second probability corresponding to each first fatigue level. Then, based on the second weight corresponding to each first fatigue level, the second display parameters corresponding to the target user at each first fatigue level are fused to determine the target display parameters.

[0090] The value of the second number is an integer greater than 1 and less than the total number of preset fatigue levels.

[0091] It should be noted that when the actual fatigue level of the target user is at the boundary of two fatigue levels, the second probability of being determined to be at the boundary of the two fatigue levels may be relatively close and have a relatively high probability according to the video data. Therefore, in the embodiment of the present disclosure, only the first display parameters corresponding to the preset age group with a relatively large first probability and the preset fatigue level with a relatively large second probability can be considered, and the first display parameters corresponding to the preset age group with a relatively small first probability and the preset fatigue level with a relatively small second probability can be discarded, so as to avoid the influence of the first display parameters corresponding to the preset age group with a relatively small first probability and the preset fatigue level with a relatively small second probability on the target display parameters, thereby more accurately determining the target display parameters of the target user.

[0092] In the disclosed embodiment, the preset age group corresponding to the first probability with the largest number can be determined as the first age group, and then the first weight corresponding to each first age group is determined based on the first probability corresponding to each first age group, and then the first display parameters corresponding to the first age group under the same preset fatigue level are fused based on the first weight corresponding to each first age group to determine the second display parameters corresponding to the target user under each preset fatigue level, and finally the second display parameters corresponding to the target user under each preset fatigue level are fused based on each second probability to determine the target display parameters. Thus, when the first display parameters corresponding to the preset age group with a larger first probability under the same preset fatigue level are fused, only the first display parameters corresponding to the preset age group with a larger first probability are considered, avoiding the influence of the first display parameters corresponding to the preset age group with a smaller first probability on the target display parameters, and then when the second display parameters are fused based on the second probability corresponding to each fatigue level, the possibility that the target user belongs to each fatigue level is fully considered, so that the target display parameters of the target user can be determined more accurately.

[0093] Figure 4 A flow chart of a method for determining display parameters provided by an embodiment of the present disclosure is shown as follows: Figure 4 As shown, the method for determining the display parameters may include the following steps:

[0094] Step 401, determining a first probability that the target user belongs to each preset age group based on the facial image and voice information of the target user.

[0095] Step 402: determining a second probability that the target user belongs to each preset fatigue level according to the video data corresponding to the eye area of ​​the target user.

[0096] Step 403, determining the target display parameters corresponding to the target user according to the first probability, the second probability and the first display parameters, wherein users of each preset age group correspond to a set of first display parameters at each preset fatigue level.

[0097] The specific implementation forms of steps 401 to 403 can refer to the detailed descriptions in other embodiments of the present disclosure, and will not be described in detail here.

[0098] Step 404: if the target user has color vision impairment, update the target display parameters based on the color vision impairment type of the target user.

[0099] Among them, color vision disorders can be divided into color blindness, color weakness, etc.

[0100] It should be noted that color blindness is a color vision disorder caused by congenital genetic or acquired disease factors, which is mainly manifested by reduced color discrimination ability. Although color-blind patients can see the colors that normal people see, their ability to recognize colors is slow or very poor. In dim light, some can hardly distinguish colors. Therefore, if the color vision disorder type of the target user is color blindness, the color saturation, brightness, etc. can be further improved based on the target display parameters.

[0101] In some embodiments, when the color vision impairment type of the target user is color weakness, a third probability that the target user is color weak and a fourth probability that the target user is not color weak can be determined, and then based on the third probability and the fourth probability, the third display parameters and target display parameters corresponding to color weakness under the current ambient brightness are fused to obtain updated target display parameters.

[0102] The third probability is greater than the fourth probability. It should be noted that, since the color vision disorder type of the target user is color blindness, the third probability of color blindness is greater than the fourth probability of non-color blindness.

[0103] It should be noted that different ambient brightness has a greater impact on the display parameters of color-blind users. Therefore, in the embodiment of the present disclosure, different display parameters can be configured for color-blind users under different ambient brightness. Thus, the third display parameter corresponding to color-blindness under the current ambient brightness can be directly obtained.

[0104] In some embodiments, the recognition results of the target user for a third number of first images can be determined first, wherein the first images are used to identify whether the user is color blind. Then, it is determined that the fourth number corresponding to the first images whose recognition results are incorrect is determined to be a fifth number corresponding to the first images whose recognition results are correct. Finally, the ratio of the fourth number to the third number is determined as the third probability, and the ratio of the fifth number to the fourth number is determined as the fourth probability.

[0105] For example, the third number is 100 images, and the target user correctly identifies 40 images and incorrectly identifies 60 images, then the third probability is 0.6 and the fourth probability is 0.4.

[0106] It should be noted that color blindness is a color vision disorder caused by abnormal or incomplete photosensitive pigments in cone cells, resulting in a lack of ability to distinguish one or several colors. Therefore, in the case where the target user's color vision disorder type is color blindness, the colors that the target user cannot recognize can be converted into recognizable colors based on the target user's color blindness type.

[0107] In some embodiments, when the color vision impairment type of the target user is color blindness, the color blindness type corresponding to the target user can be determined first, then the color to be converted and the converted color corresponding to the color blindness type can be determined, and finally the target display parameters can be updated based on the color to be converted and the converted color.

[0108] Among them, color blindness types can include red-green color blindness, blue-yellow color blindness and total color blindness.

[0109] For example, for red-green color blindness, red can be converted to blue and green to yellow. That is, the colors to be converted are red and green, the converted color corresponding to red is blue, and the converted color corresponding to green is yellow.

[0110] In the embodiment of the present disclosure, after the target display parameters are determined according to the age and fatigue level of the target user, the target display parameters can be further updated based on the color vision impairment type of the target user when the target user has color vision impairment. Thus, when the user has color vision impairment, the display parameters of the target user can be determined based on the three dimensions of the age, fatigue level and color vision impairment type of the target user, so that the display parameters are adaptively adjusted according to the personalized information of the color vision impairment user, so that the determined target display parameters are more suitable for the current state of the color vision impairment user, which not only allows the color vision impairment user to clearly see the display content, but also protects the eyes of the color vision impairment user.

[0111] In some embodiments, after determining the target display parameter corresponding to the target user based on the first probability, the second probability and the first display parameter, the device of the target user can be controlled to display content based on the target display parameter. Thus, the device of the user can be controlled to display content based on the target display parameter, so that the screen display of the device is suitable for the current state of the user and protects the user's eyes.

[0112] In some embodiments, the blue band of the color may be changed by adjusting the hue of the color.

[0113] In some embodiments, the hue of the color may be adjusted to achieve color conversion.

[0114] In some embodiments, the contrast can be varied via a tone mapping curve.

[0115] In some embodiments, the enhancement strength of large edges and texture parts can be dynamically adjusted through high-frequency and low-frequency information, thereby achieving sharpness adjustment.

[0116] In some embodiments, resolution scaling can be performed by traditional interpolation, or artificial intelligence super-resolution.

[0117] In order to implement the above embodiment, the present disclosure also proposes a device for determining display parameters.

[0118] Figure 5 A schematic diagram of the structure of a device for determining display parameters provided in an embodiment of the present disclosure.

[0119] like Figure 5 As shown, the display parameter determination device 500 may include:

[0120] A first determination module 501 is used to determine a first probability that the target user belongs to each preset age group according to the facial image and voice information of the target user;

[0121] A second determination module 502, configured to determine a second probability that the target user belongs to each preset fatigue level according to the video data corresponding to the eye area of ​​the target user;

[0122] The third determination module 503 is used to determine the target display parameters corresponding to the target user according to the first probability, the second probability and the first display parameters, wherein users of each preset age group correspond to a set of first display parameters at each preset fatigue level.

[0123] In some embodiments, the third determining module 503 is configured to:

[0124] Based on the first probability that the target user belongs to each preset age group, a plurality of first display parameters corresponding to each preset age group at the same preset fatigue level are merged to determine the second display parameters corresponding to the target user at each preset fatigue level;

[0125] Based on the second probabilities, the second display parameters corresponding to the target user at each preset fatigue level are fused to determine the target display parameters.

[0126] In some embodiments, the third determining module 503 is configured to:

[0127] Determine the preset age group corresponding to the first probabilities with the largest first number as the first age group, wherein the first number is an integer greater than 1 and less than the total number of the preset age groups;

[0128] Determine a first weight corresponding to each first age group based on the first probability corresponding to each first age group;

[0129] Based on the first weights corresponding to the first age groups, the first display parameters corresponding to the first age groups at the same preset fatigue level are merged to determine the second display parameters corresponding to the target users at the preset fatigue levels;

[0130] Based on the second probabilities, the second display parameters corresponding to the target user at each preset fatigue level are fused to determine the target display parameters.

[0131] In some embodiments, the third determining module 503 is configured to:

[0132] Determine the preset fatigue levels corresponding to the second probabilities with the largest second number as the first fatigue level, wherein the value of the second number is an integer greater than 1 and less than the total number of preset fatigue levels;

[0133] Determining second weights corresponding to the first fatigue levels based on second probabilities corresponding to the first fatigue levels;

[0134] Based on the second weights corresponding to the first fatigue levels, the second display parameters corresponding to the target user at the first fatigue levels are integrated to determine the target display parameters.

[0135] In some embodiments, the third determining module 503 is configured to:

[0136] Determine the preset age group with the highest first probability as the second age group to which the target user belongs;

[0137] Determine the preset fatigue level with the second highest probability as the second fatigue level to which the target user belongs;

[0138] The first display parameter corresponding to the user of the second age group at the second fatigue level is determined as the target display parameter.

[0139] In some embodiments, an update module is further included, which is used to:

[0140] In the case where the target user has color vision deficiency, the target display parameters are updated based on the color vision deficiency type of the target user.

[0141] In some embodiments, the update module is used to:

[0142] When the color vision impairment type of the target user is color blindness, determining a third probability that the target user is color blind and a fourth probability that the target user is not color blind, wherein the third probability is greater than the fourth probability;

[0143] Based on the third probability and the fourth probability, the third display parameter corresponding to the color weakness under the current ambient brightness and the target display parameter are fused to obtain updated target display parameters.

[0144] In some embodiments, the update module is used to:

[0145] Determining recognition results of a third number of first images by the target user, wherein the first images are used to identify whether the user has color blindness;

[0146] Determine a fourth number corresponding to the first image whose recognition result is an incorrect recognition, and a fifth number corresponding to the first image whose recognition result is a correct recognition;

[0147] determining a ratio of the fourth quantity to the third quantity as a third probability;

[0148] The ratio of the fifth number to the fourth number is determined as a fourth probability.

[0149] In some embodiments, the update module is used to:

[0150] In the case where the color vision impairment type of the target user is color blindness, determining the color blindness type corresponding to the target user;

[0151] Determine the color to be converted and the converted color corresponding to the color blindness type;

[0152] The target display parameters are updated based on the color to be converted and the converted color.

[0153] In some embodiments, a display module is further included for:

[0154] The target user's device is controlled to display content based on the target display parameters.

[0155] The functions and specific implementation principles of the above modules in the embodiments of the present disclosure can be referred to the above method embodiments, and will not be repeated here.

[0156] The display parameter determination device of the disclosed embodiment first determines the first probability that the target user belongs to each preset age group and the second probability that the target user belongs to each preset fatigue level, and then determines the target display parameter corresponding to the target user according to the first probability, the second probability and the first display parameter. Thus, the display parameter of the target user can be determined according to the two dimensions of the age and fatigue level of the target user, and the display parameter is adaptively adjusted according to the personalized information of the user, so that the determined target display parameter is more suitable for the current state of the target user, thereby protecting the user's eyes.

[0157] In order to implement the above embodiments, the present disclosure further proposes an electronic device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, the method for determining display parameters proposed in the above embodiments of the present disclosure is implemented.

[0158] Figure 6A block diagram of an exemplary electronic device suitable for implementing embodiments of the present disclosure is shown. Figure 6 The electronic device 12 shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.

[0159] like Figure 6 As shown, the electronic device 12 is in the form of a general purpose computing device. The components of the electronic device 12 may include, but are not limited to: one or more processors or processing units 16, a system memory 28, and a bus 18 that connects various system components (including the system memory 28 and the processing unit 16).

[0160] The bus 18 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, a graphics acceleration port, a processor or a local bus using any of a variety of bus structures. For example, these architectures include but are not limited to Industry Standard Architecture (ISA) bus, Micro Channel Architecture (MAC) bus, Enhanced ISA bus, Video Electronics Standards Association (VESA) local bus and Peripheral Component Interconnection (PCI) bus.

[0161] The electronic device 12 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by the electronic device 12, including volatile and non-volatile media, removable and non-removable media.

[0162] The memory 28 may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 30 and / or cache memory 32. The electronic device 12 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, the storage system 34 may be used to read and write non-removable, non-volatile magnetic media ( Figure 6 not shown, usually called a "hard drive"). Although Figure 6Not shown in the figure, a disk drive for reading and writing a removable non-volatile disk (e.g., a "floppy disk"), and an optical disk drive for reading and writing a removable non-volatile optical disk (e.g., a compact disc read only memory (CD-ROM), a digital versatile disc read only memory (DVD-ROM), or other optical media) may be provided. In these cases, each drive may be connected to the bus 18 via one or more data medium interfaces. The memory 28 may include at least one program product having a set (e.g., at least one) of program modules configured to perform the functions of the various embodiments of the present disclosure.

[0163] A program / utility 40 having a set (at least one) of program modules 42 may be stored, for example, in the memory 28, such program modules 42 including but not limited to an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment. The program modules 42 generally perform the functions and / or methods of the embodiments described in the present disclosure.

[0164] The electronic device 12 may also communicate with one or more external devices 14 (e.g., keyboards, pointing devices, displays 24, etc.), may also communicate with one or more devices that enable a user to interact with the electronic device 12, and / or may communicate with any device that enables the electronic device 12 to communicate with one or more other computing devices (e.g., network cards, modems, etc.). Such communication may be performed via an input / output (I / O) interface 22. Furthermore, the electronic device 12 may also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) via a network adapter 20. As shown, the network adapter 20 communicates with other modules of the electronic device 12 via a bus 18. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with the electronic device 12, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0165] The processing unit 16 executes various functional applications and data processing by running programs stored in the system memory 28, such as implementing the methods mentioned in the above embodiments.

[0166] In order to implement the above embodiments, the present disclosure further proposes a chip, including: the chip includes a processing circuit, and the processing circuit is configured to execute the display parameter determination method provided by the above embodiments.

[0167] Figure 7 is a schematic diagram of the structure of the chip proposed in the embodiment of the present disclosure. Figure 7 The structure of the chip 700 is shown, but is not limited to this.

[0168] The chip 700 includes a processing circuit 701 , and the processing circuit 701 is configured to execute any of the above methods.

[0169] In some embodiments, the chip 700 further includes one or more interface circuits 702. Optionally, the interface circuit 702 is connected to the memory 703, and the interface circuit 702 can be used to receive signals from the memory 703 or other devices, and the interface circuit 702 can be used to send signals to the memory 703 or other devices. For example, the interface circuit 702 can read instructions stored in the memory 703 and send the instructions to the processing circuit 701.

[0170] In some embodiments, the interface circuit 702 performs at least one of the communication steps such as sending and / or receiving in the above method, and the processing circuit 701 performs other steps.

[0171] In some embodiments, terms such as interface circuit, interface, transceiver pin, and transceiver may be used interchangeably.

[0172] In some embodiments, the chip 700 further includes one or more memories 703 for storing instructions. Optionally, all or part of the memory 703 may be outside the chip 700.

[0173] In order to implement the above embodiments, the present disclosure further proposes a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, the method for determining display parameters proposed in the above embodiments of the present disclosure is implemented.

[0174] The collection, storage, use, processing, transmission, provision and disclosure of user personal information involved in this disclosure shall comply with the relevant laws and regulations and shall not violate public order and good morals.

[0175] It should be noted that personal information from users should be collected for legitimate and reasonable purposes and should not be shared or sold outside of these legitimate uses. In addition, such collection / sharing should be carried out after receiving the user's informed consent, including but not limited to notifying the user to read the user agreement / user notice and sign the agreement / authorization including authorization of relevant user information before the user uses the function. In addition, any necessary steps should be taken to protect and safeguard access to such personal information data and ensure that others who have access to personal information data comply with its privacy policy and procedures.

[0176] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present disclosure. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0177] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the features. In the description of the present disclosure, "plurality" means at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0178] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code that includes one or more executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present disclosure includes additional implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present disclosure belong.

[0179] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute the instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purpose of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or processing in other suitable ways if necessary, and then stored in a computer memory.

[0180] It should be understood that the various parts of the present disclosure can be implemented in hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one of the following technologies known in the art or a combination thereof can be used to implement: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0181] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0182] In addition, each functional unit in each embodiment of the present disclosure may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0183] The storage medium mentioned above may be a read-only memory, a disk or an optical disk, etc. Although the embodiments of the present disclosure have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limitations of the present disclosure. A person of ordinary skill in the art may change, modify, replace and modify the above embodiments within the scope of the present disclosure.

Claims

1. A method for determining display parameters, characterized in that: The method comprises: Determining, based on the facial image and voice information of the target user, a first probability that the target user belongs to each preset age group; determining, according to the video data corresponding to the eye area of ​​the target user, a second probability that the target user belongs to each preset fatigue level; The target display parameters corresponding to the target user are determined according to the first probability, the second probability and the first display parameters, wherein users of each preset age group correspond to a set of first display parameters at each preset fatigue level.

2. The method according to claim 1, characterized in that: The determining, according to the first probability, the second probability and the first display parameter, a target display parameter corresponding to the target user includes: Based on the first probability that the target user belongs to each preset age group, a plurality of first display parameters corresponding to each preset age group at the same preset fatigue level are merged to determine the second display parameters corresponding to the target user at each preset fatigue level; Based on each of the second probabilities, the second display parameters corresponding to the target user at each preset fatigue level are fused to determine the target display parameters.

3. The method according to claim 1, characterized in that The determining, according to the first probability, the second probability and the first display parameter, a target display parameter corresponding to the target user includes: Determine the preset age group corresponding to the first probabilities having the largest first number as the first age group, wherein the first number is an integer greater than 1 and less than the total number of the preset age groups; Determining a first weight corresponding to each of the first age groups based on a first probability corresponding to each of the first age groups; Based on the first weights corresponding to the first age groups, the first display parameters corresponding to the first age groups at the same preset fatigue level are merged to determine the second display parameters corresponding to the target user at each preset fatigue level; Based on each of the second probabilities, the second display parameters corresponding to the target user at each preset fatigue level are fused to determine the target display parameters.

4. The method according to claim 2 or 3, characterized in that: The step of fusing the second display parameters corresponding to the target user at each preset fatigue level based on each of the second probabilities to determine the target display parameter includes: Determine the preset fatigue levels corresponding to the second probabilities having the largest second number as the first fatigue level, wherein the value of the second number is an integer greater than 1 and less than the total number of the preset fatigue levels; determining, based on second probabilities corresponding to respective first fatigue levels, second weights corresponding to respective first fatigue levels; Based on the second weights corresponding to the first fatigue levels, the second display parameters corresponding to the target user at the first fatigue levels are fused to determine the target display parameters.

5. The method according to claim 1, characterized in that The determining, according to the first probability, the second probability and the first display parameter, a target display parameter corresponding to the target user includes: Determine the preset age group with the highest first probability as the second age group to which the target user belongs; Determining the preset fatigue level with the second highest probability as the second fatigue level to which the target user belongs; The first display parameter corresponding to the user of the second age group at the second fatigue level is determined as the target display parameter.

6. The method according to claim 1, characterized in that After determining the target display parameter corresponding to the target user according to the first probability, the second probability and the first display parameter, the method further includes: In the case that the target user has color vision deficiency, the target display parameter is updated based on the color vision deficiency type of the target user.

7. The method according to claim 6, characterized in that The updating of the target display parameter based on the color vision impairment type of the target user includes: In a case where the color vision impairment type of the target user is color blindness, determining a third probability that the target user is color blind and a fourth probability that the target user is not color blind, wherein the third probability is greater than the fourth probability; Based on the third probability and the fourth probability, the third display parameter corresponding to the color weakness under the current ambient brightness and the target display parameter are fused to obtain an updated target display parameter.

8. The method according to claim 7, characterized in that The determining a third probability that the target user is color-blind and a fourth probability that the target user is not color-blind includes: Determining recognition results of the target user for a third number of first images, wherein the first images are used to identify whether the user is color blind; Determine a fourth number corresponding to the first image whose recognition result is an incorrect recognition, and a fifth number corresponding to the first image whose recognition result is a correct recognition; determining a ratio of the fourth number to the third number as the third probability; The ratio of the fifth number to the fourth number is determined as the fourth probability.

9. The method according to claim 6, characterized in that The updating of the target display parameter based on the color vision impairment type of the target user includes: In a case where the color vision impairment type of the target user is color blindness, determining the color blindness type corresponding to the target user; Determine the color to be converted and the converted color corresponding to the color blindness type; The target display parameter is updated based on the color to be converted and the converted color.

10. The method according to any one of claims 1 to 9, characterized in that: After determining the target display parameter corresponding to the target user according to the first probability, the second probability and the first display parameter, the method further includes: The device of the target user is controlled to display content based on the target display parameter.

11. A device for determining display parameters, characterized in that: The device comprises: A first determination module, used to determine a first probability that the target user belongs to each preset age group according to the facial image and voice information of the target user; A second determination module, configured to determine, based on the video data corresponding to the eye area of ​​the target user, a second probability that the target user belongs to each preset fatigue level; The third determination module is used to determine the target display parameters corresponding to the target user according to the first probability, the second probability and the first display parameters, wherein users of each preset age group correspond to a set of first display parameters at each preset fatigue level.

12. An electronic device, characterized in that: The invention comprises a memory, a processor and a computer program stored in the memory and executable on the processor. When the processor executes the program, the method for determining the display parameters as claimed in any one of claims 1 to 10 is implemented.

13. A chip, characterized in that: The chip comprises a processing circuit, and the processing circuit is configured to execute the method for determining display parameters as claimed in any one of claims 1-10.

14. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the method for determining display parameters as described in any one of claims 1 to 10 is implemented.

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