Optimization method and device for three-dimensional object touch interaction interface, equipment and medium

Abstract

The invention relates to an optimization method and device for a three-dimensional object touch interaction interface, equipment and a medium. According to the method, to-be-selected interaction interfaces with different types of interaction influence factors and different interaction feedback levels of the interaction influence factors are constructed; enabling the testee to execute a preset touch interaction task on each to-be-selected interaction interface, recording a touch duration and a bias error rate corresponding to the execution of each touch interaction task on each to-be-selected interaction interface, and judging the execution efficiency of the touch interaction tasks on different to-be-selected interaction interfaces according to the touch duration and the bias error rate; therefore, the interaction influence factors and the interaction feedback level which are beneficial to the touch interaction efficiency are determined by comparing the execution efficiency differences, and the optimization of the touch interaction interface of the three-dimensional object is realized.

Description

Technical Field

[0001] The present invention relates to the field of computer interface interaction technology, and in particular to a method, device, equipment and medium for optimizing a three-dimensional object touch interaction interface. Background Art

[0002] With the development and widespread application of new-generation information technologies such as the Internet of Things and big data, manufacturing and production activities are gradually moving towards intelligence, and digital twins have developed accordingly and have more applications. Digital twins refer to the use of digital technology to create a digital model corresponding to a physical entity or system in a virtual space. This model can reflect the state, behavior and characteristics of the physical entity in real time, and monitor, simulate and optimize through sensors, data analysis and AI technology, thereby improving productivity.

[0003] The interactivity of the digital twin system is one of the keys to improving productivity. Touch interaction is mainly used because it is more intuitive and efficient for users. During the touch interaction process, the interactive interface is the way for users to receive information and complete cognitive and operational responses. The effectiveness of the interactive interface in expressing information to users and the degree of fit between the interactive interface content expression form and user cognitive understanding will directly affect the user experience and interaction efficiency during the touch interaction process.

[0004] In the interactive process, three-dimensional interaction is more efficient in expressing information, so three-dimensional object touch interaction is more commonly used in current interactions. Clarifying the factors that affect the efficiency of users' touch interaction with three-dimensional objects during use, thereby guiding the design of three-dimensional object touch interaction interfaces, is a direct and effective way to improve interaction efficiency. Summary of the invention

[0005] In view of this, an embodiment of the present invention provides a method, device, equipment and medium for optimizing a three-dimensional object touch interaction interface to solve the problem of how to determine the influencing factors affecting the three-dimensional object touch interaction so as to complete the design optimization of the three-dimensional object touch interaction interface.

[0006] In a first aspect, a method for optimizing a three-dimensional object touch interaction interface is provided, the method comprising:

[0007] Setting a preset number of interaction feedback levels for each interaction influencing factor, combining various interaction influencing factors with different interaction feedback levels, and constructing a candidate interaction interface corresponding to each combination;

[0008] Execute each three-dimensional object operation task a set number of times on all the to-be-selected interactive interfaces, and determine the touch duration and error rate for completing each three-dimensional object operation task on each of the to-be-selected interactive interfaces;

[0009] According to the touch duration and the error rate, a candidate interaction interface that can improve the three-dimensional object touch interaction effect is determined, and the optimization of the three-dimensional object touch interaction interface is completed.

[0010] In a second aspect, a device for optimizing a three-dimensional object touch interaction interface is provided, the device comprising:

[0011] A candidate interaction interface construction module is used to set a preset number of interaction feedback levels for each interaction influencing factor, combine various interaction influencing factors with different interaction feedback levels, and construct a candidate interaction interface corresponding to each combination;

[0012] A touch interaction efficiency detection module, used to execute each three-dimensional object operation task a set number of times on all the to-be-selected interaction interfaces, and determine the touch duration and error rate for completing each three-dimensional object operation task on each of the to-be-selected interaction interfaces;

[0013] The touch interaction interface optimization module is used to determine a candidate interaction interface that can improve the touch interaction effect of the three-dimensional object according to the touch duration and the error rate, and complete the optimization of the touch interaction interface of the three-dimensional object.

[0014] In a third aspect, an embodiment of the present invention provides a computer device, comprising a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method for optimizing the touch interaction interface of a three-dimensional object as described in the first aspect when executing the computer program.

[0015] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for optimizing the touch interaction interface of a three-dimensional object as described in the first aspect is implemented.

[0016] Compared with the prior art, the present invention has the following beneficial effects:

[0017] The present invention constructs candidate interaction interfaces with different types of interaction influencing factors and different interaction feedback levels for each interaction influencing factor, and enables subjects to perform pre-set touch interaction tasks on each candidate interaction interface and records the touch duration and error rate corresponding to the execution of various touch interaction tasks on each candidate interaction interface. The touch duration and error rate are used to judge the execution efficiency of the touch interaction tasks on different candidate interaction interfaces, and the interaction influencing factors and interaction feedback levels that are beneficial to the touch interaction efficiency are determined by comparing the differences in execution efficiency, thereby achieving optimization of the touch interaction interface of three-dimensional objects. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0019] Figure 1 This is a schematic diagram of an application environment of a method for optimizing a three-dimensional object touch interaction interface provided by the first embodiment of the present invention;

[0020] Figure 2 It is a flowchart of a method for optimizing a three-dimensional object touch interaction interface provided by the first embodiment of the present invention;

[0021] Figure 3 is a schematic diagram of a device involved in touch interaction in an embodiment of the present invention;

[0022] Figure 4 is a schematic diagram of touch interaction task types listed in an embodiment of the present invention;

[0023] Figure 5 is a schematic diagram of the measurement of depth perception and the corresponding device in the present invention;

[0024] Figure 6 is a schematic diagram of a touch interaction interface when depth perception clues and visual feedback are used as interaction influencing factors in one embodiment of the present invention;

[0025] Figures 7 to 9 In one embodiment of the present invention, Figure 6 A schematic diagram of the touch interaction interface performing the touch interaction tasks of moving, rotating and scaling;

[0026] Fig.10 is a schematic diagram of various candidate interaction interfaces when depth perception clues and visual feedback forms are used as interaction influencing factors in one embodiment of the present invention;

[0027] Fig.11 is a schematic diagram of the measurement results of the subject's behavior in one embodiment of the present invention;

[0028] Fig.12 It is a flowchart of a method for determining a candidate interaction interface that can improve the touch interaction effect of a three-dimensional object provided by an embodiment of the present invention;

[0029] Fig.13 is a schematic diagram of an experimental scene in which an eye tracker is added in one embodiment of the present invention;

[0030] Fig.14 is a schematic diagram of a heat map and a trajectory map obtained based on eye movement data in one embodiment of the present invention;

[0031] Fig.15 as well as Fig.16 is a statistical diagram of the total touch duration and total workload of each task in one embodiment of the present invention;

[0032] Fig.17 It is a structural schematic diagram of a device for optimizing a three-dimensional object touch interaction interface provided by a second embodiment of the present invention;

[0033] Fig.18 It is a structural diagram of a computer device provided in Embodiment 3 of the present invention. DETAILED DESCRIPTION

[0034] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present invention. However, it should be clear to those skilled in the art that the present invention may be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present invention.

[0035] It should be understood that when used in the present specification and the appended claims, the term "comprising" indicates the presence of described features, integers, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or combinations thereof.

[0036] It should also be understood that the term "and / or" used in the present description and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.

[0037] As used in the present specification and the appended claims, the term "if" can be interpreted as "when" or "uponce" or "in response to determining" or "in response to detecting", depending on the context. Similarly, the phrase "if it is determined" or "if [described condition or event] is detected" can be interpreted as meaning "uponce it is determined" or "in response to determining" or "uponce [described condition or event] is detected" or "in response to detecting [described condition or event]", depending on the context.

[0038] In addition, in the description of the present specification and the appended claims, the terms "first", "second", "third", etc. are only used to distinguish the descriptions and cannot be understood as indicating or implying relative importance.

[0039] References to "one embodiment" or "some embodiments" etc. described in the present specification mean that one or more embodiments of the present invention include specific features, structures or characteristics described in conjunction with the embodiment. Therefore, the statements "in one embodiment", "in some embodiments", "in some other embodiments", "in some other embodiments", etc. that appear in different places in this specification do not necessarily refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways. The terms "including", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0040] The embodiments of the present invention can acquire and process relevant data based on artificial intelligence technology. Artificial Intelligence (AI) is the theory, method, technology and application system that uses digital computers or machines controlled by digital computers to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the best results.

[0041] AI basic technologies generally include sensors, dedicated AI chips, cloud computing, distributed storage, big data processing technology, operation / interaction systems, mechatronics, etc. AI software technologies mainly include computer vision technology, robotics technology, biometrics technology, speech processing technology, natural language processing technology, and machine learning / deep learning.

[0042] It should be understood that the order of execution of the steps in the following embodiments does not imply a precedence of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0043] In order to illustrate the technical solution of the present invention, specific embodiments are provided below for illustration.

[0044] A method for optimizing a three-dimensional object touch interaction interface provided by the first embodiment of the present invention can be applied in the following aspects: Figure 1 In an application environment, a client communicates with a server. The client includes but is not limited to a PDA, a desktop computer, a laptop computer, an ultra-mobile personal computer (UMPC), a netbook, a cloud terminal device, a personal digital assistant (PDA), and other terminal devices. The server can be implemented by an independent server or a server cluster consisting of multiple servers.

[0045] See also Figure 2, is a flow chart of a method for optimizing a three-dimensional object touch interaction interface provided by the first embodiment of the present invention. The method for optimizing a three-dimensional object touch interaction interface can be applied to Figure 1 The server side in the embodiment of the present invention is connected to a corresponding database, rule base, etc., and the corresponding computer device of the server side is connected to the corresponding database, rule base, etc. to obtain the corresponding data in the database. The above-mentioned computer device is also connected to the client side to collect the data and control instructions sent by the client user, and provide the user with information display and content response after the user operation to successfully realize the interaction.

[0046] like Figure 2 As shown, the optimization method of the three-dimensional object touch interaction interface may include the following steps:

[0047] Step S101 : setting a preset number of interaction feedback levels for each interaction influencing factor, combining various interaction influencing factors with different interaction feedback levels, and constructing a candidate interaction interface corresponding to each combination.

[0048] like Figure 3 As shown, touch interaction is involved in smart phones, dashboards and tablet devices. In the actual application of the touch interaction system, there are many factors that affect the touch interaction efficiency of the three-dimensional object transformation. This embodiment evaluates the touch interaction efficiency of the three-dimensional object transformation to find out how various influencing factors affect the touch interaction efficiency of the three-dimensional object transformation, thereby guiding the interaction design and improving the user experience.

[0049] In order to explore the influence of various interaction factors on the touch interaction efficiency of three-dimensional object transformation in the three-dimensional object touch interaction interface, this embodiment sets the following touch interaction efficiency based on the common touch behavior of users on three-dimensional object transformation: Figure 4 The three tasks of moving, rotating and scaling are shown, and for the sake of ease of description, it is assumed that the target three-dimensional object is a cube. In order to maximize the optimization degree of the touch interaction interface, this embodiment takes into account the various types of interaction influencing factors and the need to consider multiple interaction influencing factors. It also takes into account that the interaction feedback level of a single interaction influencing factor will also affect the user's information receiving efficiency and cognitive response efficiency when using the touch interaction interface, so a preset number of interaction feedback levels is additionally set for each interaction influencing factor. Among them, setting a preset number of interaction feedback levels for each interaction influencing factor means that the number of interaction feedback levels of different interaction influencing factors can be the same or different, and the preset number of interaction feedback levels can be 1 or greater than 1.

[0050] After setting a preset number of interactive feedback levels for each interactive influencing factor, different interactive feedback levels can be selected from each interactive influencing factor to combine all interactive influencing factors. Each combination includes all the selected interactive influencing factors, and the interactive feedback levels of the interactive influencing factors in different combinations are not completely the same. For each combination, a corresponding interactive interface can be constructed as a candidate interactive interface for subsequent subjects to verify its interactive effect.

[0051] In this embodiment, a total of 24 subjects were recruited, including 12 males and 12 females, aged 21 to 29. All subjects had good vision or corrected vision, no color blindness or color weakness, were right-handed, had 7 to 14 years of experience in using touch devices, and were students of different majors such as industrial design, mechanical engineering, and information engineering.

[0052] Regarding the relevant software used in the experiment, Unity 3D was used to write the experimental task program, ErgoLAB program was used to synchronize the human-computer environment, and SPSS and MATLAB were used to analyze the experimental data. The experimental task program was run using a Microsoft Surface Book 2 laptop. The experiment was conducted under normal lighting conditions under a 40-watt fluorescent lamp. The distance from the subject's eyes to the screen was controlled at 55-60 cm, the viewing angle was 11.45°, the screen size was 15 inches, the resolution was set to 3000*2000, the refresh rate was 60Hz, the color format was RGB, and the color space was standard dynamic range (SDR).

[0053] Step S102, executing each three-dimensional object operation task a set number of times on all the to-be-selected interaction interfaces, and determining the touch duration and error rate for completing each three-dimensional object operation task on each of the to-be-selected interaction interfaces.

[0054] After clarifying the selection of experimental objects, i.e., subjects, the setting of corresponding experimental environment and experimental conditions, and the different types of candidate interaction interfaces used for the experiment, each subject can perform the preset touch interaction task on each candidate interaction interface in turn. The specific execution method can be: first perform one of the touch interaction tasks, such as the rotation task, and then based on the value of the set number of times, that is, the number of times the selected touch interaction task (such as the rotation task) needs to be performed on each candidate interaction interface, the total number of trials is obtained, and then the subject randomly performs each trial from all the trials in turn. Between two adjacent trials, the subject can have sufficient rest time to eliminate the test errors caused by fatigue, and after each trial, the touch duration and error rate of the subject completing the touch interaction task or the three-dimensional object operation task in the trial will be recorded.

[0055] After all the trials corresponding to the touch interaction tasks are completed, the touch duration and error rate of each of the three-dimensional object operation tasks completed on each of the selected interactive interfaces can be determined. The touch duration is easy to understand, that is, the duration of the three-dimensional object operation task, and the error rate refers to the degree of deviation between the actual position and the target position of the target three-dimensional object after the three-dimensional object operation task is completed. That is, the error rate calculation method is the absolute value of the difference between the actual coordinates of the target three-dimensional object and the target coordinates, divided by the shortest coordinate distance of the target three-dimensional object from the initial state to the target state, and the result is multiplied by 100% to obtain the error rate in percentage form. The specific formula is as follows:

[0056]

[0057] Among them, Deviation Ratio represents the error rate, P actual represents the actual coordinates of the target three-dimensional object, P target represents the target coordinates of the target 3D object, P initial Indicates the initial coordinates of the target 3D object.

[0058] Based on the fact that the three-dimensional object operation tasks set in this embodiment are specifically movement, rotation and scaling, the error rate calculation methods for the three tasks are specifically as follows.

[0059] For the moving task, assuming that the target 3D object moves along the x-axis, the error rate is:

[0060]

[0061] Among them, Deviation Ratiomove represents the error rate of the mobile task, Indicates the actual x-axis coordinate of the target three-dimensional object. represents the x-axis target coordinate of the target three-dimensional object, and X0 represents the x-axis initial coordinate of the target three-dimensional object.

[0062] For the rotation task, assuming that the target three-dimensional object rotates on the xy plane, that is, it rotates with the z axis as the rotation center, then the error rate is:

[0063]

[0064] Among them, Deviation Ratio rotate represents the rotation task error rate, Indicates the angle of rotation of the target 3D object on the xy plane. Since the target 3D object is a cube with a square cross section on the xy plane, every 90 degree rotation of the target 3D object on the xy plane is considered The values ​​are consistent, represents the target angle of the target 3D object, Indicates the initial angle of the target 3D object.

[0065] The error rate for the scaling task is:

[0066]

[0067] Among them, Deviation Ratio scale represents the error rate of the scaling task, Indicates the actual size of the target three-dimensional object in the y-axis direction. It represents the target size of the target three-dimensional object in the y-axis direction, and Y0 represents the initial size of the target three-dimensional object in the y-axis direction.

[0068] Step S103, determining a candidate interaction interface that can improve the three-dimensional object touch interaction effect according to the touch duration and the error rate, and completing the optimization of the three-dimensional object touch interaction interface.

[0069] After obtaining the touch duration and error rate corresponding to each touch interaction task implemented on different candidate interaction interfaces, the variable control method can be used to clarify which interaction influencing factor has a more obvious impact on the touch interaction. After further determining the interaction influencing factors with a more obvious impact, continue to determine which interaction feedback level among the interaction influencing factors with a more obvious impact has a more prominent impact on the touch interaction, so as to finally determine a single or multiple candidate interaction interfaces that can improve the touch interaction effect of three-dimensional objects, and select them as the actual touch interaction interface to complete the optimization of the touch interaction interface of three-dimensional objects.

[0070] The method in this embodiment constructs candidate interaction interfaces with different types of interaction influencing factors and different interaction feedback levels for each interaction influencing factor, and enables the subjects to perform pre-set touch interaction tasks on each candidate interaction interface, and then records the touch duration and error rate corresponding to the various touch interaction tasks performed on each candidate interaction interface. By comparing the differences in touch duration and error rate corresponding to different candidate interaction interfaces, the interaction influencing factors and interaction feedback levels that are beneficial to the touch interaction efficiency are determined, thereby achieving the optimization of the touch interaction interface of the three-dimensional object.

[0071] In one embodiment, the specific method for determining the touch duration and error rate for completing each of the three-dimensional object operation tasks on each of the to-be-selected interactive interfaces in step S102 is as follows:

[0072] After all subjects have executed the current three-dimensional object operation task a set number of times on the current interaction interface to be selected, the mean touch duration and the mean error rate of all the subjects who executed the current three-dimensional object operation task the set number of times on the current interaction interface to be selected are calculated, and the mean touch duration is used as the touch duration for completing the current three-dimensional object operation task on the current interaction interface to be selected, and the mean error rate is used as the error rate for completing the current three-dimensional object operation task on the current interaction interface to be selected.

[0073] Taking into account that the value of the set number of times can be 1 or greater than 1, and in order to improve the accuracy of the experiment, it is usually preferred to set the value of the set number of times to be greater than 1, so after a certain three-dimensional object operation task is executed on a certain interactive interface to be selected, it is necessary to average it to improve the accuracy of the execution result, that is, to average the touch duration and error rate of the current three-dimensional object operation task performed the set number of times by all the subjects on the current interactive interface to be selected, and use the obtained average as the touch duration and error rate for completing the current three-dimensional object operation task on the current interactive interface to be selected.

[0074] In one embodiment, considering that a large number of three-dimensional scenes displayed in digital twin systems are mainly affected by two interactive influencing factors: depth perception cues and visual feedback forms, this implementation limits the interactive influencing factors to depth perception cues and visual feedback forms, so as to improve the overall optimization efficiency of the three-dimensional object touch interaction interface of the digital twin system.

[0075] Among them, the earliest measurement of depth perception began with the three pins experiment designed by HVHelmholtz. Figure 5 On this basis, HJ Howard designed the first depth perception tester. The subjects observed through a rectangular window. One of the two straight sticks was fixed, and the position of the other straight stick needed to be adjusted until the two straight sticks were considered to be side by side and stopped moving, as shown in Figure 1. Figure 5 As shown in part b on the right side of the figure.

[0076] Based on the interactive factors, specifically the depth perception clues and visual feedback forms, the previous construction of the depth perception measurement scene, and the limitation of the target three-dimensional object as a cube in the above embodiment, the following is given: Figure 6 The specific scenario of the touch interaction task shown in the figure is as follows: x A movable three-dimensional object, a cube ref is an immovable reference cube, and other randomly distributed cubes. x and cuberef It is a cuboid with a length, width and height ratio of 1:1:8. In addition, the sizes and positions of other cubes are random, which can form occlusions to provide some depth perception clues and increase the difficulty of the task.

[0077] Based on the specific scenario of the given touch interaction task, the touch interaction tasks at this time, namely, the moving, rotating, and scaling tasks are as follows: Figures 7 to 9 As shown, the target three-dimensional object, that is, the cube, is realized in turn. x position, angle and size of touch.

[0078] Specifically, the moving task is to slide up and down with one finger to control the cube x Move forward and backward on the x-axis, with the target cubes on both sides ref The front and back positions are consistent; the rotation task is to move the cube in the middle left and right with one finger x Rotate left and right along its own z-axis, and the cube ref The angle is consistent. In the rotation task at this time, since both left and right rotations can reach the target state, if the cube is randomly set x The initial angle and target angle of the left and right directions may be inconsistent. To control this variable, the difference between the two was set to 45 degrees in the formal experiment. The zoom task is to pinch and expand the control cube with two fingers. x Zoom in and out based on its own geometric center, similar to cube ref After collecting data and conducting preliminary analysis, it was found that the independent variable of depth perception cues did not have a significant impact on the dependent variable. Therefore, randomly placed blocks were added to the formal experiment to form occlusion, provide partial depth perception cues, and increase the difficulty of the task.

[0079] Further, in another embodiment, based on the fact that the interaction influencing factors are specifically defined as depth perception clues and visual feedback forms, the step of setting a preset number of interaction feedback levels for each interaction influencing factor includes:

[0080] The interactive feedback levels of the depth perception cues include weak depth, medium depth and strong depth. The different interactive feedback levels of the depth perception cues are achieved by changing the ambient light and the material of the object. The interactive feedback levels in the form of visual feedback include no feedback, partial feedback and full feedback. No feedback means that the target three-dimensional object has no feedback when being controlled. The partial feedback means that the color of the target three-dimensional object changes to a preset color when it is controlled to reach the target state. The full feedback means that the color of the target three-dimensional object gradually changes to the preset color in the process of being controlled to reach the target state.

[0081] The interactive feedback level settings based on depth perception cues and the interactive feedback level settings in the form of visual feedback correspond to Fig.10 The variable control chart shown shows nine candidate interaction interfaces formed by the intersection of depth perception cues under weak depth, medium depth and strong depth and visual feedback forms under no feedback, partial feedback and full feedback.

[0082] In this embodiment, the preset color is green, and any feasible color, such as red, can be selected in other embodiments. Based on the selected preset color of green, it is necessary to further explain that the non-feedback in the form of visual feedback specifically refers to the target three-dimensional object, that is, Figure 6 The cube shown x , in such Fig.10 There is no color change in the movement task shown, and the partial feedback in the form of visual feedback specifically refers to the target three-dimensional object, that is, Figure 6 The cube shown x , in such Fig.10 In the moving task shown in the figure, when the target position is reached, the color suddenly turns green. The full feedback in the form of visual feedback specifically refers to the target three-dimensional object, that is, Figure 6 The cube shown x , in such Fig.10 In the moving task shown, the color gradually changes from white to green as the image approaches the target position from the initial position.

[0083] Corresponds to Fig.10 The candidate interaction interface shown in the figure can be formed after all subjects complete the experiment. Fig.11 The behavior measurement result diagram of the subjects shown in FIG. 1 and the behavior measurement result data table shown in Table 1 below, wherein the preferred setting value of the number of times in this embodiment is 3 times, that is, in a certain specified three-dimensional object operation task, each subject needs to perform the operation as shown in FIG. Fig.10 The specified three-dimensional object operation task was performed three times on each of the candidate interaction interfaces shown, for a total of 27 trials, and the presentation order of the trials was random to eliminate the sequence effect and ensure the reliability and validity of the experimental results.

[0084] Table 1

[0085]

[0086]

[0087] Depend on Fig.11 And from Table 1, we can see that:

[0088] The average touch duration of medium depth perception clues is slightly shorter than that of weak and strong, and the average touch duration of weak and strong is not much different. The average error rates of each depth perception line are relatively close. The average touch duration of partial visual feedback is the shortest, followed by full visual feedback. The average touch duration of no visual feedback is the longest, and the average error rate of partial visual feedback is also the lowest. There is no obvious difference in the average error rate between full visual feedback and no visual feedback.

[0089] After clarifying the setting method of the specific interactive feedback levels for depth perception cues and visual feedback forms, this embodiment provides the difference analysis results of the impact of different interactive feedback levels in each interactive influencing factor on the touch interaction efficiency of three-dimensional objects, and realizes a basis for how to further improve the touch interaction efficiency by selecting different interactive feedback levels when the interactive influencing factors are depth perception cues and visual feedback forms, thereby improving the optimization effect of the three-dimensional object touch interaction interface.

[0090] Furthermore, based on the test subject behavior measurement results given in the above embodiment, Fig.12 As shown, in another embodiment, the step S103 of determining a candidate interaction interface that can improve the touch interaction effect of the three-dimensional object according to the touch duration and the error rate includes:

[0091] Step S1031 , taking the depth perception cue and the visual feedback form as variables, respectively performing a variance analysis on the touch duration and a two-factor repeated measures variance analysis on the error rate.

[0092] In order to further quantitatively analyze the difference in the impact of different interactive feedback levels on touch interaction efficiency in the same interaction influencing factor, the above Fig.11 The behavioral measurement results of the subjects shown in Table 1 were further analyzed.

[0093] Specifically, a two-way repeated measures analysis of variance (Two-way Repeated Measures Anova) was conducted to examine the effects of depth perception cues and visual feedback on touch duration and deviation ratio in the three tasks of moving, rotating, and scaling. During data preprocessing, MATLAB was used to perform Box-Cox transformation on the original data, and the converted data was subjected to Kolmogorov-Smimov normality test using SPSS, and the data followed a normal distribution.

[0094] The variance analysis results are shown in Table 2 and Table 3 below, respectively. Taking the depth perception cue and the visual feedback condition as variables, the variance analysis results on the touch duration are shown in Table 2, and the variance analysis results on the error rate are shown in Table 3.

[0095] Table 2

[0096]

[0097]

[0098] Table 3

[0099]

[0100] Among them, F represents the F statistic, which is the ratio of the mean square between groups to the mean square within groups, and is used to judge the significance of the difference between groups. df represents the degree of freedom, p represents the p value, and is used to judge the degree of certainty of the statistical hypothesis. p 2 Represents effect value, which is used to estimate the effect size of the independent variable.

[0101] Step S1032, in the variance analysis results about the touch duration or the variance analysis results about the error rate, if the interaction between the depth perception cue and the visual feedback form is significant, then a simple effect test is performed on the touch duration or the error rate corresponding to the significant interaction between the depth perception cue and the visual feedback form; if the interaction between the depth perception cue and the visual feedback form is not significant, then multiple comparisons are performed on the touch duration or the error rate corresponding to the significant main effect of the interaction factors between the depth perception cue and the visual feedback form.

[0102] After obtaining the variance analysis results on the touch duration and the variance analysis results on the error rate, the data analysis results of the three tasks of move, rotate, and scale are described in turn.

[0103] 1. About mobile tasks:

[0104] As shown in Table 2, the results of the variance analysis on touch duration showed that the main effect of depth perception cues was not significant in the movement task (F=0.321, p=0.726>0.05, η p 2 =0.005), the main effect of visual feedback form was extremely significant (F = 14.007, p < 0.01, ηp 2 =0.165), the interaction effect between the two was not significant (F = 1.468, p = 0.212 > 0.05, η p 2 =0.020).

[0105] As shown in Table 3, the results of the variance analysis on the deviation ratio showed that the main effect of depth perception cues was not significant in the movement task (F = 0.917, p = 0.402 > 0.05, η p 2 =0.013), the main effect of visual feedback form was extremely significant (F = 20.148, p < 0.01, η p 2 =0.221), the interaction effect between the two was not significant (F = 2.225, p = 0.066 > 0.05, η p 2 =0.030).

[0106] Since the main effects of visual feedback form in the variance analysis results on touch duration and error rate were extremely significant, and the main effects of depth perception cues in the variance analysis results on touch duration and error rate were extremely insignificant, and the interaction effect between the two was not significant in the variance analysis results on touch duration and error rate, multiple comparisons were further performed on the touch duration and error rate of the visual feedback condition, and the multiple comparison results of touch duration under the visual feedback form in the movement task as shown in Table 4 below, and the multiple comparison results of error rate under the visual feedback form in the movement task as shown in Table 5 below were obtained.

[0107] Table 4

[0108]

[0109] Based on estimated marginal means

[0110] *.The mean difference is significant at the 0.05level.

[0111] b.Adjustment for multiple comparisons: Bonferroni.

[0112] Table 5

[0113]

[0114] Based on estimated marginal means

[0115] *.The mean difference is significant at the 0.05level.

[0116] b.Adjustment for multiple comparisons: Bonferroni.

[0117] The results of multiple comparisons of touch duration under visual feedback in the mobile task are shown in Table 4. There is a significant difference between no visual feedback and partial visual feedback (p < 0.01), a significant difference between no visual feedback and full visual feedback (p < 0.01), and no significant difference between partial visual feedback and full visual feedback (p = 1.000 > 0.05). The results show that both partial visual feedback and full visual feedback significantly shorten the touch duration, but the degree of influence of the two on the touch duration is similar.

[0118] The results of multiple comparisons of the error rate under visual feedback in the mobile task are shown in Table 5. There is a significant difference between no visual feedback and partial visual feedback (p < 0.01), no significant difference between no visual feedback and full visual feedback (p = 0.625 > 0.05), and a significant difference between partial visual feedback and full visual feedback (p < 0.01). The results show that partial visual feedback can significantly reduce the error rate, but the influence of full visual feedback on the error rate is similar to that of no visual feedback, and it does not significantly reduce the error rate.

[0119] 2. About the rotation task:

[0120] As shown in Table 2, the results of the variance analysis on touch duration showed that the main effects of depth perception cues and visual feedback form were not significant in the rotation task (F = 1.842, p = 0.162 > 0.05, η p 2 =0.025) (F=1.010, p=0.367>0.05, η p 2 =0.014), the interaction effect between the two was not significant (F = 0.549, p = 0.677 > 0.05, η p 2 =0.008).

[0121] As shown in Table 3, the results of the variance analysis on the deviation ratio showed that the main effects of depth perception cues and visual feedback form were not significant in the rotation task (F = 0.626, p = 0.536 > 0.05, η p 2 =0.009) (F=2.437, p=0.091>0.05, η p 2 =0.033), the interaction effect between the two was significant (F = 2.529, p = 0.041 < 0.05, η p 2 =0.034).

[0122] Since the interaction effect between depth perception cues and visual feedback forms was significant in the variance analysis results of the error rate, a simple effects test was further conducted on depth perception cues and visual feedback forms. The results of the simple effects test of depth perception cues × visual feedback forms on the error rate are shown in Table 6 below, and the results of the simple effects test of visual feedback forms × depth perception cues on the error rate are shown in Table 7 below.

[0123] Table 6

[0124]

[0125]

[0126] Based on estimated marginal means

[0127] *.The mean difference is significant at the 0.05level.

[0128] b.Adjustment for multiple comparisons: Sidak.

[0129] Table 7

[0130]

[0131] Based on estimated marginal means

[0132] *.The mean difference is significant at the 0.05level.

[0133] b.Adjustment for multiple comparisons: Sidak.

[0134] As shown in Table 6, in the case of weak depth perception cues, the difference in the effect of partial visual feedback and full visual feedback on the deviation ratio is significant (p=0.021<0.05). As shown in Table 7, in the case of partial visual feedback, the difference in the effect of weak depth perception cues and strong depth perception cues on the deviation ratio is significant (p=0.035<0.05).

[0135] The results show that in the case of weak depth perception cues, the error rate of partial visual feedback is lower than that of full visual feedback; in the case of partial visual feedback, the error rate of strong depth perception cues is lower than that of weak depth perception cues.

[0136] 3. About scaling tasks:

[0137] As shown in Table 2, the results of the variance analysis on touch duration showed that the main effect of depth perception cues was extremely significant in the zoom task (F=11.727, p<0.01, η p 2 =0.142), and the main effect of visual feedback form was extremely significant (F = 5.050, p = 0.008 < 0.01, η p 2 =0.066, the interaction effect between the two was not significant (F = 0.235, p = 0.918 > 0.05, η p 2 =0.014).

[0138] As shown in Table 3, the results of the variance analysis on the deviation ratio showed that the main effect of depth perception cues was not significant in the zoom task (F = 0.523, p = = 0.594 > 0.05, η p 2 =0.007), the main effect of visual feedback form was not significant (F = 0.410, p = = 0.664 > 0.05, η p 2 = = 0.006), the interaction effect between the two was not significant (F = 1.414, p = 0.229 < 0.05, η p 2 =0.020).

[0139] Since the interaction effect between depth perception cues and visual feedback forms was not significant in the variance analysis results for both touch duration and error rate, and the main effects of depth perception cues and visual feedback forms were extremely significant in the variance analysis results for touch duration, and the main effects of depth perception cues and visual feedback forms were not significant in the variance analysis results for error rate, we further performed multiple comparisons on the touch duration of depth perception cues, as shown in Table 8, and performed multiple comparisons on the touch duration of visual feedback forms, as shown in Table 9.

[0140] Table 8

[0141]

[0142] Based on estimated marginal means

[0143] *.The mean difference is significant at the.05level.

[0144] b.Adjustment for multiple comparisons: Bonferroni.

[0145] Table 9

[0146]

[0147]

[0148] Based on estimated marginal means

[0149] *.The mean difference is significant at the.05level.

[0150] b.Adjustment for multiple comparisons: Bonferroni.

[0151] The multiple comparison results of touch duration under depth perception cues in the zoom task are shown in Table 8. The difference between weak depth perception cues and medium depth perception cues is extremely significant (p=0.000<0.01), the difference between weak depth perception cues and strong depth perception cues is not significant (p=0.238>0.05), and the difference between medium depth perception cues and strong depth perception cues is extremely significant (p=0.009<0.01). The results show that medium depth perception cues significantly shorten the touch duration, but strong depth perception cues and weak depth perception cues have similar effects on touch duration and do not significantly shorten the touch duration.

[0152] The multiple comparison results of touch duration under visual feedback in the zoom task are shown in Table 9. There is no significant difference between no visual feedback and partial visual feedback (p=1.000>0.05), there is a significant difference between no visual feedback and full visual feedback (p=0.022<0.05), and there is a significant difference between partial visual feedback and full visual feedback (p=0.025<0.05). The results show that full visual feedback significantly shortens the touch duration, but no visual feedback and partial visual feedback have similar effects on touch duration and do not significantly shorten the touch duration.

[0153] In summary, for different touch tasks of three-dimensional object transformation, in the moving task, both partial visual feedback and full visual feedback significantly shortened the touch duration, and partial visual feedback can significantly reduce the error rate; in the rotation task, in the case of weak depth perception, the partial visual feedback has a lower error rate than full visual feedback, and in the case of partial visual feedback, the error rate of strong depth perception is lower than that of weak depth perception; in the scaling task, medium depth perception and full visual feedback significantly shortened the touch duration. Therefore, based on the above analysis results, it is preferred to use medium depth perception cues and partial visual feedback to widely adapt to different touch interaction scenarios.

[0154] In one embodiment, it also includes collecting the subject's eye movement data and total workload when completing each of the three-dimensional object operation tasks, and using the eye movement data and workload as evaluation dimensions to complete the optimization of the three-dimensional object touch interaction interface.

[0155] Specifically, Fig.13 As shown in FIG. 1 , a Tobii Pro X3-120 eye tracker is set on the Microsoft Surface Book2 laptop used in the experiment to collect the eye movement data of the subjects when they complete each of the three-dimensional object manipulation tasks. The purpose is to analyze the visual processing process of the subjects when they complete the touch task, and the following graphs are drawn accordingly: Fig.14The heat map and track map shown in the figure. The heat map is a graph that represents the density of gazes through color coding. In the heat map, the depth of the color is usually proportional to the length of the gaze time, that is, the longer the gaze time, the darker or "hotter" the color. It can intuitively reveal the distribution of the participants' visual attention. The track map shows the path and order of the participants' eye gazes when performing the task.

[0156] In summary, when performing the three tasks, the subjects' visual attention was focused on the cube. x In the figure, the attention of moving and scaling is distributed in an “I” shape, while that of rotation tends to be distributed in a “T” shape. x With cube ref And look at the key features of the cube to compare the cube x With cube ref This interaction strategy is particularly evident in the rotation task.

[0157] In addition, in order to evaluate the workload of the subjects when completing the touch task, a questionnaire survey was conducted using NASA-TLX. The subjects were asked to score the six dimensions of Mental Demands, Physical Demands, Temporal Demands, Own Performance, Effort, and Frustration (0 to 20 points), and then rank the six dimensions. The total workload score was then obtained through weighted calculation. The calculation formula is:

[0158]

[0159] Among them, total workload represents workload, Rating i is the score of the i-th dimension, Weight i is the weight of the i-th dimension. The weight value of each dimension can be set by the implementer according to the actual situation and is not specifically limited in this embodiment.

[0160] Fig.15 as well as Fig.16 The statistical results of the total touch time and total workload of each task are shown in Figure 2. The results show that the total touch time of the moving task is the shortest, followed by the rotation task, and finally the scaling task. Correspondingly, the average total workload of the moving task is the lowest, followed by the rotation task, and the average total workload of the scaling task is slightly higher than that of the rotation task.

[0161] From the above analysis of eye movement data and total workload, we can further know that: 2. When performing the moving and scaling tasks, visual attention is distributed in an "I" type, while the rotation task tends to be distributed in a "T" type. When performing different touch tasks, the strategy of scanning the target and reference and focusing on the key features of the target is used; 3. The total touch duration and total workload of the three touch tasks of moving, rotating, and scaling increase in sequence.

[0162] According to the above analysis results, the eye movement data and the workload can be used as evaluation dimensions to complete the optimization of the three-dimensional object touch interaction interface, so as to further improve the optimization effect.

[0163] Corresponding to the method of the above embodiment, Fig.17 The structural block diagram of the optimization device for the three-dimensional object touch interactive interface provided by the second embodiment of the present invention is shown. The above-mentioned optimization device is applied to a computer device, and the computer device is connected to the target database through a preset application program interface. When the target database is driven to execute a corresponding task, a corresponding task log will be generated, and the above-mentioned task log can be collected through the API. For the convenience of explanation, only the part related to the embodiment of the present invention is shown.

[0164] See also Fig.17 , the optimization device comprises:

[0165] The candidate interaction interface construction module 21 is used to set a preset number of interaction feedback levels for each interaction influencing factor, combine various interaction influencing factors with different interaction feedback levels, and construct the candidate interaction interface corresponding to each combination;

[0166] A touch interaction efficiency detection module 22, configured to execute each three-dimensional object operation task on all the to-be-selected interaction interfaces for a set number of times, and determine the touch duration and error rate for completing each three-dimensional object operation task on each of the to-be-selected interaction interfaces;

[0167] The touch interaction interface optimization module 23 is used to determine a candidate interaction interface that can improve the touch interaction effect of the three-dimensional object according to the touch duration and the error rate, and complete the optimization of the touch interaction interface of the three-dimensional object.

[0168] Optionally, the to-be-selected interactive interface construction module 21 includes:

[0169] The interactive influencing factor limiting unit is used to limit the interactive influencing factors to include depth perception clues and visual feedback forms.

[0170] Optionally, the interaction influencing factor limiting unit is further used to further limit the setting of a preset number of interaction feedback levels for each interaction influencing factor, including:

[0171] The interactive feedback levels of the depth perception cues include weak depth, medium depth and strong depth. The different interactive feedback levels of the depth perception cues are achieved by changing the ambient light and the material of the object. The interactive feedback levels in the form of visual feedback include no feedback, partial feedback and full feedback. No feedback means that the target three-dimensional object has no feedback when being controlled. The partial feedback means that the color of the target three-dimensional object changes to a preset color when it is controlled to reach the target state. The full feedback means that the color of the target three-dimensional object gradually changes to the preset color in the process of being controlled to reach the target state.

[0172] Optionally, the touch interaction efficiency detection module 22 includes:

[0173] A touch interaction efficiency detection unit is used to calculate the mean touch duration and the mean error rate of all subjects performing the current three-dimensional object operation task for the set number of times on the current interaction interface to be selected, after all subjects have performed the current three-dimensional object operation task on the current interaction interface to be selected for a set number of times; the mean touch duration is used as the touch duration for completing the current three-dimensional object operation task on the current interaction interface to be selected, and the mean error rate is used as the error rate for completing the current three-dimensional object operation task on the current interaction interface to be selected.

[0174] Optionally, the touch interaction interface optimization module 23 includes:

[0175] A variance analysis unit, used for performing a variance analysis on the touch duration and a two-factor repeated measures variance analysis on the error rate respectively, with the depth perception cue and the visual feedback form as variables;

[0176] A refinement analysis unit is used to, if in the variance analysis results about the touch duration or the variance analysis results about the error rate, conduct a simple effect test on the touch duration or the error rate corresponding to the significant interaction between the depth perception cues and the visual feedback form; if the interaction between the depth perception cues and the visual feedback form is not significant, conduct multiple comparisons on the touch duration or the error rate corresponding to the significant main effect of the interaction factors between the depth perception cues and the visual feedback form.

[0177] Optionally, the touch interaction interface optimization module 23 further includes:

[0178] The candidate interaction interface selection unit is used to use the candidate interaction interface corresponding to the medium depth perception clue and the partial visual feedback form as the three-dimensional object touch interaction interface.

[0179] Optionally, the above device further comprises:

[0180] The evaluation dimension superposition module 24 is used to collect the eye movement data and total workload of the subjects when completing each of the three-dimensional object operation tasks, and use the eye movement data and workload as additional evaluation dimensions to optimize the three-dimensional object touch interaction interface.

[0181] It should be noted that the information interaction, execution process and other contents between the above modules are based on the same concept as the embodiment of the method of the present invention. Their specific functions and technical effects can be found in the method embodiment part and will not be repeated here.

[0182] Fig.18 This is a schematic diagram of the structure of a computer device provided in Embodiment 3 of the present invention. Fig.18 As shown, the computer device of this embodiment includes: at least one processor ( Fig.18 Only one is shown), a memory, and a computer program stored in the memory and executable on at least one processor, wherein when the processor executes the computer program, the steps in any of the above-mentioned health prediction method embodiments are implemented.

[0183] The computer device may include, but is not limited to, a processor and a memory. Those skilled in the art will appreciate that Fig.17 This is merely an example of a computer device and does not constitute a limitation on the computer device. The computer device may include more or fewer components than shown in the figure, or a combination of certain components, or different components.

[0184] The processor may be a CPU, or other general-purpose processors, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0185] The memory includes a readable storage medium, an internal memory, etc., wherein the internal memory may be the memory of a computer device, and the internal memory provides an environment for the operation of an operating system and computer-readable instructions in the readable storage medium. The readable storage medium may be a hard disk of a computer device, and in other embodiments may also be an external storage device of a computer device, for example, a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. equipped on a computer device. Further, the memory may also include both an internal storage unit of a computer device and an external storage device. The memory is used to store an operating system, an application program, a boot loader (BootLoader), data, and other programs, such as program codes of computer programs, etc. The memory may also be used to temporarily store data that has been output or is to be output.

[0186] The technicians in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example. In practical applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the device is divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated into a processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of the present invention. The specific working process of the units and modules in the above-mentioned device can refer to the corresponding process in the above-mentioned method embodiment, which will not be repeated here. If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such understanding, the present invention implements all or part of the processes in the above-mentioned embodiment method, which can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a computer-readable storage medium. When the computer program is executed by the processor, the steps of the above-mentioned method embodiment can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may at least include: any entity or device capable of carrying computer program code, recording medium, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium. For example, a USB flash drive, a mobile hard disk, a magnetic disk or an optical disk. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electric carrier signals and telecommunication signals.

[0187] The present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by a computer program product. When the computer program product runs on a computer device, the computer device can implement the steps in the above-mentioned method embodiment when executing.

[0188] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0189] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0190] In the embodiments provided by the present invention, it should be understood that the disclosed devices / computer equipment and methods can be implemented in other ways. For example, the device / computer equipment embodiments described above are only schematic, for example, the division of modules or units is only a logical function division, and there may be other division methods in actual implementation, such as multiple units 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, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0191] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0192] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the protection scope of the present invention.

Claims

1. A method for optimizing a three-dimensional object touch interaction interface, characterized in that: The method comprises: Setting a preset number of interaction feedback levels for each interaction influencing factor, combining various interaction influencing factors with different interaction feedback levels, and constructing a candidate interaction interface corresponding to each combination; Execute each three-dimensional object operation task a set number of times on all the to-be-selected interactive interfaces, and determine the touch duration and error rate for completing each three-dimensional object operation task on each of the to-be-selected interactive interfaces; According to the touch duration and the error rate, a candidate interaction interface that can improve the three-dimensional object touch interaction effect is determined, and the optimization of the three-dimensional object touch interaction interface is completed.

2. The method for optimizing the three-dimensional object touch interaction interface according to claim 1, characterized in that: The interaction influencing factors include depth perception cues and visual feedback forms.

3. The method for optimizing the three-dimensional object touch interaction interface according to claim 2, characterized in that: The step of setting a preset number of interactive feedback levels for each interactive influencing factor includes: The interactive feedback levels of the depth perception cues include weak depth, medium depth and strong depth. The different interactive feedback levels of the depth perception cues are achieved by changing the ambient light and the material of the object. The interactive feedback levels in the form of visual feedback include no feedback, partial feedback and full feedback. No feedback means that the target three-dimensional object has no feedback when being controlled. The partial feedback means that the color of the target three-dimensional object changes to a preset color when it is controlled to reach the target state. The full feedback means that the color of the target three-dimensional object gradually changes to the preset color in the process of being controlled to reach the target state.

4. The method for optimizing the three-dimensional object touch interaction interface according to claim 1, characterized in that: The step of executing each three-dimensional object operation task a set number of times on all the to-be-selected interaction interfaces, and determining the touch duration and error rate for completing each three-dimensional object operation task on each of the to-be-selected interaction interfaces, includes: After all subjects have executed the current three-dimensional object operation task a set number of times on the current interaction interface to be selected, the mean touch duration and the mean error rate of all the subjects who executed the current three-dimensional object operation task the set number of times on the current interaction interface to be selected are calculated, and the mean touch duration is used as the touch duration for completing the current three-dimensional object operation task on the current interaction interface to be selected, and the mean error rate is used as the error rate for completing the current three-dimensional object operation task on the current interaction interface to be selected.

5. The method for optimizing the three-dimensional object touch interaction interface according to claim 2 or 3, characterized in that: The step of determining, according to the touch duration and the error rate, a candidate interaction interface that can improve the touch interaction effect of the three-dimensional object includes: Taking the depth perception cue and the visual feedback form as variables, respectively conducting an analysis of variance on the touch duration and a two-factor repeated measures analysis of variance on the error rate; In the variance analysis results of the touch duration or the variance analysis results of the error rate, if the interaction between the depth perception cues and the visual feedback form is significant, a simple effect test is performed on the touch duration or the error rate corresponding to the significant interaction between the depth perception cues and the visual feedback form; if the interaction between the depth perception cues and the visual feedback form is not significant, multiple comparisons are performed on the touch duration or the error rate corresponding to the significant main effect of the interactive influencing factors between the depth perception cues and the visual feedback form.

6. The method for optimizing the three-dimensional object touch interaction interface according to claim 5, characterized in that: A candidate interaction interface corresponding to medium depth perception clues and partial visual feedback form is adopted as the three-dimensional object touch interaction interface.

7. The method according to claim 1, characterized in that: Also includes: The eye movement data and total workload of the subjects when completing each of the three-dimensional object operation tasks are collected, and the eye movement data and workload are used as additional evaluation dimensions to complete the optimization of the three-dimensional object touch interaction interface.

8. An optimization device for a three-dimensional object touch interactive interface, characterized in that: The device comprises: A candidate interaction interface construction module is used to set a preset number of interaction feedback levels for each interaction influencing factor, combine various interaction influencing factors with different interaction feedback levels, and construct a candidate interaction interface corresponding to each combination; A touch interaction efficiency detection module, used to execute each three-dimensional object operation task on all the to-be-selected interaction interfaces for a set number of times, and determine the touch duration and error rate for completing each three-dimensional object operation task on each of the to-be-selected interaction interfaces; The touch interaction interface optimization module is used to determine a candidate interaction interface that can improve the touch interaction effect of the three-dimensional object according to the touch duration and the error rate, and complete the optimization of the touch interaction interface of the three-dimensional object.

9. A computer device, characterized in that: The computer device includes a processor, a memory, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the method for optimizing the touch interaction interface of a three-dimensional object as described in any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the method for optimizing the three-dimensional object touch interaction interface as described in any one of claims 1 to 7 is implemented.

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