CN117931007B - Low-delay writing method, device, computer equipment and medium - Google Patents
Low-delay writing method, device, computer equipment and medium Download PDFInfo
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- CN117931007B CN117931007B CN202410330428.6A CN202410330428A CN117931007B CN 117931007 B CN117931007 B CN 117931007B CN 202410330428 A CN202410330428 A CN 202410330428A CN 117931007 B CN117931007 B CN 117931007B
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
- G06F3/03—Arrangements for converting the position or the displacement of a member into a coded form
- G06F3/041—Digitisers, e.g. for touch screens or touch pads, characterised by the transducing means
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Abstract
The invention discloses a low-delay writing method, a low-delay writing device, computer equipment and a medium, and belongs to the technical field of multimedia intelligent education blackboards. Comprising the following steps: acquiring a first touch pointTouch points within a predictive modelClassified as points; Judging the type of the next point, if the next point is a moving pressing pointThe prediction model judges whether to generate a predicted pointIf it is generated, it is based on the pressing pointPredicted pointDrawing lines; Circularly acquiring the next pressing pointAnd transmitting into a predictive model that calculates the compression pointsOpposed linesIs a degree of deviation of (2); and automatically correcting and updating the prediction model according to the deviation degree result. The invention can generate the prediction model matched with the user according to the preference self-learning of different users, and is suitable for users with different writing habits.
Description
Technical Field
The invention belongs to the technical field of multimedia intelligent education blackboards, and particularly relates to a low-delay writing method, a low-delay writing device, computer equipment and a medium.
Background
Touch display devices such as electronic whiteboards/all-in-one machines/blackboards generally support annotating writing and other functions, and the functions serve as basic functions for replacing the writing functions of traditional whiteboards/blackboards, so that indexes such as writing time delay and response speed have great influence on user experience. The existing writing software is optimized by various rendering mechanisms, so that the writing delay is reduced, but the problems of no hand following and the like which can be obviously perceived by people still exist. The main bottlenecks at present are:
1. The data of the touch equipment is reported with time delay, the touch equipment acquires the signals of infrared rays, voltage and the like of the touch, and then the signals are transmitted to the computing equipment through equipment calculation and are notified to upper software, and the process has the time delay of 10-50 ms.
2. When An Zhuoban cards are externally connected with other signals, the signals are displayed with delay, video frames need to be cached due to image processing factors such as signal motion compensation, and according to the refresh rate n, the interval between every two frames is 1000/n ms, for example, if a refresh list is 60fps, the delay of 2 frames of cache can reach 35ms.
The current method is limited by factors such as cost, basic science and the like, and the time delay of the two parts is directly compressed in terms of performance, so that the time delay is difficult and the effect is general.
Disclosure of Invention
The invention provides a low-delay writing method, a low-delay writing device, computer equipment and a medium for solving the technical problems in the background technology.
The invention adopts the following technical scheme: a method of low latency writing comprising the steps of: the method comprises the following steps:
Pre-configuring a prediction model to obtain a first touch point And the touch point is touchedA prediction model is transmitted in; touch points within a predictive modelClassified as points; I is the number of points in the prediction model;
judging the type of the next point, if the next point is a moving pressing point According to the pressing pointAnd a touch pointDrawing a line and pressing the pressing pointA prediction model is transmitted in; the prediction model judges whether to generate a predicted pointIf it is generated, it is based on the pressing pointPredicted pointDrawing lines; Pressing points within a predictive modelClassified as points；
Circularly acquiring the next pressing pointAnd transmitting into a predictive model that calculates the compression pointsOpposed linesIs a degree of deviation of (2); determining based on the degree of deviationReliability of (c): eliminating lines if reliability is poorPredicted pointThe predictive model is based on the pressing pointsPressing pointRedrawing lines; According to linesRegenerating the predicted pointPressing the pointClassified as points; J is the number of the true point;
and repeating the steps, and automatically correcting and updating the prediction model when the prediction model predicts the next pressing point.
In a further embodiment, the types of points include: a moving pressing point and a lifting point; if the current point is judged to be the raised point, the writing is ended.
In a further embodiment, the predictive model determines whether to generate the predicted pointThe judging process of (2) is as follows:
a threshold value J for the point number and a threshold value S for the distance pixel are preset, and if the point number of the current pressing point is smaller than the threshold value J or/and the distance pixel between the current pressing point and the last pressing point is smaller than the threshold value S, the predicted point cannot be generated ; Otherwise, generating predicted points。
In a further embodiment, the pressing pointOpposed linesThe degree of deviation of (2) includes at least: deviation of direction and distance; the direction is then the vector trend of the points that have been generated, the distance being the true pixel distance between the two points.
In a further embodiment, the method further comprises the steps of:
Judging whether the user logs in or not, if so, downloading a prediction model of the corresponding user from the server; if the user does not log in, a local preset general prediction model is used.
In a further embodiment, if the image display is delayed during writing, the writing function is turned on, and the corresponding interface is called to stop the image processing; and exiting the writing function and restoring the previous image processing flow.
In a further embodiment, the updated prediction model is uploaded to an account of the corresponding user of the server.
A low-latency writing device, the device comprising:
A first module configured to pre-configure the predictive model to obtain a first touch point And the touch point is touchedA prediction model is transmitted in; touch points within a predictive modelClassified as points; I is the number of points in the prediction model;
A second module configured to determine the type of the next point if the next point is a moving pressed point According to the pressing pointAnd a touch pointDrawing a line and pressing the pressing pointA prediction model is transmitted in; the prediction model judges whether to generate a predicted pointIf it is generated, it is based on the pressing pointPredicted pointDrawing lines; Pressing points within a predictive modelClassified as points；
A third module configured to circularly acquire the next pressing pointAnd transmitting into a predictive model that calculates the compression pointsOpposed linesIs a degree of deviation of (2); determining based on the degree of deviationReliability of (c): eliminating lines if reliability is poorPredicted pointThe predictive model is based on the pressing pointsPressing pointRedrawing lines; According to linesRegenerating the predicted pointPressing the pointClassified as points; J is the number of the true point;
And the fourth module is set to repeat in this way, and the prediction model automatically rectifies and updates the prediction model when the prediction model predicts the next pressing point.
A computer device comprising a memory storing a computer program and a processor implementing the steps of the method as described above when the processor executes the computer program.
A computer readable storage medium having stored thereon a computer program which when executed by a processor realizes the steps of the method as described above.
The invention has the beneficial effects that: the prediction model of the invention can be a point prediction model stored in the cloud, can also be a local universal model, and has wide application range. If the point prediction model is in the cloud, the point prediction model is corresponding to the number ID, the prediction model matched with the user can be generated according to the preference self-learning of different users, and the method is suitable for users with different writing habits. The concrete steps are as follows: the prediction model calculates the deviation degree according to the last prediction point and the actual point transmitted in this time; re-updating parameters according to the deviation degree, and automatically iterating; and adjusting the drawn line according to the deviation degree of the current point returned by the model and the last predicted point.
When the writing function is opened, the signal processing of the channel image at the board card end can be closed; after the writing function is finished, the signal processing of the channel image is re-opened.
Drawings
Fig. 1 is a flow chart of low latency writing.
Detailed Description
The invention is further described below with reference to the drawings and examples of the specification.
In this embodiment, a prediction model Premodel is created by using a smart blackboard OPS whiteboard client to write an example, and a correction model Guidingmodel is embedded in the prediction model Premodel, so that different correction models Guidingmodel are configured according to different users, so that the predicted points conform to the writing habit of the users.
In this embodiment, the smart blackboard OPS whiteboard client is a Windows computer module in an electronic board or an all-in-one machine. And the Windows-end writing whiteboard software is configured.
A method of low latency writing comprising the steps of: the method comprises the following steps:
Pre-configuring a prediction model to judge whether a user logs in, and downloading the prediction model of the corresponding user from a server if the user logs in; if the user does not log in, a local preset general prediction model is used.
Acquiring a first touch pointAnd the touch point is touchedA prediction model is transmitted in; touch points within a predictive modelClassified as points; I is the number of points in the prediction model;
judging the type of the next point, if the next point is a moving pressing point According to the pressing pointAnd a touch pointDrawing a line and pressing the pressing pointA prediction model is transmitted in; the prediction model judges whether to generate a predicted pointIf it is generated, it is based on the pressing pointPredicted pointDrawing lines; Pressing points within a predictive modelClassified as points；
Circularly acquiring the next pressing pointAnd transmitting into a predictive model that calculates the compression pointsOpposed linesIs a degree of deviation of (2); determining based on the degree of deviationReliability of (c): eliminating lines if reliability is poorPredicted pointThe predictive model is based on the pressing pointsPressing pointRedrawing lines; According to linesRegenerating the predicted pointPressing the pointClassified as points; J is the number of the true point;
And repeating the steps, when the prediction model predicts the next pressing point, automatically correcting and updating the prediction model, and uploading the updated prediction model to an account of a corresponding user of the server.
And closing the software, informing the board card to resume image processing, wherein the board card in the implementation is a main control board card of the electronic blackboard/all-in-one machine, is responsible for displaying signals on a point screen, and has an intelligent operating system.
Further, the types of points include: a moving pressing point and a lifting point; if the current point is judged to be the raised point, the writing is ended.
The prediction model judges whether to generate a predicted pointThe judging process of (2) is as follows:
a threshold value J for the point number and a threshold value S for the distance pixel are preset, and if the point number of the current pressing point is smaller than the threshold value J or/and the distance pixel between the current pressing point and the last pressing point is smaller than the threshold value S, the predicted point cannot be generated ; Otherwise, generating predicted points。
The pressing pointOpposed linesThe degree of deviation of (2) includes at least: deviation of direction and distance; the direction is then the vector trend of the points that have been generated, the distance being the true pixel distance between the two points. For example, the number of points is variable, ranging from 3 to 20, depending on the speed of drawing the line, too slow the number of demand points will be large and too fast the number of demand points will be small). The vector trend is a change trend of a plurality of points, and the distance is 34 degrees, 34.5 degrees, 34.6 degrees, 34.7 degrees … … degrees, and the angle of the predicted point should be the last angle +0.1 degrees under the specific uniform change trend.
If the image display is delayed during writing, opening a writing function, and calling a corresponding interface to stop image processing; and exiting the writing function and restoring the previous image processing flow.
Claims (8)
1. A method of low latency writing comprising the steps of: the method comprises the following steps:
Pre-configuring a prediction model, obtaining a first touch point P s, and transmitting the touch point P s into the prediction model; classifying touch point P s as point P l(i) within the predictive model; i is the number of points in the prediction model;
Judging the type of the next point, if the next point is a moving pressing point P m(j), drawing a line according to the pressing point P m(j) and a touch point P s, and transmitting the pressing point P m(j) into a prediction model; judging whether a predicted point P c(j+1) is generated or not by the prediction model, and if so, drawing a line S c(j) based on the pressing point P m(j) and the predicted point P c(j+1); classifying the press point P m(j) as a point P l(j+1) within the predictive model;
The next pressing point P m(j+1) is circularly obtained and is transmitted into a prediction model, and the deviation degree of the pressing point P m(j+1) relative to the line S c(j) is calculated by the prediction model; and judging the reliability of the P c(j+1) based on the deviation degree: if the reliability is poor, eliminating the line S c(j) and the predicted point P c(j+1), and redrawing the line S , c(j) by the predicted model according to the pressing point P m(j+1) and the pressing point P m(j); regenerating a predicted point P c,(j+1) according to the line S , c(j), and classifying the point pressing point P m(j+1) as a point P l(j+1); j is the number of the true point;
Repeating the steps, and automatically correcting and updating the prediction model when the prediction model predicts the next pressing point;
The types of the points include: a moving pressing point and a lifting point; if the current point is judged to be the raised point, ending writing;
the judging process of judging whether to generate the predicted point P c(j+1) by the prediction model is as follows:
A threshold value J for the point number and a threshold value S for the distance pixel are preset, and if the point number of the current pressing point is smaller than the threshold value J or/and the distance pixel between the current pressing point and the last pressing point is smaller than the threshold value S, the predicted point P c(j+1) cannot be generated; and otherwise, generating a predicted point P c(j+1).
2. The method of low latency writing according to claim 1, wherein the degree of deviation of the pressing point P m(j+1) from the line S c(j) includes at least: deviation of direction and distance; the direction is then the vector trend of the points that have been generated, the distance being the true pixel distance between the two points.
3. A method of low latency writing according to claim 1, further comprising the steps of:
Judging whether the user logs in or not, if so, downloading a prediction model of the corresponding user from the server; if the user does not log in, a local preset general prediction model is used.
4. A method of low latency writing according to claim 1, wherein if the image display is delayed during writing, the writing function is turned on, and the corresponding interface is invoked to stop image processing; and exiting the writing function and restoring the previous image processing flow.
5. A method of low latency writing according to claim 3, wherein the updated predictive model is uploaded to the account of the corresponding user at the server.
6. A low latency writing device for implementing the method of low latency writing of any of claims 1 to 5, the device comprising:
The first module is configured to pre-configure a prediction model, acquire a first touch point P s, and transmit the touch point P s into the prediction model; classifying touch point P s as point P l(i) within the predictive model; i is the number of points in the prediction model;
The second module is configured to judge the type of the next point, if the next point is a moving pressing point P m(j), drawing a line according to the pressing point P m(j) and a touch point P s and transmitting the pressing point P m(j) into the prediction model; judging whether a predicted point P c(j+1) is generated or not by the prediction model, and if so, drawing a line S c(j) based on the pressing point P m(j) and the predicted point P c(j+1); classifying the press point P m(j) as a point P l(j+1) within the predictive model;
A third module configured to circularly acquire a next pressing point P m(j+1) and to input a prediction model that calculates a degree of deviation of the pressing point P m(j+1) from the line S c(j); and judging the reliability of the P c(j+1) based on the deviation degree: if the reliability is poor, eliminating the line S c(j) and the predicted point P c(j+1), and redrawing the line S , c(j) by the predicted model according to the pressing point P m(j+1) and the pressing point P m(j); regenerating a predicted point P c,(j+1) according to the line S , c(j), and classifying the point pressing point P m(j+1) as a point P l(j+1); j is the number of the true point;
The fourth module is set to repeat in this way, and when the prediction model predicts the next pressing point, the prediction model is automatically corrected and updated;
wherein the types of the points include: a moving pressing point and a lifting point; if the current point is judged to be the raised point, ending writing;
the judging process of judging whether to generate the predicted point P c(j+1) by the prediction model is as follows:
A threshold value J for the point number and a threshold value S for the distance pixel are preset, and if the point number of the current pressing point is smaller than the threshold value J or/and the distance pixel between the current pressing point and the last pressing point is smaller than the threshold value S, the predicted point P c(j+1) cannot be generated; and otherwise, generating a predicted point P c(j+1).
7. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any one of claims 1 to 5 when the computer program is executed.
8. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 5.
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