Active eye protection display screen control method, device and electronic equipment

Abstract

The present application discloses a display screen control method, device and electronic device for active eye protection, which detects and collects real-time changes in ambient light intensity using sensors, and simultaneously obtains screen display parameter data of the display screen, such as screen brightness value, and combines a deep learning algorithm to perform a temporal responsiveness correlation analysis on the ambient light intensity data and the screen display parameter data, thereby exploring the adaptability and implicit interaction features between the ambient light mode of the current scene and the screen display brightness, thereby adaptively controlling the changes in screen brightness to achieve the purpose of active eye protection of the display screen.

Description

Technical Field

[0001] The present application relates to the field of intelligent control, and more specifically, to a display screen control method, device and electronic device for active eye protection. Background Art

[0002] When using existing computers, the parameters of the screen brightness, contrast, etc. are usually fixed. If the user feels uncomfortable, the user needs to manually operate the buttons on the display screen to adjust, which is inconvenient. Furthermore, if the light conditions in the user's environment change significantly, the user needs to make multiple adjustments, which will cause the user to feel uncomfortable.

[0003] Therefore, a display screen control method, device and electronic device with active eye protection are desired. Summary of the invention

[0004] In order to solve the above technical problems, this application is proposed. The embodiments of this application provide a display screen control method, device and electronic device for active eye protection, which uses sensors to detect and collect real-time changes in ambient light intensity, and simultaneously obtains screen display parameter data of the display screen such as screen brightness value, and combines deep learning algorithms to perform temporal responsiveness correlation analysis on ambient light intensity data and screen display parameter data, and explores the adaptability and implicit interaction characteristics between the ambient light mode of the current scene and the screen display brightness, thereby adaptively controlling the change of screen brightness to achieve the purpose of active eye protection of the display screen.

[0005] According to one aspect of the present application, a display screen control method for active eye protection is provided, which includes:

[0006] Get the time series of ambient light intensity values ​​collected by the sensor;

[0007] Acquire a time series of screen display parameters of the display screen, wherein the screen display parameters include a screen brightness value;

[0008] Performing common space mode association mapping conversion on the time series of the ambient light intensity value and the time series of the screen display parameter to obtain a time-domain spatial covariance matrix of the ambient light intensity and a time-domain spatial covariance matrix of the screen brightness;

[0009] Performing time series pattern feature filtering on the time-domain spatial covariance matrix of the ambient light intensity and the time-domain spatial covariance matrix of the screen brightness to obtain a time series correlation feature vector of the ambient light intensity and a time series correlation feature vector of the screen brightness;

[0010] The ambient light intensity time series correlation feature vector and the screen brightness time series correlation feature vector are passed through a nonlinear response interaction optimization module to obtain an ambient light intensity-screen brightness time series interaction implicit feature vector;

[0011] A control instruction for screen brightness is determined based on the ambient light intensity-screen brightness timing interaction implicit feature vector.

[0012] According to another aspect of the present application, there is provided a display screen control device for active eye protection, comprising:

[0013] An ambient light intensity acquisition module is used to acquire a time series of ambient light intensity values ​​collected by a sensor;

[0014] A screen display parameter acquisition module, used to acquire a time series of screen display parameters of the display screen, wherein the screen display parameters include a screen brightness value;

[0015] An association mapping conversion module, used for performing common space mode association mapping conversion on the time series of the ambient light intensity value and the time series of the screen display parameter to obtain a time domain spatial covariance matrix of the ambient light intensity and a time domain spatial covariance matrix of the screen brightness;

[0016] A time series pattern feature filtering module, used for performing time series pattern feature filtering on the time-domain spatial covariance matrix of the ambient light intensity and the time-domain spatial covariance matrix of the screen brightness to obtain a time series correlation feature vector of the ambient light intensity and a time series correlation feature vector of the screen brightness;

[0017] A nonlinear response interaction optimization module, used for obtaining an ambient light intensity-screen brightness timing interaction implicit feature vector by passing the ambient light intensity timing association feature vector and the screen brightness timing association feature vector through the nonlinear response interaction optimization module;

[0018] A control instruction generation module is used to determine the control instruction of the screen brightness based on the implicit feature vector of the ambient light intensity-screen brightness timing interaction.

[0019] According to another aspect of the present application, there is provided an electronic device, comprising:

[0020] processor;

[0021] A memory, in which computer program instructions are stored, and when the computer program instructions are executed by the processor, the processor executes the aforementioned active eye protection display screen control method.

[0022] Compared with the prior art, the present application provides a display screen control method, device and electronic device with active eye protection, which uses sensors to detect and collect real-time changes in ambient light intensity, and simultaneously obtains screen display parameter data of the display screen, such as screen brightness value, and combines deep learning algorithms to perform temporal responsiveness correlation analysis on ambient light intensity data and screen display parameter data, and explores the adaptability and implicit interaction characteristics between the ambient light mode of the current scene and the screen display brightness, thereby adaptively controlling changes in screen brightness to achieve the purpose of active eye protection of the display screen. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] By describing the embodiments of the present application in more detail in conjunction with the accompanying drawings, the above and other purposes, features and advantages of the present application will become more apparent. The accompanying drawings are used to provide a further understanding of the embodiments of the present application and constitute a part of the specification. Together with the embodiments of the present application, they are used to explain the present application and do not constitute a limitation of the present application. In the accompanying drawings, the same reference numerals generally represent the same components or steps.

[0024] Figure 1 is a flow chart of a display screen control method for active eye protection according to an embodiment of the present application;

[0025] Figure 2 A system architecture diagram of a display screen control method for active eye protection according to an embodiment of the present application;

[0026] Figure 3 is a flowchart of sub-step S3 of the display screen control method for active eye protection according to an embodiment of the present application;

[0027] Figure 4 is a flowchart of sub-step S5 of the active eye protection display screen control method according to an embodiment of the present application;

[0028] Figure 5 is a block diagram of a display screen control device for active eye protection according to an embodiment of the present application;

[0029] Figure 6 is a block diagram of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0030] Below, the exemplary embodiments according to the present application will be described in detail with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments of the present application, and it should be understood that the present application is not limited to the exemplary embodiments described here.

[0031] As shown in this application, unless the context clearly indicates an exception, the words "a", "an", "an" and / or "the" do not refer to the singular, but also include the plural. Generally speaking, the terms "include" and "comprise" only indicate the inclusion of the steps and elements that have been clearly identified, and these steps and elements do not constitute an exclusive list, and the method or device may also include other steps or elements.

[0032] Although the present application makes various references to certain modules in the system according to the embodiments of the present application, any number of different modules can be used and run on the user terminal and / or server. The modules are only illustrative, and different aspects of the system and method can use different modules.

[0033] Flowcharts are used in the present application to illustrate the operations performed by the system according to the embodiments of the present application. It should be understood that the preceding or following operations are not necessarily performed accurately in order. On the contrary, various steps may be processed in reverse order or simultaneously as required. Meanwhile, other operations may also be added to these processes, or a certain step or several steps of operations may be removed from these processes.

[0034] Below, the exemplary embodiments according to the present application will be described in detail with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments of the present application, and it should be understood that the present application is not limited to the exemplary embodiments described here.

[0035] In the technical solution of the present application, a display screen control method for active eye protection is proposed. Figure 1 The figure is a flow chart of a display screen control method for active eye protection according to an embodiment of the present application. Figure 2 FIG. 1 is a system architecture diagram of a display screen control method for active eye protection according to an embodiment of the present application. Figure 1 and Figure 2 As shown, the active eye protection display screen control method according to an embodiment of the present application includes the steps of:

[0036] S1, obtaining the time series of ambient light intensity values ​​collected by the sensor;

[0037] S2, obtaining a time series of screen display parameters of the display screen, wherein the screen display parameters include a screen brightness value;

[0038] S3, performing common space pattern association mapping conversion on the time series of the ambient light intensity value and the time series of the screen display parameter to obtain a time-domain spatial covariance matrix of the ambient light intensity and a time-domain spatial covariance matrix of the screen brightness;

[0039] S4, performing time series pattern feature filtering on the time-domain spatial covariance matrix of the ambient light intensity and the time-domain spatial covariance matrix of the screen brightness to obtain a time series correlation feature vector of the ambient light intensity and a time series correlation feature vector of the screen brightness;

[0040] S5, the ambient light intensity time series correlation feature vector and the screen brightness time series correlation feature vector are subjected to a nonlinear response interaction optimization module to obtain an ambient light intensity-screen brightness time series interaction implicit feature vector;

[0041] S6, determining a control instruction for screen brightness based on the ambient light intensity-screen brightness timing interaction implicit feature vector.

[0042] In particular, the S1 obtains the time series of ambient light intensity values ​​collected by the sensor. Here, the time series of ambient light intensity values ​​collected by the sensor is the basis for realizing real-time monitoring and analysis of ambient light conditions, so that the screen brightness can be further dynamically adjusted based on the current light intensity to meet the user's vision protection needs and provide a comfortable viewing experience. In an embodiment of the present application, the sensor can be a photosensitive sensor (Photodiode) and an ambient light sensor (Ambient Light Sensor, ALS).

[0043] In particular, the step S2 obtains a time series of screen display parameters of the display screen, wherein the screen display parameters include a screen brightness value. It should be understood that obtaining a time series of screen display parameters can provide real-time data about the current state of the screen, which is necessary for quickly responding to environmental changes and user behavior.

[0044] In particular, the S3 performs common space pattern association mapping conversion on the time series of the ambient light intensity values ​​and the time series of the screen display parameters to obtain the time-domain spatial covariance matrix of the ambient light intensity and the time-domain spatial covariance matrix of the screen brightness.

[0045] In particular, in a specific example of the present application, Figure 3 As shown, the S3 includes: S31, arranging the time series of the ambient light intensity value and the time series of the screen display parameters according to the time dimension respectively to obtain the ambient light intensity timing input vector and the screen brightness timing input vector; S32, calculating the spatial covariance matrix of the ambient light intensity timing input vector and the screen brightness timing input vector to obtain the ambient light intensity time-domain spatial covariance matrix and the screen brightness time-domain spatial covariance matrix.

[0046] Specifically, the S31 arranges the time series of the ambient light intensity values ​​and the time series of the screen display parameters respectively according to the time dimension to obtain the ambient light intensity time series input vector and the screen brightness time series input vector. In the technical solution of the present application, arranging the time series of the ambient light intensity values ​​and the time series of the screen display parameters respectively according to the time dimension can convert the discretely distributed time series data into a structured vector representation, so that various network models based on deep learning algorithms can be applied later. At the same time, this arrangement method according to the time dimension can also retain the time series information of the ambient light intensity and the screen display parameters, which is helpful to understand the dynamic time series fluctuations and change patterns of the light intensity and screen brightness.

[0047] Specifically, the S32 calculates the spatial covariance matrix of the ambient light intensity time series input vector and the screen brightness time series input vector to obtain the ambient light intensity time domain spatial covariance matrix and the screen brightness time domain spatial covariance matrix. In the technical solution of the present application, the time-dependent correlation relationship in the ambient light intensity time series input vector and the screen brightness time series input vector is extracted respectively by calculating the spatial covariance matrix. Specifically, since the ambient light intensity data and the screen brightness time series data present a complex correlation pattern in the time dimension and do not exist independently, the calculation of the spatial covariance matrix can reveal and describe the fluctuation characteristics in the time series data, that is, reveal how the ambient light intensity changes with time and how the screen brightness changes with time and how there is a correlation.

[0048] In a specific example of the present application, the encoding process of calculating the spatial covariance matrix of the ambient light intensity timing input vector to obtain the ambient light intensity time-domain spatial covariance matrix is: after calculating the ambient light intensity timing input vector and the transposed vector of the ambient light intensity timing input vector to obtain the ambient light intensity related mapping projection matrix, the ambient light intensity related mapping projection matrix is ​​divided by the trace of the ambient light intensity related mapping projection matrix to obtain the ambient light intensity time-domain spatial covariance matrix, wherein the trace of the ambient light intensity related mapping projection matrix is ​​the sum of the diagonal elements in the ambient light intensity related mapping projection matrix. In a specific example, the spatial covariance matrix of the ambient light intensity timing input vector and the screen brightness timing input vector is calculated by the following formula to obtain the ambient light intensity time-domain spatial covariance matrix and the screen brightness time-domain spatial covariance matrix; wherein the formula is:

[0049]

[0050] in, is the ambient light intensity timing input vector, is the transposed vector of the ambient light intensity timing input vector, is the trace of the projection matrix of the ambient light intensity related mapping, is the time-domain spatial covariance matrix of the ambient light intensity.

[0051] It is worth mentioning that in other specific examples of the present application, the time series of the ambient light intensity values ​​and the time series of the screen display parameters can also be converted into a common space pattern association mapping in other ways to obtain the ambient light intensity time-domain spatial covariance matrix and the screen brightness time-domain spatial covariance matrix, for example: input the time series of the ambient light intensity values ​​and the time series of the screen display parameters; map the time series of the ambient light intensity values ​​and the time series of the screen display parameters to the same space through the common space pattern association mapping conversion; calculate the time domain spatial covariance matrix of the ambient light intensity and the time domain spatial covariance matrix of the screen brightness in the common space to describe the time domain relationship between them; to obtain the ambient light intensity time domain spatial covariance matrix and the screen brightness time domain spatial covariance matrix.

[0052] In particular, the S4 performs temporal pattern feature filtering on the time-domain spatial covariance matrix of the ambient light intensity and the time-domain spatial covariance matrix of the screen brightness to obtain the time-series correlation feature vector of the ambient light intensity and the time-series correlation feature vector of the screen brightness. In particular, in a specific example of the present application, the time-domain spatial covariance matrix of the ambient light intensity and the time-domain spatial covariance matrix of the screen brightness are filtered through a temporal pattern feature filter based on a hole convolution layer to obtain the time-series correlation feature vector of the ambient light intensity and the time-series correlation feature vector of the screen brightness. Among them, the hole convolution layer can capture local patterns and long-distance dependencies in time series data, which is crucial for understanding the dynamic characteristics of time series data. Specifically, compared with traditional convolution layers, hole convolution allows the receptive field of feature extraction to be increased without increasing the amount of computation, which means that the model can capture dependencies between farther time steps to enrich the expression of the time-domain distribution characteristics of ambient light intensity and the time-domain distribution characteristics of screen brightness.

[0053] In particular, in S5, the time-series correlation feature vector of the ambient light intensity and the time-series correlation feature vector of the screen brightness are passed through a nonlinear response interaction optimization module to obtain an ambient light intensity-screen brightness time-series interaction implicit feature vector. It should be understood that in order to be able to adaptively adjust the screen brightness of the current display screen according to the real-time ambient light conditions, the complex relationship between the ambient light intensity and the actual screen brightness of the display screen should also be understood. For example, in an actual application scenario, the user of the display screen may set the screen brightness (the actual screen brightness of the display screen) according to personal preferences, and the acceptance of changes in ambient light is high. What is more complicated is that the user's screen brightness preference may change over time, such as at different times of the day or between different activities. Therefore, in order to be able to more intelligently learn how to adjust the screen brightness of the display screen to the most appropriate place, in the technical solution of the present application, the time-series correlation feature vector of the ambient light intensity and the time-series correlation feature vector of the screen brightness are further passed through a nonlinear response interaction optimization module to obtain an ambient light intensity-screen brightness time-series interaction implicit feature vector. In this way, the complex nonlinear relationship between ambient light intensity and screen brightness is captured and modeled through a nonlinear response interaction optimization module, rather than directly using a simple linear model to characterize and express it.

[0054] In particular, in a specific example of the present application, Figure 4 As shown, the S5 includes:

[0055] S51, fusing the ambient light intensity time series correlation feature vector and the screen brightness time series correlation feature vector to obtain an ambient light intensity-screen brightness time series correlation fusion vector;

[0056] S52, constructing a first ambient light intensity-screen brightness nonlinear response factor and a second ambient light intensity-screen brightness nonlinear response factor based on the ambient light intensity-screen brightness time series associated fusion vector;

[0057] S53: Divide the first ambient light intensity-screen brightness nonlinear response factor by the second ambient light intensity-screen brightness nonlinear response factor to obtain the ambient light intensity-screen brightness temporal interaction implicit feature vector.

[0058] Specifically, the S51 is to fuse the ambient light intensity timing correlation feature vector and the screen brightness timing correlation feature vector to obtain an ambient light intensity-screen brightness timing correlation fusion vector. In a specific example, the positional division of the ambient light intensity timing correlation feature vector and the screen brightness timing correlation feature vector is calculated to obtain the ambient light intensity-screen brightness timing correlation fusion vector.

[0059] Specifically, in S52, a first ambient light intensity-screen brightness nonlinear response factor and a second ambient light intensity-screen brightness nonlinear response factor are constructed based on the ambient light intensity-screen brightness temporal correlation fusion vector.

[0060] In a specific example, first, the weighted sum of the quadratic term of the ambient light intensity-screen brightness timing association fusion vector and its linear term is calculated to obtain the first ambient light intensity-screen brightness nonlinear response factor; then the weighted sum of the quadratic term of the ambient light intensity-screen brightness timing association fusion vector, the linear term of the ambient light intensity-screen brightness timing association fusion vector and one is calculated to obtain the second ambient light intensity-screen brightness nonlinear response factor.

[0061] Specifically, in S53, the first ambient light intensity-screen brightness nonlinear response factor is divided by the second ambient light intensity-screen brightness nonlinear response factor to obtain the ambient light intensity-screen brightness time series interaction implicit feature vector. It should be understood that by dividing the first ambient light intensity-screen brightness nonlinear response factor by the second ambient light intensity-screen brightness nonlinear response factor, a new factor can be obtained, which reflects the change ratio of the first factor relative to the second factor, which helps to better understand the interaction between the two.

[0062] In summary, in the above embodiment, the ambient light intensity timing correlation feature vector and the screen brightness timing correlation feature vector are subjected to a nonlinear response interaction optimization module to obtain an ambient light intensity-screen brightness timing interaction implicit feature vector, including: using a nonlinear response interaction optimization module to perform nonlinear response interaction optimization on the ambient light intensity timing correlation feature vector and the screen brightness timing correlation feature vector using the following formula to obtain the ambient light intensity-screen brightness timing interaction implicit feature vector; wherein the formula is:

[0063]

[0064] in, and are respectively the time series correlation feature vector of the ambient light intensity and the time series correlation feature vector of the screen brightness. The value of the position, , , and The hyperparameters are adjusted for responses with different values, is the implicit feature vector of the ambient light intensity-screen brightness temporal interaction The value of the position.

[0065] It is worth mentioning that in other specific examples of the present application, the ambient light intensity time-series correlation feature vector and the screen brightness time-series correlation feature vector can also be optimized through a nonlinear response interaction module in other ways to obtain an ambient light intensity-screen brightness time-series interaction implicit feature vector, for example: input the ambient light intensity time-series correlation feature vector and the screen brightness time-series correlation feature vector; through nonlinear response interaction optimization, the time-series correlation feature vectors of ambient light intensity and screen brightness are interacted to obtain a more representative ambient light intensity-screen brightness time-series interaction implicit feature vector; in the optimization module, nonlinear response functions such as ReLU, Sigmoid, etc. are introduced to perform nonlinear transformation on the feature vectors of ambient light intensity and screen brightness to capture more complex feature relationships; through interaction, concatenation, dot multiplication, addition, etc. can be used to obtain the interaction characteristics between them; through the iterative process of the optimization module, the interaction relationship between the feature vectors is continuously adjusted to maximize the implicit feature representation between the ambient light intensity and the screen brightness, improve the performance and generalization ability of the model, and obtain the ambient light intensity-screen brightness time-series interaction implicit feature vector.

[0066] In particular, the S6 determines the control instruction of the screen brightness based on the ambient light intensity-screen brightness timing interaction implicit feature vector. In particular, in a specific example of the present application, the ambient light intensity-screen brightness timing interaction implicit feature vector is passed through a classifier-based screen brightness adaptive controller to obtain a control instruction, and the control instruction is used to indicate that the screen brightness value should increase, decrease, or remain unchanged. Specifically, the ambient light intensity-screen brightness timing interaction implicit feature vector is fully connected encoded using multiple fully connected layers of the classifier to obtain an encoded classification feature vector; and the encoded classification feature vector is passed through the Softmax classification function of the classifier to obtain the classification result.

[0067] In a preferred example, the ambient light intensity-screen brightness timing interaction implicit feature vector is passed through a classifier-based screen brightness adaptive controller to obtain a control instruction, including the following steps: performing a dot addition on the ambient light intensity-screen brightness timing interaction implicit feature vector and the square root of the length of the ambient light intensity-screen brightness timing interaction implicit feature vector and the reciprocal of the square root of the second norm of the ambient light intensity-screen brightness timing interaction implicit feature vector to obtain an ambient light intensity-screen brightness timing interaction offset feature vector; calculating an exponential function of the ambient light intensity-screen brightness timing interaction offset feature vector with a natural constant as the base to obtain an ambient light intensity-screen brightness timing interaction offset feature vector; The invention discloses a method for obtaining an ambient light intensity-screen brightness timing interaction constraint feature vector by performing dot multiplication on the ambient light intensity-screen brightness timing interaction implicit feature vector and a norm and a weight hyperparameter of the ambient light intensity-screen brightness timing interaction implicit feature vector to obtain an ambient light intensity-screen brightness timing interaction constraint feature vector; the ambient light intensity-screen brightness timing interaction offset prediction feature vector and the ambient light intensity-screen brightness timing interaction constraint feature vector are dotted to obtain an optimized ambient light intensity-screen brightness timing interaction implicit feature vector; and the optimized ambient light intensity-screen brightness timing interaction implicit feature vector is passed through a classifier-based screen brightness adaptive controller to obtain a control instruction.

[0068] Specifically, taking into account the local spatial correlation characteristics of the spatial covariance distribution of the ambient light intensity and screen brightness of the ambient light intensity and screen brightness of the implicit feature vector of the time series interaction, the response interaction fusion distribution based on the nonlinear response interaction is based on the overall distribution regression constraint of the classifier, in the above preferred example, the structured norm representation of the ambient light intensity and screen brightness time series interaction implicit feature vector is used as the local canonical coordinates for each eigenvalue of the ambient light intensity and screen brightness time series interaction implicit feature vector to determine the vector overall classification of the ambient light intensity and screen brightness time series interaction implicit feature vector. The cloth represents the class rotation offset relative to the eigenvalue for the class offset prediction direction of each eigenvalue of the ambient light intensity-screen brightness timing interaction implicit feature vector as the center, and uses the bounding box of the vector eigenvalue distribution of the ambient light intensity-screen brightness timing interaction implicit feature vector to perform eigenvalue constraints to improve the constraint of the ambient light intensity-screen brightness timing interaction implicit feature vector under the overall regression distribution, thereby improving the training speed of the model and the accuracy of the control instructions obtained by the ambient light intensity-screen brightness timing interaction implicit feature vector through the classifier-based screen brightness adaptive controller.

[0069] In summary, according to the active eye protection display screen control method of the embodiment of the present application, a sensor is utilized to detect and collect real-time changes in ambient light intensity, and simultaneously obtains screen display parameter data of the display screen, such as the screen brightness value, and combines a deep learning algorithm to perform a timing responsiveness correlation analysis on the ambient light intensity data and the screen display parameter data, thereby exploring the adaptability and implicit interaction characteristics between the ambient light mode of the current scene and the screen display brightness, and thus adaptively controlling the changes in screen brightness to achieve the purpose of active eye protection of the display screen.

[0070] Figure 5 FIG. 1 is a block diagram of a display screen control device for active eye protection according to an embodiment of the present application. Figure 5 As shown, the active eye protection display screen control device 300 according to the embodiment of the present application includes:

[0071] The ambient light intensity acquisition module 310 is used to acquire the time series of ambient light intensity values ​​collected by the sensor;

[0072] A screen display parameter acquisition module 320 is used to acquire a time series of screen display parameters of a display screen, wherein the screen display parameters include screen brightness values; an association mapping conversion module 330 is used to perform a common space mode association mapping conversion on the time series of the ambient light intensity values ​​and the time series of the screen display parameters to obtain a time-domain spatial covariance matrix of the ambient light intensity and a time-domain spatial covariance matrix of the screen brightness;

[0073] A time series pattern feature filtering module 340 is used to perform time series pattern feature filtering on the time-domain spatial covariance matrix of the ambient light intensity and the time-domain spatial covariance matrix of the screen brightness to obtain a time series correlation feature vector of the ambient light intensity and a time series correlation feature vector of the screen brightness;

[0074] A nonlinear response interaction optimization module 350, configured to obtain an ambient light intensity-screen brightness timing interaction implicit feature vector by passing the ambient light intensity timing association feature vector and the screen brightness timing association feature vector through a nonlinear response interaction optimization module;

[0075] The control instruction generation module 360 ​​is used to determine the control instruction of the screen brightness based on the implicit feature vector of the ambient light intensity-screen brightness time sequence interaction.

[0076] As described above, the active eye protection display screen control device 300 according to the embodiment of the present application can be implemented in various wireless terminals, such as a server with an active eye protection display screen control algorithm. In one possible implementation, the active eye protection display screen control device 300 according to the embodiment of the present application can be integrated into the wireless terminal as a software module and / or a hardware module. For example, the active eye protection display screen control device 300 can be a software module in the operating system of the wireless terminal, or it can be an application developed for the wireless terminal; of course, the active eye protection display screen control device 300 can also be one of the many hardware modules of the wireless terminal.

[0077] Alternatively, in another example, the active eye protection display screen control device 300 and the wireless terminal may also be separate devices, and the active eye protection display screen control device 300 may be connected to the wireless terminal via a wired and / or wireless network, and transmit interactive information in accordance with an agreed data format.

[0078] Below, reference Figure 6 To describe an electronic device according to an embodiment of the present application.

[0079] Figure 6 A block diagram of an electronic device according to an embodiment of the present application is illustrated.

[0080] like Figure 6 As shown, the electronic device 10 includes one or more processors 11 and a memory 12 .

[0081] The processor 11 may be a central processing unit (CPU) or other forms of processing units having data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device 10 to perform desired functions.

[0082] The memory 12 may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, random access memory (RAM) and / or cache memory (cache), etc. The non-volatile memory may include, for example, a read-only memory (ROM), a hard disk, a flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage medium, and the processor 11 may run the program instructions to implement the functions of the active eye protection display screen control method of each embodiment of the present application described above and / or other desired functions. Various contents such as the implicit feature vector of the interaction of the ambient light intensity-screen brightness timing may also be stored in the computer-readable storage medium.

[0083] In one example, the electronic device 10 may further include: an input device 13 and an output device 14 , and these components are interconnected via a bus system and / or other forms of connection mechanisms (not shown).

[0084] The input device 13 may include, for example, a keyboard, a mouse, etc.

[0085] The output device 14 can output various information to the outside, including classification results, etc. The output device 14 can include, for example, a display, a speaker, a printer, a communication network and a remote output device connected thereto, and the like.

[0086] Of course, to simplify, Figure 6 Only some of the components related to the present application in the electronic device 10 are shown, and components such as a bus, an input / output interface, etc. are omitted. In addition, according to specific application situations, the electronic device 10 may also include any other appropriate components.

[0087] The embodiments of the present disclosure have been described above, and the above description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and changes will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The selection of terms used herein is intended to best explain the principles of the embodiments, practical applications, or improvements to the technology in the market, or to enable other persons of ordinary skill in the art to understand the embodiments disclosed herein.

Claims

1. A display screen control method for active eye protection, characterized in that: include: Get the time series of ambient light intensity values ​​collected by the sensor; Acquire a time series of screen display parameters of the display screen, wherein the screen display parameters include a screen brightness value; Performing common space mode association mapping conversion on the time series of the ambient light intensity value and the time series of the screen display parameter to obtain a time-domain spatial covariance matrix of the ambient light intensity and a time-domain spatial covariance matrix of the screen brightness; Performing time series pattern feature filtering on the time-domain spatial covariance matrix of the ambient light intensity and the time-domain spatial covariance matrix of the screen brightness to obtain a time series correlation feature vector of the ambient light intensity and a time series correlation feature vector of the screen brightness; The ambient light intensity time series correlation feature vector and the screen brightness time series correlation feature vector are passed through a nonlinear response interaction optimization module to obtain an ambient light intensity-screen brightness time series interaction implicit feature vector; Determine a control instruction for screen brightness based on the ambient light intensity-screen brightness temporal interaction implicit feature vector; Performing a common space mode association mapping conversion on the time series of the ambient light intensity value and the time series of the screen display parameter to obtain a time-domain spatial covariance matrix of the ambient light intensity and a time-domain spatial covariance matrix of the screen brightness, including: Arranging the time series of the ambient light intensity values ​​and the time series of the screen display parameters according to the time dimension respectively to obtain an ambient light intensity time series input vector and a screen brightness time series input vector; Calculating the ambient light intensity time series input vector and the transposed vector of the ambient light intensity time series input vector to obtain an ambient light intensity related mapping projection matrix; Dividing the ambient light intensity correlation mapping projection matrix by the trace of the ambient light intensity correlation mapping projection matrix to obtain the ambient light intensity time-domain spatial covariance matrix, wherein the trace of the ambient light intensity correlation mapping projection matrix is ​​the sum of the diagonal elements in the ambient light intensity correlation mapping projection matrix; The ambient light intensity time series correlation feature vector and the screen brightness time series correlation feature vector are subjected to a nonlinear response interaction optimization module to obtain an ambient light intensity-screen brightness time series interaction implicit feature vector, including: Fusion of the ambient light intensity time series correlation feature vector and the screen brightness time series correlation feature vector to obtain an ambient light intensity-screen brightness time series correlation fusion vector; Constructing a first ambient light intensity-screen brightness nonlinear response factor and a second ambient light intensity-screen brightness nonlinear response factor based on the ambient light intensity-screen brightness temporal correlation fusion vector; The first ambient light intensity-screen brightness nonlinear response factor is divided by the second ambient light intensity-screen brightness nonlinear response factor to obtain the ambient light intensity-screen brightness temporal interaction implicit feature vector.

2. The active eye protection display screen control method according to claim 1, characterized in that: Performing time series pattern feature filtering on the time-domain spatial covariance matrix of the ambient light intensity and the time-domain spatial covariance matrix of the screen brightness to obtain a time series correlation feature vector of the ambient light intensity and a time series correlation feature vector of the screen brightness, including: The ambient light intensity time-domain spatial covariance matrix and the screen brightness time-domain spatial covariance matrix are passed through a temporal pattern feature filter based on a hole convolution layer to obtain the ambient light intensity time-series correlation feature vector and the screen brightness time-series correlation feature vector.

3. The active eye protection display screen control method according to claim 1, characterized in that: The step of fusing the ambient light intensity time series correlation feature vector and the screen brightness time series correlation feature vector to obtain an ambient light intensity-screen brightness time series correlation fusion vector includes: The position-based division of the ambient light intensity time series correlation feature vector and the screen brightness time series correlation feature vector is calculated to obtain the ambient light intensity-screen brightness time series correlation fusion vector.

4. The active eye protection display screen control method according to claim 3, characterized in that: Constructing a first ambient light intensity-screen brightness nonlinear response factor and a second ambient light intensity-screen brightness nonlinear response factor based on the ambient light intensity-screen brightness temporal correlation fusion vector, including: Calculate the weighted sum of the quadratic term and the linear term of the ambient light intensity-screen brightness time series correlation fusion vector to obtain the first ambient light intensity-screen brightness nonlinear response factor; The quadratic term of the ambient light intensity-screen brightness timing correlation fusion vector, the weighted sum of the linear term of the ambient light intensity-screen brightness timing correlation fusion vector and one are calculated to obtain the second ambient light intensity-screen brightness nonlinear response factor.

5. The active eye protection display screen control method according to claim 4, characterized in that: Determining a control instruction for screen brightness based on the ambient light intensity-screen brightness temporal interaction implicit feature vector includes: The ambient light intensity-screen brightness temporal interaction implicit feature vector is passed through a classifier-based screen brightness adaptive controller to obtain the control instruction, and the control instruction is used to indicate whether the screen brightness value should increase, decrease or remain unchanged.

6. A display screen control device for active eye protection, characterized in that: An ambient light intensity acquisition module is used to acquire a time series of ambient light intensity values ​​collected by a sensor; A screen display parameter acquisition module, used to acquire a time series of screen display parameters of the display screen, wherein the screen display parameters include a screen brightness value; An association mapping conversion module, used for performing common space mode association mapping conversion on the time series of the ambient light intensity value and the time series of the screen display parameter to obtain a time domain spatial covariance matrix of the ambient light intensity and a time domain spatial covariance matrix of the screen brightness; A time series pattern feature filtering module, used for performing time series pattern feature filtering on the time-domain spatial covariance matrix of the ambient light intensity and the time-domain spatial covariance matrix of the screen brightness to obtain a time series correlation feature vector of the ambient light intensity and a time series correlation feature vector of the screen brightness; A nonlinear response interaction optimization module, used for obtaining an ambient light intensity-screen brightness timing interaction implicit feature vector by passing the ambient light intensity timing association feature vector and the screen brightness timing association feature vector through the nonlinear response interaction optimization module; A control instruction generation module, used for determining a control instruction for screen brightness based on the ambient light intensity-screen brightness time sequence interaction implicit feature vector; The time series of the ambient light intensity values ​​and the time series of the screen display parameters are subjected to a common space mode association mapping conversion to obtain a time-domain spatial covariance matrix of the ambient light intensity and a time-domain spatial covariance matrix of the screen brightness, including: Arranging the time series of the ambient light intensity values ​​and the time series of the screen display parameters according to the time dimension respectively to obtain an ambient light intensity time series input vector and a screen brightness time series input vector; Calculating the ambient light intensity time series input vector and the transposed vector of the ambient light intensity time series input vector to obtain an ambient light intensity related mapping projection matrix; Dividing the ambient light intensity correlation mapping projection matrix by the trace of the ambient light intensity correlation mapping projection matrix to obtain the ambient light intensity time-domain spatial covariance matrix, wherein the trace of the ambient light intensity correlation mapping projection matrix is ​​the sum of the diagonal elements in the ambient light intensity correlation mapping projection matrix; The ambient light intensity time series correlation feature vector and the screen brightness time series correlation feature vector are subjected to a nonlinear response interaction optimization module to obtain an ambient light intensity-screen brightness time series interaction implicit feature vector, including: Fusion of the ambient light intensity time series correlation feature vector and the screen brightness time series correlation feature vector to obtain an ambient light intensity-screen brightness time series correlation fusion vector; Constructing a first ambient light intensity-screen brightness nonlinear response factor and a second ambient light intensity-screen brightness nonlinear response factor based on the ambient light intensity-screen brightness temporal correlation fusion vector; The first ambient light intensity-screen brightness nonlinear response factor is divided by the second ambient light intensity-screen brightness nonlinear response factor to obtain the ambient light intensity-screen brightness temporal interaction implicit feature vector.

7. An electronic device, characterized in that: include: processor; A memory, in which computer program instructions are stored, and when the computer program instructions are executed by the processor, the processor executes the display screen control method for active eye protection as described in any one of claims 1-5.

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