Virtual Reality Translation Gain Threshold Expansion Method Based on Telescope-Style Field Angle Transform

Abstract

This invention discloses a virtual reality translation gain threshold expansion method based on telescope-style field-of-view transformation, relating to the VR field. This method employs an implicit modification of the expanded translation gain threshold using a "telescope" effect to process the user's virtual view. By reducing the FOV of the head-mounted display, it effectively expands the translation gain threshold while maintaining user immersion and comfort. During the dynamic adjustment of the key scaling factor K, a comfort constraint is established with the goal of suppressing motion sickness, used to update the gain threshold range. This ensures that motion sickness is suppressed while effectively expanding the translation gain, thereby providing users with a better gain and comfort experience.

Description

Technical Field

[0001] This invention relates to the field of VR technology, specifically to a virtual reality translation gain threshold expansion method based on telescopic field-of-view transformation. Background Technology

[0002] In virtual reality, subtle differences between visual input and body movement can redirect users to an adjusted path without their awareness, thus preventing collisions in physical space. This difference between virtual and real movement is called redirection gain. Translation gain adjusts the translation ratio of the user's virtual walking, making the user move faster or slower in the virtual environment.

[0003] However, there is a threshold limitation in perceived gain. When the gain exceeds this threshold range, users may perceive unnatural movement, which affects the immersion and comfort of the VR experience. Furthermore, the gain ratio can also have a certain impact on the occurrence of motion sickness. In order to balance user experience and the occurrence of motion sickness, a virtual reality translation gain threshold expansion method based on telescope-style field of view transformation is provided. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a virtual reality translation gain threshold expansion method based on telescopic field-of-view transformation. This method solves the problem that in existing virtual reality, there is a threshold limitation on perceived gain. When the gain exceeds this threshold range, users may perceive unnatural movement, thus affecting the immersion and comfort of the VR experience. Furthermore, the gain ratio can also have a certain impact on the occurrence of motion sickness in users.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a virtual reality translation gain threshold expansion method based on telescope-style field-of-view transformation, comprising the following steps:

[0006] S1. System initialization, including:

[0007] Hardware parameter configuration: Set the default horizontal field of view of the headset. Obtain the basic translation gain threshold. Set the maximum permissible motion sickness threshold. ;

[0008] Model parameter calibration: gain threshold expansion coefficient Gain threshold offset Motion sickness sensitivity coefficient Baseline motion sickness value ;

[0009] S2. Determine the target gain range by inputting the virtual environment layout parameters and then calculating the required gain range using the following formula:

[0010]

[0011] in Indicates physical space dimensions. Indicates the size of the virtual space. For safety factor;

[0012] S3. Calculate the FOV scaling factor, which includes:

[0013] S31. Gain range mapping is solved by using a logarithmic extension model to obtain the scaling factor K, and the formula is as follows:

[0014]

[0015] in This represents the minimum gain under the current scaling factor K, while That is, the variable to be solved;

[0016] This represents the maximum gain under the current scaling factor K, while That is, the variable to be solved;

[0017] S32. Comfort constraint verification: To suppress motion sickness, it is necessary to limit the degree of FOV reduction. The SSQ increment is used as a constraint, and its formula is as follows;

[0018]

[0019] S4. Apply FOV transformation to calculate the field of view and render the view simultaneously;

[0020] S5, Motion Mapping, acquires the user's actual displacement in real time. Then select a gain value within the threshold range. Its functional expression is:

[0021]

[0022] Then based on the gain value The formula for calculating virtual displacement is as follows:

[0023] ;

[0024] Preferably, in S1, when configuring hardware parameters and calibrating model parameters, it is also necessary to further establish a user profile database, acquire model data on users' age, VR experience and history of motion sickness, and then provide better gain threshold expansion and optimization schemes for different types of users based on the database.

[0025] Preferably, in S31, after solving for the scaling factor K for the gain range mapping, the value of K is sought by solving an optimization problem, and the formula is as follows;

[0026]

[0027] in Represents the target minimum gain. This represents the target maximum gain.

[0028] The optimization problem needs to satisfy two objectives simultaneously;

[0029] Lower boundary approaching:

[0030] This indicates that when the virtual space is much larger than the physical space, control is required. At this point, the displacement is extended;

[0031] The upper limit is approaching:

[0032] This indicates that when the virtual space is much smaller than the physical space, control is required. At this point, the compression displacement occurs.

[0033] Preferably, the steps for solving the optimization problem include:

[0034] S311. Establish a dual-objective optimization function

[0035] Now, let's define the bi-objective loss function, and its formula is:

[0036]

[0037] in Indicates the lower limit loss;

[0038] in Indicates the upper limit of loss;

[0039] S312. Analyze the characteristics of the function, including:

[0040] Monotonicity Analysis

[0041] ,therefore It is a decreasing function of K.

[0042] ,therefore It is an increasing function of K;

[0043] curvature characteristics

[0044]

[0045] Therefore, it can be determined that the loss function is a convex function and has a unique minimum value;

[0046] S313, Finding Extreme Points by Differentiation

[0047] Let the derivative be zero, since This indicates that the optimal solution appears in the region where the upper and lower bound errors have the same sign, and in this case, a piecewise solution should be performed.

[0048] Preferably, when solving in segments, three cases are considered based on the relative position of the target gain;

[0049] Scenario 1: The target range completely covers the base range. In this case, the optimal solution is... At this point, the default FOV is maintained;

[0050] Case 2: The target range shifts to the left. In this case, space needs to be compressed, and the equation to be solved is:

[0051]

[0052] Case 3: The target range shifts to the right, requiring an expansion of the space. The equation to be solved in this case is:

[0053] .

[0054] Preferably, in S32, if

[0055]

[0056] but:

[0057]

[0058] This ensures that the current scaling factor K is within the allowable motion sickness threshold range.

[0059] Preferably, in S4, a scaling factor is introduced. The transformed FOV can be expressed as:

[0060]

[0061] The view rendering process includes:

[0062] S41. Capture the original view. ;

[0063] S42. Extract the central area, horizontal angle vertical angle ;

[0064] S43. Calculate the magnification by subtracting the angle of the central region of the original view. Stretch to full screen to generate a "telescope" effect; the relationship between visual magnification M and K is as follows:

[0065] ,

[0066] In actual rendering, this is achieved by adjusting the projection matrix or scaling the central area using the rendering texture.

[0067] Preferably, the user profile database predicts individual perception thresholds based on historical data, giving users a higher sense of immersion; it quickly initializes similar user profiles to improve user adaptability; and it dynamically constrains the K value according to the sensitivity model to give users a higher level of comfort.

[0068] Preferably, the user profile database construction process includes:

[0069] S11, Data Acquisition;

[0070] S12, Feature extraction;

[0071] S13, Cluster analysis;

[0072] S14, Model Training;

[0073] S15, Real-time updates.

[0074] Its beneficial effects are as follows:

[0075] 1. This virtual reality translation gain threshold expansion method based on telescope-style field of view transformation adopts an implicit modification of the expanded translation gain threshold. It uses a "telescope" effect to process the user's virtual view. By reducing the FOV of the head-mounted display, it effectively expands the translation gain threshold while maintaining the user's immersion and comfort.

[0076] 2. This virtual reality translation gain threshold expansion method based on telescope-style field-of-view transformation sets comfort constraints with the goal of suppressing motion sickness during the dynamic adjustment of the key scaling factor K value. This ensures that motion sickness is suppressed while effectively expanding the translation gain, thereby bringing users a better sense of immersion and extending the user's immersion time.

[0077] 3. This virtual reality translation gain threshold expansion method based on telescope-style field-of-view transformation establishes a user profile database to acquire model data on users' age, VR experience, and history of motion sickness. Based on historical data, it predicts individual perception thresholds to provide users with a higher sense of immersion. It quickly initializes the data through similar user profiles to improve user adaptability. It dynamically constrains the K value according to the sensitivity model to provide users with a higher level of comfort. In this way, it can quickly adjust the initial gain threshold range for different types of users and provide different gain schemes for different users. Attached Figure Description

[0078] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0079] Figure 1 This is a flowchart of the virtual reality translation gain threshold expansion method based on telescope-type field of view transformation according to the present invention;

[0080] Figure 2 Flowchart for constructing the user profile database of this invention Detailed Implementation

[0081] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention are described clearly and completely. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0082] To better understand the above technical solutions, the following will provide a detailed explanation of the technical solutions in conjunction with the accompanying drawings and specific implementation methods.

[0083] This invention discloses a virtual reality translation gain threshold expansion method based on telescope-type field-of-view transformation, according to the appendix. Figure 1-2 As shown, it includes the following steps:

[0084] S1. System initialization, including:

[0085] Hardware parameter configuration: Set the default horizontal field of view of the headset. Obtain the basic translation gain threshold. Set the maximum permissible motion sickness threshold. ;

[0086] Model parameter calibration: gain threshold expansion coefficient Gain threshold offset Motion sickness sensitivity coefficient Baseline motion sickness value ;

[0087] S2. Determine the target gain range by inputting the virtual environment layout parameters and then calculating the required gain range using the following formula:

[0088]

[0089] in Indicates physical space dimensions. Indicates the size of the virtual space. For safety factor;

[0090] S3. Calculate the FOV scaling factor, which includes:

[0091] S31. Gain range mapping is solved by using a logarithmic extension model to find the scaling factor K, and the formula is as follows:

[0092]

[0093] in This represents the minimum gain under the current scaling factor K, while That is, the variable to be solved;

[0094] This represents the maximum gain under the current scaling factor K, while That is, the variable to be solved;

[0095] S32. Comfort constraint verification: To suppress motion sickness, it is necessary to limit the degree of FOV reduction. The SSQ increment is used as a constraint, and its formula is as follows;

[0096]

[0097] S4. Apply FOV transformation to calculate the field of view and render the view simultaneously;

[0098] S5, Motion Mapping, acquires the user's actual displacement in real time. Then select a gain value within the threshold range. Its functional expression is;

[0099]

[0100] Then based on the gain value The formula for calculating virtual displacement is as follows:

[0101] ;

[0102] In S1, after configuring hardware parameters and calibrating model parameters, it is also necessary to further establish a user profile database to acquire model data on users' age, VR experience, and history of motion sickness, so as to provide better gain threshold expansion and optimization schemes for different types of users based on the database.

[0103] In S31, after solving for the scaling factor K for the gain range mapping, the value of K is sought by solving an optimization problem, and the formula is as follows;

[0104]

[0105] in Represents the target minimum gain. This represents the target maximum gain.

[0106] The optimization problem needs to satisfy two objectives simultaneously;

[0107] Lower boundary approaching:

[0108] This indicates that when the virtual space is much larger than the physical space, control is required. At this point, the displacement is extended;

[0109] The upper limit is approaching:

[0110] This indicates that when the virtual space is much smaller than the physical space, control is required. At this point, the compression displacement occurs.

[0111] The steps to solve an optimization problem include:

[0112] S311. Establish a dual-objective optimization function

[0113] Now, let's define the bi-objective loss function, and its formula is:

[0114]

[0115] in Indicates the lower limit loss;

[0116] in Indicates the upper limit of loss;

[0117] S312. Analyze the characteristics of the function, including:

[0118] Monotonicity Analysis

[0119] ,therefore It is a decreasing function of K.

[0120] ,therefore It is an increasing function of K;

[0121] curvature characteristics

[0122]

[0123] Therefore, it can be determined that the loss function is a convex function and has a unique minimum value;

[0124] S313, Finding Extreme Points by Differentiation

[0125] Let the derivative be zero, since This indicates that the optimal solution appears in the region where the upper and lower bound errors have the same sign, and in this case, a piecewise solution should be performed.

[0126] When solving in segments, there are three cases based on the relative position of the target gain;

[0127] Scenario 1: The target range completely covers the base range. In this case, the optimal solution is... At this point, the default FOV is maintained;

[0128] Case 2: The target range shifts to the left. In this case, space needs to be compressed, and the equation to be solved is:

[0129]

[0130] Case 3: The target range shifts to the right, requiring an expansion of the space. The equation to be solved in this case is:

[0131] .

[0132] In S32, if

[0133]

[0134] but:

[0135]

[0136] This ensures that the current scaling factor K is within the allowable motion sickness threshold range.

[0137] In S4, a scaling factor is introduced. The transformed FOV can be expressed as:

[0138]

[0139] The view rendering process includes:

[0140] S41. Capture the original view. ;

[0141] S42. Extract the central area, horizontal angle vertical angle ;

[0142] S43. Calculate the magnification by subtracting the angle of the central region of the original view. Stretch to full screen to generate a "telescope" effect; the relationship between visual magnification M and K is as follows:

[0143] ,

[0144] In actual rendering, this is achieved by adjusting the projection matrix or scaling the central area using the rendering texture.

[0145] The user profile database predicts individual perception thresholds based on historical data, giving users a greater sense of immersion. It quickly initializes similar user profiles to improve user adaptability and dynamically constrains the K value according to the sensitivity model to provide users with a more comfortable experience.

[0146] The user profile database construction process includes:

[0147] S11, Data Acquisition;

[0148] S12, Feature extraction;

[0149] S13, Cluster analysis;

[0150] S14, Model Training;

[0151] S15, Real-time updates.

[0152] Working principle: In this virtual reality translation gain threshold expansion method based on telescope-style field of view transformation, an implicit modification of the field of view to expand the translation gain threshold is adopted. The "telescope" effect is used to process the user's virtual view. By reducing the FOV of the head-mounted display, the translation gain threshold is effectively expanded while maintaining the user's immersion and comfort.

[0153] Meanwhile, during the dynamic adjustment of the key scaling factor K value, comfort constraints are set with the goal of suppressing motion sickness, so as to ensure that motion sickness is suppressed while effectively expanding the translation gain, thereby bringing users a better sense of immersion and extending the user's immersion time.

[0154] Furthermore, in this solution, a user profile database is established to acquire model data on users' age, VR experience, and history of motion sickness. Based on historical data, individual perception thresholds are predicted to provide users with a higher sense of immersion. Similar user profiles are used for rapid initialization to improve user adaptability. The K value is dynamically constrained according to the sensitivity model to provide users with a higher level of comfort. In this way, the initial gain threshold range can be quickly adjusted for different types of users, providing different gain solutions for different users.

[0155] Example 2, see attached document Figure 1-2 Based on Example 1, this example will use specific simulation parameters to verify the feasibility of this solution;

[0156] I. Scene Description

[0157] Simulate a 10m×10m virtual exhibition hall in a 2m×2m physical space, with a required gain range of [0.4, 1.8].

[0158] II. Execution Process

[0159] 1. Initialization

[0160] make , , , , , ;

[0161] 2. Calculate the target K value

[0162]

[0163]

[0164]

[0165] 3. Comfort Verification

[0166]

[0167] It can be obtained through iterative calculation. hour,

[0168]

[0169] 4. Final parameters

[0170]

[0171] At this point, the gain range is...

[0172]

[0173] The gain range satisfies [0.4, 1.8];

[0174] At this point, the visual magnification is...

[0175]

[0176] The calculation results indicate that the dynamic gain range is reasonable, the visual magnification is acceptable, and the SSQ increment in the severe comfort level does not exceed the threshold, thus meeting the comfort and reasonableness requirements. Furthermore, during the subsequent dynamic adjustment process, as the SSQ increases, the gain range remains within the target gain range.

[0177] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0178] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of this invention is defined by the appended claims and their equivalents.

Claims

1. A virtual reality translation gain threshold expansion method based on telescope-style field-of-view transformation, characterized in that, Includes the following steps: S1. System initialization, including: Hardware parameter configuration: Set the default horizontal field of view of the headset. Obtain the basic translation gain threshold. Set the maximum permissible motion sickness threshold. ; Model parameter calibration: gain threshold expansion coefficient Gain threshold offset Motion sickness sensitivity coefficient Baseline motion sickness value ; S2. Determine the target gain range by inputting the virtual environment layout parameters and then calculating the required gain range using the following formula: in Indicates physical space dimensions. Indicates the size of the virtual space. For safety factor; S3. Calculate the FOV scaling factor, which includes: S31. Gain range mapping is solved by using a logarithmic extension model to find the scaling factor K, and the formula is as follows: in This represents the minimum gain under the current scaling factor K, while That is, the variable to be solved; This represents the maximum gain under the current scaling factor K, while That is, the variable to be solved; In S31, after solving for the scaling factor K for the gain range mapping, the value of K is sought by solving an optimization problem, and the formula is as follows; in Indicates the target minimum gain. Indicates the target maximum gain; The optimization problem needs to satisfy two objectives simultaneously; Lower boundary approaching: This indicates that when the virtual space is much larger than the physical space, control is required. At this point, the displacement is extended; The upper limit is approaching: This indicates that when the virtual space is much smaller than the physical space, control is required. At this point, the compression displacement occurs; S32. Comfort constraint verification: To suppress motion sickness, it is necessary to limit the degree of FOV reduction. The SSQ increment is used as a constraint, and its formula is as follows; S4. Apply FOV transformation to calculate the field of view and render the view simultaneously; S5, Motion Mapping, acquires the user's actual displacement in real time. Then select a gain value within the threshold range. Its functional expression is; Then based on the gain value The formula for calculating virtual displacement is as follows: 。 2. The virtual reality translation gain threshold expansion method based on telescope-type field-of-view transformation according to claim 1, characterized in that, In S1, after configuring hardware parameters and calibrating model parameters, it is also necessary to further establish a user profile database to acquire model data on users' age, VR experience, and history of motion sickness, so as to provide better gain threshold expansion and optimization schemes for different types of users based on the database.

3. The virtual reality translation gain threshold expansion method based on telescope-type field-of-view transformation according to claim 1, characterized in that, The steps to solve an optimization problem include: S311. Establish a dual-objective optimization function Now, let's define the bi-objective loss function, and its formula is: in Indicates the lower limit loss; in Indicates the upper limit of loss; S312. Analyze the characteristics of the function, including: Monotonicity Analysis ,therefore It is a decreasing function of K. ,therefore It is an increasing function of K; curvature characteristics Therefore, it can be determined that the loss function is a convex function and has a unique minimum value; S313, Finding Extreme Points by Differentiation Let the derivative be zero, since This indicates that the optimal solution appears in the region where the upper and lower bound errors have the same sign, and in this case, a piecewise solution should be performed.

4. The virtual reality translation gain threshold expansion method based on telescope-type field-of-view transformation according to claim 3, characterized in that, When solving in segments, there are three cases based on the relative position of the target gain; Scenario 1: The target range completely covers the base range. In this case, the optimal solution is... At this point, the default FOV is maintained; Case 2: The target range shifts to the left. In this case, space needs to be compressed, and the equation to be solved is: Case 3: The target range shifts to the right, requiring an expansion of the space. The equation to be solved in this case is: 。 5. The virtual reality translation gain threshold expansion method based on telescope-type field-of-view transformation according to claim 1, characterized in that, In S32, if but: This ensures that the current scaling factor K's scaling range is within the allowable motion sickness threshold range.

6. The virtual reality translation gain threshold expansion method based on telescope-type field-of-view transformation according to claim 1, characterized in that, In S4, a scaling factor is introduced. The transformed FOV can be expressed as: The view rendering process includes: S41. Capture the original view. ; S42. Extract the central area, horizontal angle vertical angle ; S43. Calculate the magnification by subtracting the angle of the central region of the original view. Stretch to full screen to generate a "telescope" effect; the relationship between visual magnification M and K is as follows: ， In actual rendering, this is achieved by adjusting the projection matrix or scaling the central area using the rendering texture.

7. The virtual reality translation gain threshold expansion method based on telescope-type field-of-view transformation according to claim 2, characterized in that, The user profile database predicts individual perception thresholds based on historical data, giving users a greater sense of immersion. It quickly initializes similar user profiles to improve user adaptability and dynamically constrains the K value according to the sensitivity model to provide users with a more comfortable experience.

8. The virtual reality translation gain threshold expansion method based on telescope-type field-of-view transformation according to claim 7, characterized in that, The user profile database construction process includes: S11, Data Acquisition; S12, Feature Extraction; S13, Cluster analysis; S14, Model Training; S15, Real-time updates.

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