Touch trajectory prediction method, related device, equipment and computer storage medium

Abstract

The embodiment of the present application provides a touch trajectory prediction method, related devices, equipment and computer storage medium, wherein the touch trajectory prediction method includes: in the process of reporting the sampling point of the user's finger sliding screen position to the application, obtaining the comprehensive reporting information of the current application layer reporting period, the comprehensive reporting information is used to reflect the bottom layer reporting situation and the application layer reporting situation before the last moment of the current application layer reporting period, the bottom layer reporting point refers to the reporting point of the touch screen firmware reporting the touch event, and the application layer reporting point refers to the reporting point reported by the bottom layer to the application layer, and then, determining the target prediction point of the current application layer reporting period according to the comprehensive reporting information. This method expands the correction mechanism of the application layer reporting point, reduces the deviation of the application layer reporting point, and reduces the jitter of the touch screen image caused by the touch operation.

Description

Technical Field

[0001] The present application relates to the field of display technology, and in particular to a touch trajectory prediction method, related devices, equipment and computer storage medium. Background Art

[0002] Touch screen mobile phones report touch point information through the touch screen, and upper-layer applications receive touch events and respond. The system responds by consuming events through vertical synchronization Vsync frame refresh, and displays on the screen to give user feedback. Since the Vsync frame rate is inconsistent with the underlying reporting frame rate, when obtaining events at the Vssync frame time point, the original event reported by the underlying layer may not exist, and an event point report needs to be generated through resampling or prediction.

[0003] In the prior art, resampling and prediction are performed by directly using the frame points reported by the bottom layer to perform linear prediction (interpolation) of two points. This may result in a large deviation in the historical points reported to the application, resulting in a jittery display. Summary of the invention

[0004] The present application discloses a touch trajectory prediction method, related devices, equipment and computer storage medium, which can reduce the deviation of application layer reporting points and reduce the jitter of the touch screen image caused by touch operation.

[0005] In a first aspect, an embodiment of the present application provides a touch trajectory prediction method, comprising:

[0006] In the process of reporting the sampling point of the user's finger sliding screen position to the application, the comprehensive reporting point information of the current application layer reporting period is obtained, and the comprehensive reporting point information is used to reflect the bottom layer reporting point situation and the application layer reporting point situation before the last moment of the current application layer reporting point period. The bottom layer reporting point refers to the reporting point of the touch screen firmware reporting the touch event, and the application layer reporting point refers to the reporting point reported by the bottom layer to the application layer;

[0007] The target prediction point of the current sub-application layer reporting period is determined according to the comprehensive reporting information.

[0008] Through the embodiment of the present application, in the process of reporting the sampling point of the position of the user's finger sliding on the screen to the application, the comprehensive reporting information of the current application layer reporting period is obtained. The comprehensive reporting information is used to reflect the bottom layer reporting situation and the application layer reporting situation before the last moment of the current application layer reporting period. The bottom layer reporting refers to the reporting point of the touch screen firmware reporting the touch event, and the application layer reporting refers to the reporting point reported by the bottom layer to the application layer. After that, the target prediction point of the current application layer reporting period is determined according to the comprehensive reporting information. In other words, the target prediction point of the current application layer reporting period can be determined by analyzing the bottom layer reporting situation and the application layer reporting situation before the last moment of the current application layer reporting period, which expands the correction mechanism of the application layer reporting, reduces the deviation of the application layer reporting, and thus reduces the jitter of the touch screen image caused by the touch operation.

[0009] In combination with the first aspect, in some embodiments, the current sub-application layer reporting period is the nth application layer reporting period, where n is a positive integer greater than or equal to 3; the comprehensive reporting information includes two underlying reporting information of the two historical underlying reporting periods closest to the last moment of the current sub-application layer reporting period, and two application layer reporting information of the two historical application layer reporting periods closest to the last moment of the current sub-application layer reporting period.

[0010] It can be seen that the touch trajectory prediction method starts from the third application layer reporting period, and predicts the application layer reporting point corresponding to the current period by combining the historical bottom layer reporting point information and the historical application layer reporting point information.

[0011] In combination with the first aspect, in some embodiments, determining the target prediction point of the current sub-application layer reporting period based on the comprehensive reporting information includes: determining a first prediction point based on the two underlying reporting information; determining a second prediction point based on the two application layer reporting information; and determining the target prediction point based on the first prediction point and the second prediction point.

[0012] It can be seen that the touch trajectory prediction method can determine the first reference reporting point based on the two historical bottom-level reporting points closest to the last moment of the current sub-application layer reporting cycle, determine the second reference reporting point based on the two historical application layer reporting points closest to the last moment of the current sub-application layer reporting cycle, and then obtain the target prediction point based on the first reference point and the second reference point.

[0013] In combination with the first aspect, in some embodiments, determining the first prediction point based on the two underlying reporting point information includes: determining a first moment and a first reference reporting point based on the two underlying reporting point information, the first moment being the last moment of the historical underlying reporting period that is second closest to the current sub-application layer reporting period, and the first reference reporting point being the underlying reporting point at the first moment; determining a second moment and a second reference reporting point based on the two underlying reporting point information, the second moment being the last moment of the historical underlying reporting period that is closest to the current sub-application layer reporting period, and the second reference point being the underlying reporting point at the second moment; obtaining a third moment, the third moment being the last moment of the current sub-application layer reporting period; determining a first parameter based on the first moment, the second moment and the third moment; determining the first prediction point based on the first reference reporting point, the second reference reporting point and the first parameter.

[0014] It can be seen that the touch trajectory prediction method can determine the first prediction point by analyzing the correspondence between the two historical bottom-layer reporting point information closest to the last moment of the current application layer reporting point cycle and each related moment.

[0015] In combination with the first aspect, in some embodiments, the correspondence between the first moment, the second moment, the third moment and the first parameter is: a1=(t3-t2) / (t2-t1), wherein a1 is the first parameter, t1 is the first moment, t2 is the second moment, and t3 is the third moment.

[0016] In combination with the first aspect, in some embodiments, determining the first prediction point based on the first reference reporting point, the second reference reporting point and the first parameter includes: determining a first two-dimensional coordinate based on the first reference reporting point, the first two-dimensional coordinate is used to reflect the reporting point position of the first reference reporting point, and the first two-dimensional coordinate is (x1, y1); determining a second two-dimensional coordinate based on the second reference reporting point, the second two-dimensional coordinate is used to reflect the reporting point position of the second reference reporting point, and the second two-dimensional coordinate is (x2, y2); determining a third two-dimensional coordinate based on the first two-dimensional coordinate, the second two-dimensional coordinate and the first parameter, the third two-dimensional coordinate is used to reflect the reporting point position of the first prediction point, and the third two-dimensional coordinate is (x3, y3); wherein, x3=x2+a1*(x2-x1), y3=y2+a1*(y2-y1).

[0017] In combination with the first aspect, in some embodiments, determining the second prediction point based on the two application layer reporting information includes: determining a fourth moment and a third reference reporting point based on the two application layer reporting information, the fourth moment being the last moment of the historical application layer reporting period second closest to the current sub-application layer reporting period, and the third reference reporting point being the application layer reporting point at the fourth moment; determining a fifth moment and a fourth reference reporting point based on the two application layer reporting information, the fifth moment being the last moment of the historical bottom application layer period closest to the current sub-application layer reporting period, and the fourth reference reporting point being the application layer reporting point at the fifth moment; determining a second parameter based on the third moment, the fourth moment and the fifth moment; determining the second prediction point based on the third reference reporting point, the fourth reference reporting point and the second parameter.

[0018] It can be seen that the touch trajectory prediction method can determine the second prediction point by analyzing the correspondence between the two historical application layer reporting information closest to the last moment of the current application layer reporting cycle and each related moment.

[0019] In combination with the first aspect, in some embodiments, the correspondence between the third moment, the fourth moment, the fifth moment and the second parameter is: a2=(t3-t5) / (t5-t4), wherein a2 is the second parameter, t4 is the fourth moment, and t5 is the fifth moment.

[0020] In combination with the first aspect, in some embodiments, determining the second prediction point according to the third reference reporting point, the fourth reference reporting point and the second parameter includes: determining a fourth two-dimensional coordinate according to the third reference reporting point, the fourth two-dimensional coordinate is used to reflect the reporting point position of the third reference reporting point, and the fourth two-dimensional coordinate is (x4, y4); determining a fifth two-dimensional coordinate according to the fourth reference reporting point, the fifth two-dimensional coordinate is used to reflect the reporting point position of the fourth reference reporting point, and the fifth two-dimensional coordinate is (x5, y5); determining a sixth two-dimensional coordinate according to the fourth two-dimensional coordinate, the fifth two-dimensional coordinate and the second parameter, the sixth two-dimensional coordinate is used to reflect the reporting point position of the second prediction point, and the sixth two-dimensional coordinate is (x6, y6); wherein, x6=x5+a2*(x5-x4), y6=y5+a2*(y5-y4).

[0021] In combination with the first aspect, in some embodiments, determining the target prediction point based on the first prediction point and the second prediction point includes: obtaining a preset third parameter, wherein the third parameter is greater than 0 and less than 1; determining a seventh two-dimensional coordinate based on the third two-dimensional coordinate, the sixth two-dimensional coordinate and the third parameter, wherein the seventh two-dimensional coordinate is used to reflect the reported position of the target prediction point, and the seventh two-dimensional coordinate is (x7, y7); wherein, x7=x6*a3+x3*(1-a3), y7=y6*a3+y3*(1-a3), and a3 is the third parameter.

[0022] In a second aspect, an embodiment of the present application provides a touch trajectory prediction device, the touch trajectory prediction device comprising:

[0023] An acquisition module is used to obtain comprehensive reporting information of the current application layer reporting period in the process of reporting the sampling point of the user's finger sliding screen position to the application program, wherein the comprehensive reporting information is used to reflect the bottom layer reporting situation and the application layer reporting situation before the last moment of the current application layer reporting period, wherein the bottom layer reporting point refers to the reporting point of the touch screen firmware reporting the touch event, and the application layer reporting point refers to the reporting point reported by the bottom layer to the application layer; a determination module is used to determine the target prediction point of the current application layer reporting period according to the comprehensive reporting information.

[0024] In combination with the second aspect, in some embodiments, the current sub-application layer reporting period is the nth application layer reporting period, where n is a positive integer greater than or equal to 3; the comprehensive reporting information includes two underlying reporting information of the two historical underlying reporting periods closest to the last moment of the current sub-application layer reporting period, and two application layer reporting information of the two historical application layer reporting periods closest to the last moment of the current sub-application layer reporting period.

[0025] In combination with the second aspect, in some embodiments, in terms of determining the target prediction point of the current sub-application layer reporting period based on the comprehensive reporting information, the determination module is specifically used to perform the following operations: determine a first prediction point based on the two underlying reporting information; determine a second prediction point based on the two application layer reporting information; determine the target prediction point based on the first prediction point and the second prediction point.

[0026] In combination with the second aspect, in some embodiments, in terms of determining the first prediction point based on the two underlying reporting point information, the determination module is specifically used to perform the following operations: determine a first moment and a first reference reporting point based on the two underlying reporting point information, the first moment being the last moment of the historical underlying reporting period that is second closest to the current sub-application layer reporting period, and the first reference reporting point being the underlying reporting point at the first moment; determine a second moment and a second reference reporting point based on the two underlying reporting point information, the second moment being the last moment of the historical underlying reporting period that is closest to the current sub-application layer reporting period, and the second reference point being the underlying reporting point at the second moment; obtain a third moment, the third moment being the last moment of the current sub-application layer reporting period; determine a first parameter based on the first moment, the second moment and the third moment; determine the first prediction point based on the first reference reporting point, the second reference reporting point and the first parameter.

[0027] In combination with the second aspect, in some embodiments, the correspondence between the first moment, the second moment, the third moment and the first parameter is: a1=(t3-t2) / (t2-t1), wherein a1 is the first parameter, t1 is the first moment, t2 is the second moment, and t3 is the third moment.

[0028] In combination with the second aspect, in some embodiments, in terms of determining the first prediction point based on the first reference reporting point, the second reference reporting point and the first parameter, the determination module is specifically used to perform the following operations: determine a first two-dimensional coordinate based on the first reference reporting point, the first two-dimensional coordinate is used to reflect the reporting point position of the first reference reporting point, and the first two-dimensional coordinate is (x1, y1); determine a second two-dimensional coordinate based on the second reference reporting point, the second two-dimensional coordinate is used to reflect the reporting point position of the second reference reporting point, and the second two-dimensional coordinate is (x2, y2); determine a third two-dimensional coordinate based on the first two-dimensional coordinate, the second two-dimensional coordinate and the first parameter, the third two-dimensional coordinate is used to reflect the reporting point position of the first prediction point, and the third two-dimensional coordinate is (x3, y3); wherein, x3=x2+a1*(x2-x1), y3=y2+a1*(y2-y1).

[0029] In combination with the second aspect, in some embodiments, in terms of determining the second prediction point based on the two application layer reporting point information, the determination module is specifically used to perform the following operations: determine a fourth moment and a third reference reporting point based on the two application layer reporting point information, the fourth moment being the last moment of the historical application layer reporting period second closest to the current sub-application layer reporting period, and the third reference reporting point being the application layer reporting point at the fourth moment; determine a fifth moment and a fourth reference reporting point based on the two application layer reporting point information, the fifth moment being the last moment of the historical bottom application layer period closest to the current sub-application layer reporting period, and the fourth reference reporting point being the application layer reporting point at the fifth moment; determine a second parameter based on the third moment, the fourth moment and the fifth moment; determine the second prediction point based on the third reference reporting point, the fourth reference reporting point and the second parameter.

[0030] In combination with the second aspect, in some embodiments, the correspondence between the third moment, the fourth moment, the fifth moment and the second parameter is: a2=(t3-t5) / (t5-t4), wherein a2 is the second parameter, t4 is the fourth moment, and t5 is the fifth moment.

[0031] In combination with the second aspect, in some embodiments, in the aspect of determining the second prediction point according to the third reference reporting point, the fourth reference reporting point and the second parameter, the determination module is specifically used to perform the following operations: determining a fourth two-dimensional coordinate according to the third reference reporting point, the fourth two-dimensional coordinate is used to reflect the reporting point position of the third reference reporting point, and the fourth two-dimensional coordinate is (x4, y4); determining a fifth two-dimensional coordinate according to the fourth reference reporting point, the fifth two-dimensional coordinate is used to reflect the reporting point position of the fourth reference reporting point, and the fifth two-dimensional coordinate is (x5, y5);

[0032] The sixth two-dimensional coordinate is determined according to the fourth two-dimensional coordinate, the fifth two-dimensional coordinate and the second parameter. The sixth two-dimensional coordinate is used to reflect the reported point position of the second prediction point. The sixth two-dimensional coordinate is (x6, y6); wherein, x6=x5+a2*(x5-x4), y6=y5+a2*(y5-y4).

[0033] In combination with the second aspect, in some embodiments, in terms of determining the target prediction point based on the first prediction point and the second prediction point, the determination module is specifically used to perform the following operations: obtain a preset third parameter, the third parameter being greater than 0 and less than 1; determining a seventh two-dimensional coordinate based on the third two-dimensional coordinate, the sixth two-dimensional coordinate and the third parameter, the seventh two-dimensional coordinate being used to reflect the reported point position of the target prediction point, the seventh two-dimensional coordinate being (x7, y7); wherein, x7=x6*a3+x3*(1-a3), y7=y6*a3+y3*(1-a3), a3 is the third parameter.

[0034] In a third aspect, an embodiment of the present application provides a touch trajectory prediction device, comprising: one or more processors, a memory, a touch screen, and one or more programs, wherein the one or more programs are stored in the above-mentioned memory and are configured to be executed by the above-mentioned one or more processors, and the one or more programs include instructions for the steps of the touch trajectory prediction method described in any one of the first aspects.

[0035] In a fourth aspect, an embodiment of the present application provides a computer storage medium, characterized in that it includes computer instructions, and when the computer instructions are executed on an electronic device, the electronic device executes the touch trajectory prediction method as described in any one of the first aspects.

[0036] It can be understood that the touch trajectory prediction device described in the second aspect and the computer storage medium described in the third aspect are used to execute any method provided in the first aspect. Therefore, the beneficial effects that can be achieved can refer to the beneficial effects in the corresponding method, which will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] The following is an introduction to the drawings used in the embodiments of the present application.

[0038] Figure 1 is a schematic diagram of a touch trajectory prediction system software stack provided in an embodiment of the present application;

[0039] Figure 2 A schematic diagram of a flow chart of a touch trajectory prediction method provided in an embodiment of the present application;

[0040] Figure 3 A schematic diagram of the prediction of the horizontal coordinate of a first application layer reporting point provided in an embodiment of the present application;

[0041] Figure 4 1 is a schematic diagram of a prediction of the horizontal coordinate of an nth (n is a positive integer greater than or equal to 3) application layer reporting point provided in an embodiment of the present application;

[0042] Figure 5A schematic diagram for comparing contact fluctuations provided in an embodiment of the present application;

[0043] Figure 6 is a flow chart of another touch trajectory prediction method provided in an embodiment of the present application;

[0044] Figure 7 is a flow chart of another touch trajectory prediction method provided in an embodiment of the present application;

[0045] Figure 8 is a flow chart of another touch trajectory prediction method provided in an embodiment of the present application;

[0046] Fig. 9 A schematic diagram of an application scenario provided for an embodiment of the present application;

[0047] Fig.10 is a structural schematic diagram of a touch trajectory prediction device provided in an embodiment of the present application;

[0048] Fig.11 It is a block diagram of the functional modules of a touch trajectory prediction device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0049] The following describes the embodiments of the present application in conjunction with the drawings in the embodiments of the present application. The terms used in the implementation method part of the embodiments of the present application are only used to explain the specific embodiments of the present application, and are not intended to limit the present application.

[0050] Reference Figure 1 , Figure 1 is a schematic diagram of a touch trajectory prediction system software stack provided by an embodiment of the present application. Figure 1 As shown, the touch trajectory prediction system software stack may include an application 101, a touch screen calibration module libinput102, a touch event distribution module Input Dispatcher103, and a touch screen firmware 104. The touch screen firmware 104 is used to obtain touch events, and to report the obtained touch events, corresponding to the bottom layer report point, the Input Dispatcher103 is used to distribute the touch events reported by the touch screen firmware 104, the libinput102 is used to analyze and process the touch events distributed by the Input Dispatcher103 to obtain the target application layer report point, and finally the libinput102 sends the target application layer report point to the application 101.

[0051] The libinput102 includes a corresponding program that can execute the steps in the touch trajectory prediction method provided in the present application to obtain the target application layer report point.

[0052] Please refer to Figure 2 , Figure 2 A schematic diagram of a touch trajectory prediction method provided in an embodiment of the present application. Figure 2 As shown, the touch trajectory prediction method includes s201-s202, which are as follows:

[0053] s201. In the process of reporting the sampling point of the position of the user's finger sliding on the screen to the application program, the comprehensive reporting point information of the current secondary application layer reporting period is obtained.

[0054] The comprehensive reporting information is used to reflect the bottom-layer reporting situation and the application-layer reporting situation before the last moment of the current application-layer reporting period. The bottom-layer reporting refers to the reporting of touch events by the touch screen firmware, that is, the frame rate at which the touch screen firmware reports touch events. The application-layer reporting refers to the reporting of the bottom layer to the application layer. In practice, the application-layer reporting period is different from the bottom-layer reporting period. For example, the application-layer reporting period is 16ms and the application-layer reporting period is 8ms. The application-layer reporting period and the bottom-layer reporting period can also be other values ​​without specific limitation.

[0055] The touch trajectory prediction method can be applied to an electronic device with a touch function, wherein the electronic device includes a touch screen firmware, and an application can be run on the electronic device, wherein the electronic device can be various handheld devices, vehicle-mounted devices, wearable devices, computing devices or other processing devices connected to a wireless modem, as well as various forms of user equipment (UE), mobile stations (MS), etc., without specific limitation.

[0056] s202. Determine the target prediction point of the current sub-application layer reporting period according to the comprehensive reporting information.

[0057] The touch trajectory prediction method can be applied to touch application scenarios.

[0058] Through the embodiment of the present application, in the process of reporting the sampling point of the position of the user's finger sliding on the screen to the application, the comprehensive reporting information of the current application layer reporting period is obtained. The comprehensive reporting information is used to reflect the bottom layer reporting situation and the application layer reporting situation before the last moment of the current application layer reporting period. The bottom layer reporting refers to the reporting point of the touch screen firmware reporting the touch event, and the application layer reporting refers to the reporting point reported by the bottom layer to the application layer. After that, the target prediction point of the current application layer reporting period is determined according to the comprehensive reporting information. In other words, the target prediction point of the current application layer reporting period can be determined by analyzing the bottom layer reporting situation and the application layer reporting situation before the last moment of the current application layer reporting period, which expands the correction mechanism of the application layer reporting, reduces the deviation of the application layer reporting, and thus reduces the jitter of the touch screen image caused by the touch operation.

[0059] Among them, the current application layer reporting period is the nth application layer reporting period, and n is a positive integer greater than or equal to 3; the comprehensive reporting information includes two bottom-level reporting information of the two historical bottom-level reporting periods closest to the last moment of the current application layer reporting period, and two application layer reporting information of the two historical application layer reporting periods closest to the last moment of the current application layer reporting period.

[0060] Among them, the two bottom-level reporting point information includes the two-dimensional data of the two bottom-level reporting points and the occurrence time of the corresponding touch event, which can reflect the specific position of the corresponding real touch event relative to the touch screen, and the two application layer reporting point information includes the two-dimensional data of the two application layer reporting points and the occurrence time of the corresponding touch event, which can reflect the specific position of the corresponding predicted touch event relative to the touch screen. It can be seen that the touch trajectory prediction method starts from the third application layer reporting point cycle, and combines the historical bottom-level reporting point information and the historical application layer reporting point information to predict the application layer reporting point corresponding to the current cycle.

[0061] In addition, when the current sub-application layer reporting period is the first application layer reporting period or the second application layer reporting period, the corresponding application layer reporting period can be obtained based on the existing method. For example, through a simple linear algorithm, two underlying reporting point information of the two historical underlying reporting periods closest to the last moment of the current sub-application layer reporting period are obtained, and the target prediction point of the current sub-application layer reporting period is determined according to the two underlying reporting point information. Specifically, based on the two underlying reporting point information, the two-dimensional coordinates corresponding to the two underlying reporting points and the corresponding time are determined, the horizontal coordinate corresponding to the current sub-application layer reporting point is determined according to the horizontal coordinates of the two-dimensional coordinates corresponding to the two underlying reporting points and the corresponding time, and the vertical coordinate corresponding to the current sub-application layer reporting point is determined according to the vertical coordinates of the two-dimensional coordinates corresponding to the two underlying reporting points and the corresponding time. Please refer to Figure 3 , Figure 3 A schematic diagram of the prediction of the horizontal coordinate of the first application layer reporting point provided in an embodiment of the present application is shown as follows: Figure 3 As shown in the figure, the horizontal axis T represents time, and the vertical axis X represents the horizontal axis corresponding to each related reporting point, wherein the bottom layer reporting point cycle is 8ms, and the application layer reporting point cycle is 16ms. B1 is the bottom layer reporting point that is second closest to the last moment of the first application layer reporting point cycle. The horizontal axis corresponding to B1 is t1, and the vertical axis is x1. B2 is the bottom layer reporting point that is closest to the last moment of the first application layer reporting point cycle, that is, the first application layer reporting point. The horizontal axis corresponding to B2 is t2, and the vertical axis is x2. B3 is the first application layer reporting point. The application layer reporting point corresponding to the period (i.e., the first application layer reporting point), the horizontal coordinate corresponding to B3 is t3, and the vertical coordinate is x3, x3=[(t3-t2) / (t2-t1)]*(x2-x1)+x2, the principle of determining the vertical coordinate corresponding to the current application layer reporting point according to the vertical coordinate of the two-dimensional coordinates corresponding to the two underlying reporting points and the corresponding time is the same as the principle of determining the horizontal coordinate corresponding to the current application layer reporting point according to the horizontal coordinate of the two-dimensional coordinates corresponding to the two underlying reporting points and the corresponding time, which will not be repeated here.

[0062] Further, determining the target prediction point of the current secondary application layer reporting period according to the comprehensive reporting information includes steps A1-A3:

[0063] A1. Determine a first prediction point according to the two bottom-level reporting point information.

[0064] Among them, the implementation method of determining the first prediction point according to the two underlying reporting point information can be: determine a first moment and a first reference reporting point according to the two underlying reporting point information, the first moment being the last moment of the historical underlying reporting point cycle that is second closest to the current sub-application layer reporting point cycle, and the first reference reporting point being the underlying reporting point at the first moment; determine a second moment and a second reference reporting point according to the two underlying reporting point information, the second moment being the last moment of the historical underlying reporting point cycle that is closest to the current sub-application layer reporting point cycle, and the second reference point being the underlying reporting point at the second moment; obtain a third moment, the third moment being the last moment of the current sub-application layer reporting point cycle; determine a first parameter according to the first moment, the second moment and the third moment; determine the first prediction point according to the first reference reporting point, the second reference reporting point and the first parameter.

[0065] It can be seen that the touch trajectory prediction method can determine the first prediction point by analyzing the correspondence between the two historical bottom-layer reporting point information closest to the last moment of the current application layer reporting point cycle and each related moment.

[0066] Among them, the corresponding relationship between the first moment, the second moment, the third moment and the first parameter is: a1=(t3-t2) / (t2-t1), wherein a1 is the first parameter, t1 is the first moment, t2 is the second moment, and t3 is the third moment.

[0067] Furthermore, the implementation method of determining the first prediction point according to the first reference reporting point, the second reference reporting point and the first parameter may be: determining a first two-dimensional coordinate according to the first reference reporting point, the first two-dimensional coordinate is used to reflect the reporting point position of the first reference reporting point, and the first two-dimensional coordinate is (x1, y1); determining a second two-dimensional coordinate according to the second reference reporting point, the second two-dimensional coordinate is used to reflect the reporting point position of the second reference reporting point, and the second two-dimensional coordinate is (x2, y2); determining a third two-dimensional coordinate according to the first two-dimensional coordinate, the second two-dimensional coordinate and the first parameter, the third two-dimensional coordinate is used to reflect the reporting point position of the first prediction point, and the third two-dimensional coordinate is (x3, y3); wherein, x3=x2+a1*(x2-x1), y3=y2+a1*(y2-y1).

[0068] Please refer to Figure 4 , Figure 4 : is a schematic diagram of a prediction of the horizontal coordinate of an nth (n is a positive integer greater than or equal to 3) application layer reporting point provided in an embodiment of the present application, such as Figure 4 As shown in the figure, the horizontal axis T represents time, and the vertical axis X represents the horizontal axis corresponding to each relevant reporting point, wherein the bottom layer reporting period is 8ms, the application layer reporting period is 16ms, D1 is the first reference reporting point, D2 is the second reference reporting point, D3 is the first predicted point, the horizontal axis corresponding to D1 is t1, and the vertical axis is x1, the horizontal axis corresponding to D2 is t2, and the vertical axis is x2, the horizontal axis corresponding to D3 is t3, and the vertical axis is x3, a1=(t3-t2) / (t2-t1), x3=x2+a1*(x2-x1), and similarly, y3 can be calculated, y3=y2+a1*(y2-y1).

[0069] A2. Determine a second prediction point according to the two application layer reporting point information.

[0070] Wherein, determining the second prediction point according to the two application layer reporting point information includes: determining a fourth moment and a third reference reporting point according to the two application layer reporting point information, the fourth moment being the last moment of the historical application layer reporting period second closest to the current application layer reporting period, and the third reference reporting point being the application layer reporting point at the fourth moment; determining a fifth moment and a fourth reference reporting point according to the two application layer reporting point information, the fifth moment being the last moment of the historical application layer period closest to the current application layer reporting period, and the fourth reference reporting point being the application layer reporting point at the fifth moment; determining a second parameter according to the third moment, the fourth moment and the fifth moment; determining the second prediction point according to the third reference reporting point, the fourth reference reporting point and the second parameter.

[0071] It can be seen that the touch trajectory prediction method can determine the second prediction point by analyzing the correspondence between the two historical application layer reporting information closest to the last moment of the current application layer reporting cycle and each related moment.

[0072] Furthermore, the corresponding relationship between the third moment, the fourth moment, the fifth moment and the second parameter is: a2=(t3-t5) / (t5-t4), wherein a2 is the second parameter, t4 is the fourth moment, and t5 is the fifth moment.

[0073] The method of determining the second prediction point according to the third reference reporting point, the fourth reference reporting point and the second parameter includes: determining a fourth two-dimensional coordinate according to the third reference reporting point, the fourth two-dimensional coordinate is used to reflect the reporting point position of the third reference reporting point, and the fourth two-dimensional coordinate is (x4, y4); determining a fifth two-dimensional coordinate according to the fourth reference reporting point, the fifth two-dimensional coordinate is used to reflect the reporting point position of the fourth reference reporting point, and the fifth two-dimensional coordinate is (x5, y5); determining a sixth two-dimensional coordinate according to the fourth two-dimensional coordinate, the fifth two-dimensional coordinate and the second parameter, the sixth two-dimensional coordinate is used to reflect the reporting point position of the second prediction point, and the sixth two-dimensional coordinate is (x6, y6); wherein, x6=x5+a2*(x5-x4), y6=y5+a2*(y5-y4).

[0074] like Figure 4 As shown in the figure, D4 ​​is the third reference reporting point, D5 is the fourth reference reporting point, D6 is the second predicted point, the horizontal coordinate corresponding to D4 is t4, and the vertical coordinate is x4, the horizontal coordinate corresponding to D5 is t5, and the vertical coordinate is x5, the horizontal coordinate corresponding to D6 is t6, and the vertical coordinate is x6, a2=(t3-t5) / (t5-t4), x6=x5+a2*(x5-x4), and similarly, y6 can be calculated, y6=y5+a2*(y5-y4).

[0075] A3. Determine the target prediction point according to the first prediction point and the second prediction point.

[0076] The method of determining the target prediction point based on the first prediction point and the second prediction point includes: obtaining a preset third parameter, wherein the third parameter is greater than 0 and less than 1; determining a seventh two-dimensional coordinate according to the third two-dimensional coordinate, the sixth two-dimensional coordinate and the third parameter, wherein the seventh two-dimensional coordinate is used to reflect the reported position of the target prediction point, and the seventh two-dimensional coordinate is (x7, y7); wherein x7=x6*a3+x3*(1-a3), y7=y6*a3+y3*(1-a3), and a3 is the third parameter.

[0077] like Figure 4 As shown in the figure, D7 is the target prediction point, the horizontal coordinate corresponding to D7 is t7, the vertical coordinate is x7, x7=x6*a3+x3*(1-a3), and similarly, y7 can be calculated, y7=y6*a3+y3*(1-a3).

[0078] It should be noted that, ideally, when the bottom layer reports uniformly, the results obtained by the prediction algorithm are also uniform, that is, the reporting point information received on the application side also changes uniformly, such as Figure 4 As shown in the figure, D8 is the application layer reporting point corresponding to time t2 under ideal conditions, and D9 is the application layer reporting point corresponding to time t3 under ideal conditions.

[0079] Next, the touch trajectory prediction method provided in the embodiment of the present application is analyzed in combination with the data points of the actual touch operation. Figure 5 As shown, Figure 5 A schematic diagram for comparing contact fluctuations provided in an embodiment of the present application, wherein:

[0080] Curve 1 is the coordinates of the touch point controlled by the user (only the horizontal coordinate in the two-dimensional coordinate is the analysis object), Curve 2 is the fluctuation of the horizontal coordinate in the unprocessed two-dimensional coordinate, reflecting the unprocessed touch point fluctuation, and Curve 3 is the fluctuation of the horizontal coordinate in the processed two-dimensional coordinate, reflecting the processed touch point fluctuation.

[0081] It can be seen that during the touch operation, when the touch point is not processed, the fluctuation is quite violent. In this case, the corresponding report point is reported to the application, which may eventually cause jitter problems in the upper-level application. The fluctuation of the processed data is constrained to a more limited range (relative to curve 2), which ultimately improves the user's touch experience.

[0082] With the above Figure 1 , Figure 2 For details on the embodiments shown in the drawings, please refer to Figure 6 , Figure 6 is a flow chart of another touch trajectory prediction method provided by an embodiment of the present application. Figure 6 As shown, the touch trajectory prediction method includes:

[0083] s601. In the process of reporting the sampling point of the position of the user's finger sliding on the screen to the application, the comprehensive reporting information of the current application layer reporting period is obtained, where the current application layer reporting period is the nth application layer reporting period, and n is a positive integer greater than or equal to 3. The comprehensive reporting information includes two bottom-layer reporting information of the two historical bottom-layer reporting periods closest to the last moment of the current application layer reporting period, and two application layer reporting information of the two historical application layer reporting periods closest to the last moment of the current application layer reporting period;

[0084] s602, determining a first prediction point according to the two bottom-level reporting point information;

[0085] s603, determining a second prediction point according to the two application layer report point information;

[0086] s604. Determine the target prediction point according to the first prediction point and the second prediction point.

[0087] Through the embodiment of the present application, in the process of reporting the sampling point of the position of the user's finger sliding on the screen to the application, the comprehensive reporting information of the current application layer reporting period is obtained. The comprehensive reporting information is used to reflect the bottom layer reporting situation and the application layer reporting situation before the last moment of the current application layer reporting period. The bottom layer reporting refers to the reporting point of the touch screen firmware reporting the touch event, and the application layer reporting refers to the reporting point reported by the bottom layer to the application layer. After that, the target prediction point of the current application layer reporting period is determined according to the comprehensive reporting information. In other words, the target prediction point of the current application layer reporting period can be determined by analyzing the bottom layer reporting situation and the application layer reporting situation before the last moment of the current application layer reporting period, which expands the correction mechanism of the application layer reporting, reduces the deviation of the application layer reporting, and thus reduces the jitter of the touch screen image caused by the touch operation.

[0088] With the above Figure 1 , Figure 2 For details on the embodiments shown in the drawings, please refer to Figure 7 , Figure 7 FIG. 1 is a flow chart of another touch trajectory prediction method provided in an embodiment of the present application. Figure 7 As shown, the touch trajectory prediction method includes:

[0089] s701. In the process of reporting the sampling point of the position of the user's finger sliding on the screen to the application, the comprehensive reporting information of the current application layer reporting period is obtained, where the current application layer reporting period is the nth application layer reporting period, and n is a positive integer greater than or equal to 3. The comprehensive reporting information includes two bottom-layer reporting information of the two historical bottom-layer reporting periods closest to the last moment of the current application layer reporting period, and two application layer reporting information of the two historical application layer reporting periods closest to the last moment of the current application layer reporting period;

[0090] s702, determining a first time and a first reference reporting point according to the two bottom-layer reporting point information, wherein the first time is the last time of the historical bottom-layer reporting period that is second closest to the current application layer reporting period, and the first reference reporting point is the bottom-layer reporting point at the first time;

[0091] s703, determining a second time and a second reference reporting point according to the two bottom-layer reporting point information, wherein the second time is the last time of the historical bottom-layer reporting period closest to the current secondary application layer reporting period, and the second reference point is the bottom-layer reporting point at the second time;

[0092] s704, obtaining a third time, where the third time is the last time of the current secondary application layer reporting period;

[0093] s705. Determine a first parameter according to the first moment, the second moment and the third moment;

[0094] s706. Determine the first prediction point according to the first reference reporting point, the second reference reporting point and the first parameter, wherein the corresponding relationship between the first moment, the second moment, the third moment and the first parameter is: a1=(t3-t2) / (t2-t1), wherein a1 is the first parameter, t1 is the first moment, t2 is the second moment, and t3 is the third moment;

[0095] s707, determining a first two-dimensional coordinate according to the first reference reporting point, where the first two-dimensional coordinate is used to reflect the reporting point position of the first reference reporting point, and the first two-dimensional coordinate is (x1, y1);

[0096] s708. Determine a second two-dimensional coordinate according to the second reference reporting point, where the second two-dimensional coordinate is used to reflect the reporting point position of the second reference reporting point, and the second two-dimensional coordinate is (x2, y2);

[0097] s709. Determine a third two-dimensional coordinate according to the first two-dimensional coordinate, the second two-dimensional coordinate and the first parameter, wherein the third two-dimensional coordinate is used to reflect the reported point position of the first prediction point, and the third two-dimensional coordinate is (x3, y3); wherein x3=x2+a1*(x2-x1), y3=y2+a1*(y2-y1);

[0098] s710, determining a fourth time and a third reference reporting point according to the two application layer reporting point information, wherein the fourth time is the last time of the historical application layer reporting period that is second closest to the current application layer reporting period, and the third reference reporting point is the application layer reporting point of the fourth time;

[0099] s711. Determine a fifth time and a fourth reference reporting point according to the two application layer reporting point information, wherein the fifth time is the last time of the historical application layer cycle closest to the current application layer reporting point cycle, and the fourth reference reporting point is the application layer reporting point of the fifth time;

[0100] s712, determining a second parameter according to the third moment, the fourth moment and the fifth moment;

[0101] s713, determining the second prediction point according to the third reference reporting point, the fourth reference reporting point and the second parameter, the corresponding relationship between the third moment, the fourth moment, the fifth moment and the second parameter is: a2=(t3-t5) / (t5-t4), where a2 is the second parameter, t4 is the fourth moment, and t5 is the fifth moment;

[0102] s714, determining a fourth two-dimensional coordinate according to the third reference reporting point, wherein the fourth two-dimensional coordinate is used to reflect the reporting point position of the third reference reporting point, and the fourth two-dimensional coordinate is (x4, y4);

[0103] s715. Determine a fifth two-dimensional coordinate according to the fourth reference reporting point, wherein the fifth two-dimensional coordinate is used to reflect the reporting point position of the fourth reference reporting point, and the fifth two-dimensional coordinate is (x5, y5);

[0104] s716. Determine a sixth two-dimensional coordinate according to the fourth two-dimensional coordinate, the fifth two-dimensional coordinate and the second parameter, wherein the sixth two-dimensional coordinate is used to reflect the reported point position of the second prediction point, and the sixth two-dimensional coordinate is (x6, y6), wherein x6=x5+a2*(x5-x4), y6=y5+a2*(y5-y4);

[0105] s717, obtaining a preset third parameter, where the third parameter is greater than 0 and less than 1;

[0106] s718. Determine the seventh two-dimensional coordinate based on the third two-dimensional coordinate, the sixth two-dimensional coordinate and the third parameter. The seventh two-dimensional coordinate is used to reflect the reported position of the target prediction point. The seventh two-dimensional coordinate is (x7, y7), wherein x7=x6*a3+x3*(1-a3), y7=y6*a3+y3*(1-a3), and a3 is the third parameter.

[0107] Through the embodiment of the present application, in the process of reporting the sampling point of the position of the user's finger sliding on the screen to the application, the comprehensive reporting information of the current application layer reporting period is obtained. The comprehensive reporting information is used to reflect the bottom layer reporting situation and the application layer reporting situation before the last moment of the current application layer reporting period. The bottom layer reporting refers to the reporting point of the touch screen firmware reporting the touch event, and the application layer reporting refers to the reporting point reported by the bottom layer to the application layer. After that, the target prediction point of the current application layer reporting period is determined according to the comprehensive reporting information. In other words, the target prediction point of the current application layer reporting period can be determined by analyzing the bottom layer reporting situation and the application layer reporting situation before the last moment of the current application layer reporting period, which expands the correction mechanism of the application layer reporting, reduces the deviation of the application layer reporting, and thus reduces the jitter of the touch screen image caused by the touch operation.

[0108] In addition, the embodiment of the present application can predict the application layer reporting point corresponding to the current period by combining the historical bottom layer reporting point information and the historical application layer reporting point information starting from the third application layer reporting period.

[0109] With the above Figure 1 , Figure 2 as well as Figure 7 For details on the embodiments shown in the drawings, please refer to Figure 8 , Figure 8 is a flow chart of another touch trajectory prediction method provided by an embodiment of the present application, such as Figure 8 As shown, the touch trajectory prediction method includes steps s801 to s810:

[0110] s801. Obtain target underlying reporting point data of two target underlying reporting points of target timestamps from the underlying reporting point history cache.

[0111] The above-mentioned bottom-level reporting point is also called the original reporting point (Raw Point, RP), the above-mentioned target timestamp is the last moment of the target application layer reporting period, and the target application layer reporting period is the period of the bottom-level point data to be uploaded to the application layer by the target application layer reporting point. The historical cache of the bottom-level reporting point includes the bottom-level reporting point timestamp of the historical bottom-level reporting point, the bottom-level reporting point data, and the corresponding relationship between the above-mentioned bottom-level reporting point timestamp and the above-mentioned bottom-level reporting point data. The bottom-level reporting point data is used to reflect the screen position touched by the user's finger (that is, the reporting point position of the historical bottom-level reporting point), and the bottom-level reporting point data includes the horizontal position of the screen touched by the user's finger (that is, the horizontal position of the historical bottom-level reporting point) and the vertical position of the screen touched by the user's finger (that is, the vertical position of the historical bottom-level reporting point), wherein the bottom-level reporting point timestamp is the last moment of the bottom-level reporting point in the corresponding bottom-level reporting period. The above-mentioned two target bottom-level reporting points include the historical bottom-level reporting point closest to the above-mentioned target timestamp and the historical bottom-level reporting point with the second closest distance to the target timestamp.

[0112] As shown in the figure, the bottom-level reporting point data of the two historical bottom-level reporting points close to the target timestamp T3 include RT3, RP3 and RT2, RP2 respectively, among which RT3 is the last moment of the historical bottom-level reporting point cycle closest to T3, RP3 is the reporting point position of the historical bottom-level reporting point corresponding to RT3, RT2 is the last moment of the historical bottom-level reporting point cycle second closest to T3, and RP2 is the reporting point position of the historical original reporting point corresponding to RT2.

[0113] The acquisition of the historical cache of the bottom-level reporting point includes the following steps B1 to B3:

[0114] B1. The bottom layer reports the original reporting point data according to the preset bottom layer reporting period.

[0115] B2. Record the original reporting point data of the original reporting point.

[0116] B3. Cache the original reporting point data to obtain the historical cache of the underlying reporting point.

[0117] s802. Obtain target application layer reporting point data of two application layer reporting points of the target timestamp from the historical cache of application layer reporting points.

[0118] The historical cache of application layer reporting points includes the application layer timestamps of historical application layer reporting points, application layer point data, and the corresponding relationship between the application layer timestamps and the application layer point data, wherein the application layer reporting point timestamp is the last moment of the application layer reporting point in the corresponding application layer reporting point cycle. The two target application layer reporting points of the target timestamp include the historical application layer reporting point closest to the target timestamp and the historical application layer reporting point second closest to the target timestamp.

[0119] As shown in the figure, the application layer point reporting history cache of the target timestamp T3 may include but is not limited to timestamps (T0, T1 and T2), point data (P0, P1 and P2), T0 corresponds to P0, T1 corresponds to P1, T2 corresponds to P2, T2 is the last moment of the historical application layer point reporting cycle closest to T3, P2 is the reporting point position of the historical application layer point reporting corresponding to T2, T1 is the last moment of the historical application layer point reporting cycle second closest to T3, and P1 is the reporting point position of the historical application layer point reporting corresponding to T1.

[0120] s803. Calculate a first parameter based on the target timestamp and the target underlying reporting data.

[0121] Wherein, the first parameter alpha1=(T3-RT3) / (RT3-RT2).

[0122] Preferably, when it is determined that alpha1 is less than or equal to 1, steps s804 to s810 are executed, and when it is determined that alpha1 is greater than 1, after executing step s804, the first point data prediction value is directly used as the point data of the target prediction point and reported to the application, that is, no correction is performed when alpha1 is greater than 1.

[0123] s804. Obtain first prediction point data of a first prediction point according to the first parameter and the target underlying reporting point data.

[0124] The first prediction point data can be obtained through the first corresponding relationship, which is expressed as P 3” =RP3+alpha1*(RP3-RP2).

[0125] The first prediction point data includes the horizontal position of the first prediction point and the vertical position of the first prediction point. When RP3 is the horizontal position of the historical bottom-level reporting point closest to the target timestamp and RP2 is the horizontal position of the historical bottom-level reporting point second closest to the target timestamp, then P 3” is the horizontal position of the first prediction point; when RP3 is the vertical position of the historical bottom-level reporting point closest to the target timestamp and RP2 is the vertical position of the historical bottom-level reporting point second closest to the target timestamp, then P 3” is the vertical position of the first prediction point.

[0126] s805. Calculate a second parameter based on the target timestamp and the target application layer reporting data.

[0127] Among them, the second parameter alpha2 = (T3-T2) / (T2-T1).

[0128] s806. Calculate second prediction point data of a second prediction point according to the second parameter and the target application layer report point data.

[0129] The second prediction point data can be obtained through the second corresponding relationship, and the second corresponding relationship is expressed as P 3' =P2+alpha2*(P2-P1).

[0130] The second prediction point data includes the horizontal position of the second prediction point and the vertical position of the second prediction point. When P2 is the horizontal position of the historical application layer reporting point closest to the target timestamp and P1 is the horizontal position of the historical application layer reporting point second closest to the target timestamp, then P 3' is the horizontal position of the second predicted point; when P2 is the vertical position of the historical application layer reporting point closest to the target timestamp and P1 is the vertical position of the historical application layer reporting point second closest to the target timestamp, then P 3' is the longitudinal position of the second prediction point.

[0131] s807. Set weighting parameters.

[0132] The weighting parameter alpha is greater than 0 and less than 1, such as alpha is equal to 0.5.

[0133] It should be noted that s807 occurs before s808, and there is no specific order between s807 and steps s801 to s806.

[0134] s808. Obtain the point data of the target prediction point according to the first prediction point data, the second prediction point data and the weighting parameter.

[0135] The point data of the target prediction point can be obtained through the third corresponding relationship, which is expressed as P3=P 3' *alpha+P 3” *(1-alpha).

[0136] The point data of the target prediction reporting point includes the lateral position of the target prediction reporting point and the longitudinal position of the target prediction reporting point.

[0137] When P 3” is the lateral position of the first prediction point and P 3' is the lateral position of the second prediction point, and P3 is the lateral position of the target prediction point; when P 3” is the longitudinal position of the first prediction point and P 3' is the longitudinal position of the second prediction point, and P3 is the longitudinal position of the target prediction point.

[0138] s809, cache the predicted point data of the target predicted point to obtain the updated historical cache of the application layer point.

[0139] The above-mentioned forecast point data includes point data, time stamp and the corresponding relationship between the point data and the time stamp.

[0140] s810, reporting the point data of the target prediction point to the target application.

[0141] It should be noted that there is no specific limitation on the order in which s809 and s810 occur. s809 and s810 may occur at the same time, s809 may occur before s810, or s809 may occur after s810.

[0142] It can be seen that in this example, the target prediction point of the target application layer reporting period can be determined by analyzing the two underlying reporting points closest to the last moment before the last moment of the target application layer reporting period and the two application layer reporting points closest to the last moment. This expands the correction mechanism of the application layer reporting points, reduces the deviation of the application layer reporting points, and thus reduces the jitter of the touch screen caused by touch operations.

[0143] Next, the application scenarios of the touch trajectory prediction method provided in the embodiments of the present application are introduced.

[0144] The first type is to slide up and down for image list applications (such as today's headlines, application review lists, contact lists, etc.), and the touch trajectory prediction method provided in the embodiment of the present application can even out the frame spacing to improve the smoothness of the sliding. Fig. 9 , Fig. 9 A schematic diagram of an application scenario provided in an embodiment of the present application, sliding up and down in a contact list.

[0145] The second type is to slide up and down for reading applications (such as browser web pages, e-books, etc.). The touch trajectory prediction method provided in the embodiment of the present application can be used to even out the frame spacing, thereby improving the smoothness of the sliding.

[0146] The third type is to slide the user interface (UI) control for music playback and video playback applications (such as progress and brightness adjustment seekbar). The touch trajectory prediction method provided in the embodiment of the present application can be used to even out the frame spacing, thereby improving the smoothness of the sliding and achieving smooth changes in progress control during sliding.

[0147] Fourthly, for gesture operation applications (such as left and right sliding, multi-finger zooming and other scenarios), sliding up and down, the frame spacing is evened out through the touch trajectory prediction method provided in the embodiment of the present application, and the smoothness of the sliding effect is improved during the gesture operation, so that when the gesture operation UI is achieved, the interface changes smoothly with the gesture.

[0148] It should be noted that the touch trajectory prediction method can also be applied to other application scenarios, which are not specifically limited here.

[0149] With the above Figure 1 , Figure 2 , Figure 6 , Figure 7 as well as Figure 8 For details on the embodiments shown in the drawings, please refer to Fig.10 , Fig.10 is a schematic diagram of the structure of a touch trajectory prediction device provided in an embodiment of the present application, such as Fig.10 As shown, the touch trajectory prediction device 1000 includes one or more processors 1010, a memory 1020, a touch screen 1030, a communication interface 1040, and one or more programs 1021, wherein the one or more programs 1021 are stored in the above-mentioned memory 1020 and are configured to be executed by the above-mentioned one or more processors 1010, and the one or more programs 1021 include instructions for performing the following steps;

[0150] In the process of reporting the sampling point of the user's finger sliding screen position to the application, the comprehensive reporting point information of the current application layer reporting period is obtained, and the comprehensive reporting point information is used to reflect the bottom layer reporting point situation and the application layer reporting point situation before the last moment of the current application layer reporting point period. The bottom layer reporting point refers to the reporting point of the touch screen firmware reporting the touch event, and the application layer reporting point refers to the reporting point reported by the bottom layer to the application layer;

[0151] The target prediction point of the current sub-application layer reporting period is determined according to the comprehensive reporting information.

[0152] Through the embodiment of the present application, in the process of reporting the sampling point of the position of the user's finger sliding on the screen to the application, the comprehensive reporting information of the current application layer reporting period is obtained. The comprehensive reporting information is used to reflect the bottom layer reporting situation and the application layer reporting situation before the last moment of the current application layer reporting period. The bottom layer reporting refers to the reporting point of the touch screen firmware reporting the touch event, and the application layer reporting refers to the reporting point reported by the bottom layer to the application layer. After that, the target prediction point of the current application layer reporting period is determined according to the comprehensive reporting information. In other words, the target prediction point of the current application layer reporting period can be determined by analyzing the bottom layer reporting situation and the application layer reporting situation before the last moment of the current application layer reporting period, which expands the correction mechanism of the application layer reporting, reduces the deviation of the application layer reporting, and thus reduces the jitter of the touch screen image caused by the touch operation.

[0153] In a possible example, the current sub-application layer reporting period is the nth application layer reporting period, where n is a positive integer greater than or equal to 3; the comprehensive reporting information includes two underlying reporting information of the two historical underlying reporting periods closest to the last moment of the current sub-application layer reporting period, and two application layer reporting information of the two historical application layer reporting periods closest to the last moment of the current sub-application layer reporting period.

[0154] In one possible example, in terms of determining the target prediction point of the current sub-application layer reporting period based on the comprehensive reporting information, the instructions in the one or more programs 1021 are specifically used to execute: determining a first prediction point based on the two underlying reporting information; determining a second prediction point based on the two application layer reporting information; determining the target prediction point based on the first prediction point and the second prediction point.

[0155] In one possible example, in terms of determining the first prediction point based on the two underlying reporting point information, the instructions in the one or more programs 1021 are specifically used to execute: determining a first moment and a first reference reporting point based on the two underlying reporting point information, the first moment being the last moment of the historical underlying reporting point cycle that is second closest to the current sub-application layer reporting point cycle, and the first reference reporting point being the underlying reporting point at the first moment; determining a second moment and a second reference reporting point based on the two underlying reporting point information, the second moment being the last moment of the historical underlying reporting point cycle that is closest to the current sub-application layer reporting point cycle, and the second reference point being the underlying reporting point at the second moment; obtaining a third moment, the third moment being the last moment of the current sub-application layer reporting point cycle; determining a first parameter based on the first moment, the second moment and the third moment; and determining the first prediction point based on the first reference reporting point, the second reference reporting point and the first parameter.

[0156] In a possible example, the correspondence between the first moment, the second moment, the third moment and the first parameter is: a1=(t3-t2) / (t2-t1), where a1 is the first parameter, t1 is the first moment, t2 is the second moment, and t3 is the third moment.

[0157] In one possible example, in terms of determining the first prediction point based on the first reference reporting point, the second reference reporting point and the first parameter, the instructions in the one or more programs 1021 are specifically used to execute: determining a first two-dimensional coordinate based on the first reference reporting point, the first two-dimensional coordinate being used to reflect the reporting point position of the first reference reporting point, and the first two-dimensional coordinate being (x1, y1); determining a second two-dimensional coordinate based on the second reference reporting point, the second two-dimensional coordinate being used to reflect the reporting point position of the second reference reporting point, and the second two-dimensional coordinate being (x2, y2); determining a third two-dimensional coordinate based on the first two-dimensional coordinate, the second two-dimensional coordinate and the first parameter, the third two-dimensional coordinate being used to reflect the reporting point position of the first prediction point, and the third two-dimensional coordinate being (x3, y3); wherein, x3=x2+a1*(x2-x1), y3=y2+a1*(y2-y1).

[0158] In one possible example, in terms of determining the second prediction point based on the two application layer reporting information, the instructions in the one or more programs 1021 are specifically used to execute: determining a fourth moment and a third reference reporting point based on the two application layer reporting information, the fourth moment being the last moment of the historical application layer reporting period second closest to the current sub-application layer reporting period, and the third reference reporting point being the application layer reporting point at the fourth moment; determining a fifth moment and a fourth reference reporting point based on the two application layer reporting information, the fifth moment being the last moment of the historical bottom application layer period closest to the current sub-application layer reporting period, and the fourth reference reporting point being the application layer reporting point at the fifth moment; determining a second parameter based on the third moment, the fourth moment and the fifth moment; and determining the second prediction point based on the third reference reporting point, the fourth reference reporting point and the second parameter.

[0159] In a possible example, the correspondence between the third moment, the fourth moment, the fifth moment and the second parameter is: a2=(t3-t5) / (t5-t4), where a2 is the second parameter, t4 is the fourth moment, and t5 is the fifth moment.

[0160] In one possible example, in terms of determining the second prediction point based on the third reference reporting point, the fourth reference reporting point and the second parameter, the instructions in the one or more programs 1021 are specifically used to execute: determining a fourth two-dimensional coordinate based on the third reference reporting point, the fourth two-dimensional coordinate being used to reflect the reporting point position of the third reference reporting point, and the fourth two-dimensional coordinate being (x4, y4); determining a fifth two-dimensional coordinate based on the fourth reference reporting point, the fifth two-dimensional coordinate being used to reflect the reporting point position of the fourth reference reporting point, and the fifth two-dimensional coordinate being (x5, y5); determining a sixth two-dimensional coordinate based on the fourth two-dimensional coordinate, the fifth two-dimensional coordinate and the second parameter, the sixth two-dimensional coordinate being used to reflect the reporting point position of the second prediction point, and the sixth two-dimensional coordinate being (x6, y6); wherein, x6=x5+a2*(x5-x4), y6=y5+a2*(y5-y4).

[0161] In one possible example, in terms of determining the target prediction point based on the first prediction point and the second prediction point, the instructions in the one or more programs 1021 are specifically used to execute: obtaining a preset third parameter, the third parameter being greater than 0 and less than 1; determining a seventh two-dimensional coordinate based on the third two-dimensional coordinate, the sixth two-dimensional coordinate and the third parameter, the seventh two-dimensional coordinate being used to reflect the reported position of the target prediction point, the seventh two-dimensional coordinate being (x7, y7); wherein, x7=x6*a3+x3*(1-a3), y7=y6*a3+y3*(1-a3), a3 being the third parameter.

[0162] With the above Figure 1 , Figure 2 , Figure 6 , Figure 7 as well as Figure 8 For details on the embodiments shown in the drawings, please refer to Fig.11 , Fig.11 is a functional module block diagram of a touch trajectory prediction device provided by an embodiment of the present application, such as Fig.11 As shown, the touch trajectory prediction device 1100 includes an acquisition module 1101 and a determination module 1102, wherein:

[0163] The acquisition module 1101 is used to acquire the comprehensive reporting point information of the current application layer reporting period in the process of reporting the sampling point of the user's finger sliding screen position to the application program, wherein the comprehensive reporting point information is used to reflect the bottom layer reporting point situation and the application layer reporting point situation before the last moment of the current application layer reporting point period, wherein the bottom layer reporting point refers to the reporting point of the touch screen firmware reporting the touch event, and the application layer reporting point refers to the reporting point reported by the bottom layer to the application layer;

[0164] The determination module 1102 is used to determine the target prediction point of the current secondary application layer reporting period according to the comprehensive reporting information.

[0165] Through the embodiment of the present application, in the process of reporting the sampling point of the position of the user's finger sliding on the screen to the application, the comprehensive reporting information of the current application layer reporting period is obtained. The comprehensive reporting information is used to reflect the bottom layer reporting situation and the application layer reporting situation before the last moment of the current application layer reporting period. The bottom layer reporting refers to the reporting point of the touch screen firmware reporting the touch event, and the application layer reporting refers to the reporting point reported by the bottom layer to the application layer. After that, the target prediction point of the current application layer reporting period is determined according to the comprehensive reporting information. In other words, the target prediction point of the current application layer reporting period can be determined by analyzing the bottom layer reporting situation and the application layer reporting situation before the last moment of the current application layer reporting period, which expands the correction mechanism of the application layer reporting, reduces the deviation of the application layer reporting, and thus reduces the jitter of the touch screen image caused by the touch operation.

[0166] The device 1100 may further include a storage module 1103 for storing program codes and data of the electronic device. The determination module 1102 may be a processor, and the storage module 1103 may be a memory.

[0167] In a possible example, the current sub-application layer reporting period is the nth application layer reporting period, where n is a positive integer greater than or equal to 3; the comprehensive reporting information includes two underlying reporting information of the two historical underlying reporting periods closest to the last moment of the current sub-application layer reporting period, and two application layer reporting information of the two historical application layer reporting periods closest to the last moment of the current sub-application layer reporting period.

[0168] In one possible example, in terms of determining the target prediction point of the current sub-application layer reporting period based on the comprehensive reporting information, the determination module 1102 is specifically used to perform the following operations: determine a first prediction point based on the two underlying reporting information; determine a second prediction point based on the two application layer reporting information; determine the target prediction point based on the first prediction point and the second prediction point.

[0169] In one possible example, in terms of determining the first prediction point based on the two underlying reporting point information, the determination module 1102 is specifically used to perform the following operations: determine a first moment and a first reference reporting point based on the two underlying reporting point information, the first moment being the last moment of the historical underlying reporting point cycle that is second closest to the current sub-application layer reporting point cycle, and the first reference reporting point being the underlying reporting point at the first moment; determine a second moment and a second reference reporting point based on the two underlying reporting point information, the second moment being the last moment of the historical underlying reporting point cycle that is closest to the current sub-application layer reporting point cycle, and the second reference point being the underlying reporting point at the second moment; obtain a third moment, the third moment being the last moment of the current sub-application layer reporting point cycle; determine a first parameter based on the first moment, the second moment and the third moment; determine the first prediction point based on the first reference reporting point, the second reference reporting point and the first parameter.

[0170] In a possible example, the correspondence between the first moment, the second moment, the third moment and the first parameter is: a1=(t3-t2) / (t2-t1), where a1 is the first parameter, t1 is the first moment, t2 is the second moment, and t3 is the third moment.

[0171] In one possible example, in terms of determining the first prediction point based on the first reference reporting point, the second reference reporting point and the first parameter, the determination module 1102 is specifically used to perform the following operations: determine a first two-dimensional coordinate based on the first reference reporting point, the first two-dimensional coordinate is used to reflect the reporting point position of the first reference reporting point, and the first two-dimensional coordinate is (x1, y1); determine a second two-dimensional coordinate based on the second reference reporting point, the second two-dimensional coordinate is used to reflect the reporting point position of the second reference reporting point, and the second two-dimensional coordinate is (x2, y2); determine a third two-dimensional coordinate based on the first two-dimensional coordinate, the second two-dimensional coordinate and the first parameter, the third two-dimensional coordinate is used to reflect the reporting point position of the first prediction point, and the third two-dimensional coordinate is (x3, y3); wherein, x3=x2+a1*(x2-x1), y3=y2+a1*(y2-y1).

[0172] In one possible example, in terms of determining the second prediction point based on the two application layer reporting point information, the determination module 1102 is specifically used to perform the following operations: determine a fourth moment and a third reference reporting point based on the two application layer reporting point information, the fourth moment being the last moment of the historical application layer reporting period second closest to the current sub-application layer reporting period, and the third reference reporting point being the application layer reporting point at the fourth moment; determine a fifth moment and a fourth reference reporting point based on the two application layer reporting point information, the fifth moment being the last moment of the historical bottom application layer period closest to the current sub-application layer reporting period, and the fourth reference reporting point being the application layer reporting point at the fifth moment; determine a second parameter based on the third moment, the fourth moment and the fifth moment; determine the second prediction point based on the third reference reporting point, the fourth reference reporting point and the second parameter.

[0173] In a possible example, the correspondence between the third moment, the fourth moment, the fifth moment and the second parameter is: a2=(t3-t5) / (t5-t4), where a2 is the second parameter, t4 is the fourth moment, and t5 is the fifth moment.

[0174] In a possible example, in terms of determining the second prediction point according to the third reference reporting point, the fourth reference reporting point and the second parameter, the determination module 1102 is specifically used to perform the following operations: determine a fourth two-dimensional coordinate according to the third reference reporting point, the fourth two-dimensional coordinate is used to reflect the reporting point position of the third reference reporting point, and the fourth two-dimensional coordinate is (x4, y4); determine a fifth two-dimensional coordinate according to the fourth reference reporting point, the fifth two-dimensional coordinate is used to reflect the reporting point position of the fourth reference reporting point, and the fifth two-dimensional coordinate is (x5, y5); determine a sixth two-dimensional coordinate according to the fourth two-dimensional coordinate, the fifth two-dimensional coordinate and the second parameter, the sixth two-dimensional coordinate is used to reflect the reporting point position of the second prediction point, and the sixth two-dimensional coordinate is (x6, y6); wherein, x6=x5+a2*(x5-x4), y6=y5+a2*(y5-y4).

[0175] In a possible example, in terms of determining the target prediction point based on the first prediction point and the second prediction point, the determination module 1102 is specifically used to perform the following operations: obtain a preset third parameter, the third parameter being greater than 0 and less than 1; determine a seventh two-dimensional coordinate based on the third two-dimensional coordinate, the sixth two-dimensional coordinate and the third parameter, the seventh two-dimensional coordinate being used to reflect the reported point position of the target prediction point, the seventh two-dimensional coordinate being (x7, y7); wherein, x7=x6*a3+x3*(1-a3), y7=y6*a3+y3*(1-a3), a3 being the third parameter.

[0176] An embodiment of the present application further provides a computer storage medium, wherein the computer storage medium includes computer instructions, and when the computer instructions are executed on an electronic device, the electronic device executes the touch trajectory prediction method as described in any one of the first aspects.

[0177] The embodiment of the present application also provides a computer program product, the computer program product includes a non-transitory computer-readable storage medium storing a computer program, the computer program is operable to cause a computer to execute some or all of the steps of any method described in the method embodiment. The computer program product may be a software installation package, and the computer includes an electronic device.

[0178] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the described order of actions, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present application.

[0179] In the embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0180] In the several embodiments provided in the present application, it should be understood that the disclosed device can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of the modules, which is only a logical function division. There may be other division methods in actual implementation, such as multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the device or module can be electrical or other forms.

[0181] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical modules, that is, they may be located in one place or distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0182] In addition, each functional module in each embodiment of the present application can be integrated into a processing module, or each module can exist physically separately, or two or more modules can be integrated into one module. The integrated module can be implemented in the form of hardware or software functional modules.

[0183] If the integrated module is implemented in the form of a software function module and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a memory, including a number of instructions to enable a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the above methods of each embodiment of the present application. The aforementioned memory includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (Random Access Memory, RAM), mobile hard disk, disk or CD-ROM and other media that can store program codes.

[0184] A person skilled in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable memory, and the memory can include: a flash drive, a read-only memory (English: Read-Only Memory, abbreviated as: ROM), a random access memory (English: Random Access Memory, abbreviated as: RAM), a magnetic disk or an optical disk, etc.

[0185] The terms "first", "second", etc. in the specification and claims of this application and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or modules is not limited to the listed steps or modules, but optionally includes steps or modules that are not listed, or optionally includes other steps or modules inherent to these processes, methods, products or devices.

[0186] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0187] The above is only a specific implementation of the embodiment of the present application, but the protection scope of the embodiment of the present application is not limited thereto, and any changes or replacements within the technical scope disclosed in the embodiment of the present application should be included in the protection scope of the embodiment of the present application. Therefore, the protection scope of the embodiment of the present application should be based on the protection scope of the claims.

Claims

1. A touch trajectory prediction method, characterized in that: include: In the process of reporting the sampling point of the user's finger sliding screen position to the application, the comprehensive reporting point information of the current application layer reporting period is obtained, and the comprehensive reporting point information is used to reflect the bottom layer reporting point situation and the application layer reporting point situation before the last moment of the current application layer reporting point period. The bottom layer reporting point refers to the reporting point of the touch screen firmware reporting the touch event, and the application layer reporting point refers to the reporting point reported by the bottom layer to the application layer; The target prediction point of the current sub-application layer reporting period is determined according to the comprehensive reporting information.

2. The method according to claim 1, characterized in that The current application layer reporting period is the nth application layer reporting period, where n is a positive integer greater than or equal to 3; The comprehensive reporting information includes two bottom-level reporting information of the two historical bottom-level reporting periods closest to the last moment of the current application layer reporting period, and two application layer reporting information of the two historical application layer reporting periods closest to the last moment of the current application layer reporting period.

3. The method according to claim 2, characterized in that The step of determining the target prediction point of the current secondary application layer reporting period according to the comprehensive reporting information includes: Determine a first prediction point according to the two bottom-level reporting point information; Determine a second prediction point according to the two application layer report point information; The target prediction point is determined according to the first prediction point and the second prediction point.

4. The method according to claim 3, characterized in that The determining the first prediction point according to the two bottom-level reporting point information includes: Determine a first time and a first reference reporting point according to the two bottom-layer reporting point information, wherein the first time is the last time of the historical bottom-layer reporting point cycle that is second closest to the current application layer reporting point cycle, and the first reference reporting point is the bottom-layer reporting point at the first time; Determine a second time and a second reference reporting point according to the two bottom-layer reporting point information, wherein the second time is the last time of the historical bottom-layer reporting point cycle closest to the current secondary application layer reporting point cycle, and the second reference reporting point is the bottom-layer reporting point at the second time; Obtaining a third moment, where the third moment is the last moment of the current secondary application layer reporting period; Determine a first parameter according to the first moment, the second moment, and the third moment; The first prediction point is determined according to the first reference reporting point, the second reference reporting point and the first parameter.

5. The method according to claim 4, characterized in that The corresponding relationship between the first moment, the second moment, the third moment and the first parameter is: , wherein a1 is the first parameter, t1 is the first moment, t2 is the second moment, and t3 is the third moment.

6. The method according to claim 5, characterized in that The determining the first prediction point according to the first reference reporting point, the second reference reporting point and the first parameter includes: Determine a first two-dimensional coordinate according to the first reference reporting point, the first two-dimensional coordinate is used to reflect the reporting point position of the first reference reporting point, and the first two-dimensional coordinate is (x1, y1); Determine a second two-dimensional coordinate according to the second reference reporting point, the second two-dimensional coordinate is used to reflect the reporting point position of the second reference reporting point, and the second two-dimensional coordinate is (x2, y2); Determine a third two-dimensional coordinate according to the first two-dimensional coordinate, the second two-dimensional coordinate and the first parameter, the third two-dimensional coordinate is used to reflect the reported point position of the first prediction point, and the third two-dimensional coordinate is (x3, y3); in, , .

7. The method according to claim 6, characterized in that The determining the second prediction point according to the two application layer reporting point information includes: Determine a fourth time and a third reference reporting point according to the two application layer reporting point information, wherein the fourth time is the last time of the historical application layer reporting period that is second closest to the current application layer reporting period, and the third reference reporting point is the application layer reporting point of the fourth time; Determine a fifth time and a fourth reference reporting point according to the two application layer reporting point information, wherein the fifth time is the last time of the historical bottom application layer cycle closest to the current secondary application layer reporting point cycle, and the fourth reference reporting point is the application layer reporting point of the fifth time; Determine a second parameter according to the third moment, the fourth moment and the fifth moment; The second prediction point is determined according to the third reference reporting point, the fourth reference reporting point and the second parameter.

8. The method according to claim 7, characterized in that The corresponding relationship between the third moment, the fourth moment, the fifth moment and the second parameter is: , wherein a2 is the second parameter, t4 is the fourth moment, and t5 is the fifth moment.

9. The method according to claim 8, characterized in that The determining the second prediction point according to the third reference reporting point, the fourth reference reporting point and the second parameter comprises: Determine a fourth two-dimensional coordinate according to the third reference reporting point, the fourth two-dimensional coordinate is used to reflect the reporting point position of the third reference reporting point, and the fourth two-dimensional coordinate is (x4, y4); Determine a fifth two-dimensional coordinate according to the fourth reference reporting point, the fifth two-dimensional coordinate is used to reflect the reporting point position of the fourth reference reporting point, and the fifth two-dimensional coordinate is (x5, y5); Determine a sixth two-dimensional coordinate according to the fourth two-dimensional coordinate, the fifth two-dimensional coordinate and the second parameter, the sixth two-dimensional coordinate is used to reflect the reported point position of the second prediction point, and the sixth two-dimensional coordinate is (x6, y6); in, , .

10. The method according to claim 9, characterized in that The determining the target prediction point according to the first prediction point and the second prediction point includes: Obtain a preset third parameter, where the third parameter is greater than 0 and less than 1; Determine a seventh two-dimensional coordinate according to the third two-dimensional coordinate, the sixth two-dimensional coordinate and the third parameter, the seventh two-dimensional coordinate is used to reflect the reported point position of the target prediction point, and the seventh two-dimensional coordinate is (x7, y7); in, , , a3 is the third parameter.

11. A touch trajectory prediction device, characterized in that: The touch trajectory prediction device comprises: An acquisition module, used to acquire comprehensive reporting point information of the current application layer reporting period in the process of reporting the sampling point of the user's finger sliding screen position to the application program, wherein the comprehensive reporting point information is used to reflect the bottom layer reporting point situation and the application layer reporting point situation before the last moment of the current application layer reporting period, wherein the bottom layer reporting point refers to the reporting point of the touch screen firmware reporting the touch event, and the application layer reporting point refers to the reporting point reported by the bottom layer to the application layer; A determination module is used to determine the target prediction point of the current secondary application layer reporting period according to the comprehensive reporting information.

12. The device according to claim 11, characterized in that The current application layer reporting period is the nth application layer reporting period, where n is a positive integer greater than or equal to 3; The comprehensive reporting information includes two bottom-level reporting information of the two historical bottom-level reporting periods closest to the last moment of the current application layer reporting period, and two application layer reporting information of the two historical application layer reporting periods closest to the last moment of the current application layer reporting period.

13. The device according to claim 12, characterized in that In determining the target prediction point of the current secondary application layer reporting period according to the comprehensive reporting information, the determining module is specifically used to perform the following operations: Determine a first prediction point according to the two bottom-level reporting point information; Determine a second prediction point according to the two application layer report point information; The target prediction point is determined according to the first prediction point and the second prediction point.

14. The device according to claim 13, characterized in that In the aspect of determining the first prediction point according to the two bottom-level reporting point information, the determination module is specifically used to perform the following operations: Determine a first time and a first reference reporting point according to the two bottom-layer reporting point information, wherein the first time is the last time of the historical bottom-layer reporting point cycle that is second closest to the current application layer reporting point cycle, and the first reference reporting point is the bottom-layer reporting point at the first time; Determine a second time and a second reference reporting point according to the two bottom-layer reporting point information, wherein the second time is the last time of the historical bottom-layer reporting point cycle closest to the current secondary application layer reporting point cycle, and the second reference reporting point is the bottom-layer reporting point at the second time; Obtaining a third moment, where the third moment is the last moment of the current secondary application layer reporting period; Determine a first parameter according to the first moment, the second moment, and the third moment; The first prediction point is determined according to the first reference reporting point, the second reference reporting point and the first parameter.

15. The device according to claim 14, characterized in that The corresponding relationship between the first moment, the second moment, the third moment and the first parameter is: , wherein a1 is the first parameter, t1 is the first moment, t2 is the second moment, and t3 is the third moment.

16. The device according to claim 15, characterized in that In the aspect of determining the first prediction point according to the first reference reporting point, the second reference reporting point and the first parameter, the determining module is specifically configured to perform the following operations: Determine a first two-dimensional coordinate according to the first reference reporting point, the first two-dimensional coordinate is used to reflect the reporting point position of the first reference reporting point, and the first two-dimensional coordinate is (x1, y1); Determine a second two-dimensional coordinate according to the second reference reporting point, the second two-dimensional coordinate is used to reflect the reporting point position of the second reference reporting point, and the second two-dimensional coordinate is (x2, y2); Determine a third two-dimensional coordinate according to the first two-dimensional coordinate, the second two-dimensional coordinate and the first parameter, the third two-dimensional coordinate is used to reflect the reported point position of the first prediction point, and the third two-dimensional coordinate is (x3, y3); in, , .

17. The device according to claim 16, characterized in that In the aspect of determining the second prediction point according to the two application layer reporting point information, the determination module is specifically used to perform the following operations: Determine a fourth time and a third reference reporting point according to the two application layer reporting point information, wherein the fourth time is the last time of the historical application layer reporting period that is second closest to the current application layer reporting period, and the third reference reporting point is the application layer reporting point of the fourth time; Determine a fifth time and a fourth reference reporting point according to the two application layer reporting point information, wherein the fifth time is the last time of the historical bottom application layer cycle closest to the current secondary application layer reporting point cycle, and the fourth reference reporting point is the application layer reporting point of the fifth time; Determine a second parameter according to the third moment, the fourth moment and the fifth moment; The second prediction point is determined according to the third reference reporting point, the fourth reference reporting point and the second parameter.

18. The device according to claim 17, characterized in that The corresponding relationship between the third moment, the fourth moment, the fifth moment and the second parameter is: , wherein a2 is the second parameter, t4 is the fourth moment, and t5 is the fifth moment.

19. The device according to claim 18, characterized in that In the aspect of determining the second prediction point according to the third reference reporting point, the fourth reference reporting point and the second parameter, the determining module is specifically configured to perform the following operations: Determine a fourth two-dimensional coordinate according to the third reference reporting point, the fourth two-dimensional coordinate is used to reflect the reporting point position of the third reference reporting point, and the fourth two-dimensional coordinate is (x4, y4); Determine a fifth two-dimensional coordinate according to the fourth reference reporting point, the fifth two-dimensional coordinate is used to reflect the reporting point position of the fourth reference reporting point, and the fifth two-dimensional coordinate is (x5, y5); Determine a sixth two-dimensional coordinate according to the fourth two-dimensional coordinate, the fifth two-dimensional coordinate and the second parameter, the sixth two-dimensional coordinate is used to reflect the reported point position of the second prediction point, and the sixth two-dimensional coordinate is (x6, y6); in, , .

20. The device according to claim 19, characterized in that In the aspect of determining the target prediction point according to the first prediction point and the second prediction point, the determination module is specifically configured to perform the following operations: Obtain a preset third parameter, where the third parameter is greater than 0 and less than 1; Determine a seventh two-dimensional coordinate according to the third two-dimensional coordinate, the sixth two-dimensional coordinate and the third parameter, the seventh two-dimensional coordinate is used to reflect the reported point position of the target prediction point, and the seventh two-dimensional coordinate is (x7, y7); in, , , a3 is the third parameter.

21. A touch trajectory prediction device, characterized in that: include: One or more processors, a memory, a touch screen, and one or more programs, wherein the one or more programs are stored in the above-mentioned memory and are configured to be executed by the above-mentioned one or more processors, and the one or more programs include instructions for the steps of the touch trajectory prediction method as described in any one of claims 1-10.

22. A computer storage medium, characterized in that The method comprises computer instructions, and when the computer instructions are executed on an electronic device, the electronic device executes the touch trajectory prediction method according to any one of claims 1 to 10.

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