Evaluation method and device for simulating HUD binocular parallax based on AR equipment

Abstract

The invention provides an evaluation method and device for simulating HUD binocular parallax based on AR equipment, and the method comprises the steps: determining an initial parallax distance of a binocular image center point on a screen focal plane of the AR equipment according to an interpupillary distance and the initial imaging distance of HUD and AR under the condition that the AR equipment is worn and simulated eyes are projected to a target focal plane; according to the initial parallax distance and the monocular screen width and height pixel number of the AR equipment, determining the calibration position of the center point of the binocular image; obtaining a target binocular distortion image sequence after the calibration position is aligned; and the binocular parallax of the to-be-tested HUD is evaluated by sequentially delivering each binocular distortion image in the target binocular distortion image sequence to the left screen and the right screen of the AR equipment. According to the method, the left screen and the right screen of the AR equipment are used for transmitting different images, so that the binocular parallax effect is generated, the HUD is endowed with the space depth sense, and compared with a testing method using a testing rack and a testing vehicle, the method has the advantages of being low in testing cost, flexible, convenient, high in controllability, good in universality and the like.

Description

Technical Field

[0001] The present application relates to the field of vehicle technology, and more specifically, to an evaluation method and device for simulating HUD binocular parallax based on an AR device. Background Art

[0002] HUD (Head Up Display) refers to a driver-centric, blind-operated, multi-functional instrument panel. Its function is to project important driving information such as speed and navigation onto the windshield in front of the driver, so that the driver can see important driving information such as speed and navigation without lowering or turning his head.

[0003] Before the HUD is put into production, the binocular parallax performance of the HUD needs to be evaluated. The current mainstream evaluation method is to use test benches and test vehicles for subjective evaluation. However, this evaluation method has problems such as high cost of test benches and test vehicles, difficulty in reproducing problematic working conditions, and low test efficiency. Summary of the invention

[0004] The present application provides an evaluation method and device based on AR equipment simulating HUD binocular parallax, which can solve the problems of using test benches and test vehicles for subjective evaluation, such as high cost of test benches and test vehicles, difficulty in reproducing problematic working conditions, and low testing efficiency.

[0005] The specific technical solutions are as follows:

[0006] In a first aspect, an embodiment of the present application provides an evaluation method based on an AR device simulating HUD binocular parallax, the method comprising:

[0007] When the tester wears an augmented reality (AR) device and simulates the human eye's gaze projected onto the target focal plane, the initial parallax distance of the center points of the binocular images on the focal plane of the AR device screen is determined according to the tester's pupil distance, the initial imaging distance of the head-up display (HUD) to be tested, and the initial imaging distance of the AR device, wherein the imaging distance from the human eye to the target focal plane is the initial imaging distance of the HUD to be tested;

[0008] Determine a calibration position of a binocular image center point on a focal plane of the AR device screen according to the initial parallax distance, the number of pixels of a monocular screen width of the AR device, and the number of pixels of a monocular screen height of the AR device;

[0009] A target binocular distorted image sequence after aligning the calibration position is obtained, and each binocular distorted image in the target binocular distorted image sequence is sequentially projected to the left and right screens of the AR device to achieve binocular parallax evaluation of the HUD to be tested.

[0010] In a possible implementation, determining the initial parallax distance of the center points of the binocular images on the focal plane of the AR device screen according to the pupil distance of the tester, the initial imaging distance of the head-up display HUD to be tested, and the initial imaging distance of the AR device includes:

[0011] Calculating a first equivalent angle of the HUD to be tested according to the pupil distance and the initial imaging distance of the HUD to be tested, and calculating a second equivalent angle of the AR device according to the pupil distance and the initial imaging distance of the AR device;

[0012] Calculating the binocular point equivalent angle when a person's eyes are projected onto the target focal plane according to the first equivalent angle and the second equivalent angle;

[0013] The initial parallax distance of the binocular image center point on the focal plane of the AR device screen is calculated according to the binocular point equivalent angle.

[0014] In a possible implementation, the first equivalent angle is the angle between the first line segment and the second line segment when no image data is input, the first line segment is a line segment passing through the midpoint of the center points of the binocular images on the target focal plane and the center point of the left pupil, and the second line segment is a line segment passing through the midpoint of the center points of the binocular images on the target focal plane and the center point of the right pupil; and / or,

[0015] The second equivalent angle is the angle between the third line segment and the fourth line segment, the third line segment is a line segment passing through the midpoint of the calibrated position of the binocular image center point and the center point of the left eye pupil, and the fourth line segment is a line segment passing through the midpoint of the calibrated position of the binocular image center point and the center point of the right eye pupil; and / or,

[0016] The binocular point equivalent angle is the angle between the fifth line segment and the sixth line segment, the fifth line segment is a line segment passing through the midpoint of the left and right pupil center points and the left eye calibration position, and the sixth line segment is a line segment passing through the midpoint of the left and right pupil center points and the right eye calibration position.

[0017] In a possible implementation manner, obtaining a target binocular distorted image sequence aligned with the calibrated position includes:

[0018] When the simulated distortion mode is started, the center point of the binocular standard image is aligned to the calibration position, and multiple parallax distance changes caused by the distortion are calculated according to the distortion data. The position of the center point of each first binocular distorted image is determined according to the initial parallax distance, each of the parallax distance changes, the number of pixels of the monocular screen width of the AR device, and the number of pixels of the monocular screen height of the AR device. According to the binocular standard image after the calibration position is aligned and the positions of the center points of the multiple first binocular distorted images, a first binocular distorted image sequence including multiple first binocular distorted images is generated, and the first binocular distorted image sequence is determined as the target binocular distorted image sequence, wherein the binocular standard image is an image in which the left and right eye images are the same and are not distorted.

[0019] In a possible implementation, the distortion data includes a distortion angle, a distortion range, a transformation step, and a test duration.

[0020] In a possible implementation manner, obtaining a target binocular distorted image sequence aligned with the calibrated position includes:

[0021] When the fixed distortion mode is started, a pre-generated second binocular distorted image sequence with binocular parallax is obtained, and after each second binocular distorted image in the second binocular distorted image sequence is aligned to the calibration position, the second binocular distorted image sequence aligned to the calibration position is obtained, and the second binocular distorted image sequence aligned to the calibration position is determined as the target binocular distorted image sequence.

[0022] In a second aspect, another embodiment of the present application provides an evaluation device for simulating HUD binocular parallax based on an AR device, the device comprising:

[0023] A parallax distance determination unit is used to determine the initial parallax distance of the center points of the binocular images on the focal plane of the AR device screen according to the pupil distance of the tester, the initial imaging distance of the head-up display HUD to be tested and the initial imaging distance of the AR device, when the tester wears an augmented reality AR device and simulates the human eye's gaze projected onto the target focal plane, wherein the imaging distance from the human eye to the target focal plane is the initial imaging distance of the HUD to be tested;

[0024] A calibration unit, configured to determine a calibration position of a binocular image center point on a focal plane of the AR device screen according to the initial parallax distance, a number of pixels of a monocular screen width of the AR device, and a number of pixels of a monocular screen height of the AR device;

[0025] An acquisition unit, used for acquiring a target binocular distorted image sequence after aligning the calibration position;

[0026] The evaluation unit is used to evaluate the binocular parallax of the HUD to be tested by sequentially projecting each binocular distorted image in the target binocular distorted image sequence to the left and right screens of the AR device.

[0027] In a possible implementation manner, the parallax distance determining unit includes:

[0028] a first calculation module, configured to calculate a first equivalent angle of the HUD to be tested according to the pupil distance and the initial imaging distance of the HUD to be tested, and to calculate a second equivalent angle of the AR device according to the pupil distance and the initial imaging distance of the AR device;

[0029] A second calculation module, used for calculating the binocular point equivalent angle when the human eye is projected onto the target focal plane according to the first equivalent angle and the second equivalent angle;

[0030] The third calculation module is used to calculate the initial parallax distance of the binocular image center point on the focal plane of the AR device screen according to the binocular point equivalent angle.

[0031] In a possible implementation, the first equivalent angle is the angle between the first line segment and the second line segment when no image data is input, the first line segment is a line segment passing through the midpoint of the center points of the binocular images on the target focal plane and the center point of the left pupil, and the second line segment is a line segment passing through the midpoint of the center points of the binocular images on the target focal plane and the center point of the right pupil; and / or,

[0032] The second equivalent angle is the angle between the third line segment and the fourth line segment, the third line segment is a line segment passing through the midpoint of the calibrated position of the binocular image center point and the center point of the left eye pupil, and the fourth line segment is a line segment passing through the midpoint of the calibrated position of the binocular image center point and the center point of the right eye pupil; and / or,

[0033] The binocular point equivalent angle is the angle between the fifth line segment and the sixth line segment, the fifth line segment is a line segment passing through the midpoint of the left and right pupil center points and the left eye calibration position, and the sixth line segment is a line segment passing through the midpoint of the left and right pupil center points and the right eye calibration position.

[0034] In a possible implementation, the acquisition unit includes: a first acquisition module or a second acquisition module;

[0035] The first acquisition module is configured to align the center point of the binocular standard image to the calibration position when the simulated distortion mode is started, calculate multiple parallax distance changes caused by the distortion according to the distortion data, determine the position of the center point of each first binocular distorted image according to the initial parallax distance, each of the parallax distance changes, the number of pixels of the width of a single eye screen of the AR device, and the number of pixels of the height of a single eye screen of the AR device, generate a first binocular distorted image sequence including multiple first binocular distorted images according to the binocular standard image after aligning the calibration position and the positions of the center points of the multiple first binocular distorted images, and determine the first binocular distorted image sequence as the target binocular distorted image sequence, wherein the binocular standard image is an image in which the left and right eye images are the same and are not distorted;

[0036] The second acquisition module is used to acquire a pre-generated second binocular distorted image sequence with binocular parallax when the fixed distortion mode is started, and align each second binocular distorted image in the second binocular distorted image sequence with the calibration position to obtain the second binocular distorted image sequence aligned with the calibration position, and determine the second binocular distorted image sequence aligned with the calibration position as the target binocular distorted image sequence.

[0037] In a possible implementation, the distortion data includes a distortion angle, a distortion range, a transformation step, and a test duration.

[0038] In a third aspect, another embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon, wherein the program, when executed by a processor, implements the method described in any embodiment of the first aspect.

[0039] In a fourth aspect, another embodiment of the present application provides an electronic device, the electronic device comprising:

[0040] one or more processors;

[0041] a storage device for storing one or more programs,

[0042] When the one or more programs are executed by the one or more processors, the one or more processors implement the method as described in any embodiment of the first aspect.

[0043] In a fifth aspect, an embodiment of the present application provides a computer program product, which includes instructions. When the instructions are executed on a computer or a processor, the computer or the processor executes the method described in any possible implementation of the first aspect.

[0044] From the above content, it can be seen that the evaluation method and device for simulating HUD binocular parallax based on AR device provided in the embodiment of the present application can be used when the tester wears AR (Augmented Reality) device and simulates the human eye gaze projected to the target focal plane (the imaging distance of the target focal plane is the initial imaging distance of the HUD to be tested). First, according to the pupil distance of the tester, the initial imaging distance of the HUD to be tested and the initial imaging distance of the AR device, the initial parallax distance of the binocular image center point on the focal plane of the AR device screen is determined, and then according to the initial parallax distance, the number of pixels of the width of the monocular screen of the AR device and the number of pixels of the height of the monocular screen of the AR device, the calibration position of the binocular image center point on the focal plane of the AR device screen is determined, and then the target binocular distorted image sequence after aligning the calibration position can be obtained, and each target binocular distorted image in the target binocular distorted image sequence is sequentially projected to the left and right screens of the AR device to achieve the binocular parallax evaluation of the HUD to be tested. It can be seen from this that the embodiment of the present application can use the left and right screens of the AR device to project different images, thereby producing a binocular parallax effect and giving the HUD a sense of spatial depth. In order to obtain accurate and reliable test results, eliminate the influence of the test subject and test equipment on the evaluation results, and quantify the correlation between binocular parallax and the subjective perception of the human eye, compared with the binocular parallax test method using a test bench and a test vehicle, the embodiment of the present application has the advantages of low testing cost, flexibility and convenience, strong controllability, and good versatility.

[0045] In addition, the embodiment of the present application can also obtain the target binocular distorted image sequence after alignment and calibration by two methods:

[0046] One method includes: first aligning the center point of a binocular standard image to a calibration position, then generating a first binocular distorted image sequence with different binocular image center points according to distortion data and the binocular standard image, and determining the first binocular distorted image sequence as a target binocular distorted image sequence; another method includes: directly acquiring a pre-generated second binocular distorted image sequence with binocular parallax, and aligning each second binocular distorted image in the second binocular distorted image sequence to the calibration position, so as to obtain a second binocular distorted image sequence aligned to the calibration position, and determining the second binocular distorted image sequence aligned to the calibration position as the target binocular distorted image sequence.

[0047] Among them, the first method automatically displays images with corresponding binocular parallax according to the distortion data configured by the user, which is convenient for testing the acceptable range and acceptance limit of binocular parallax for the human eye, and checking the human eye's acceptance of industry-specified standards. The second method is suitable for quickly simulating and displaying the effects of the optical design of HUD products, reducing R&D time and costs.

[0048] Of course, implementing any product or method of the present application does not necessarily require achieving all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings required for use in the embodiments or the prior art description are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For those of ordinary skill in the art, other drawings can also be obtained based on these drawings without creative work.

[0050] Figure 1 A flowchart of an evaluation method for simulating HUD binocular parallax based on an AR device provided in an embodiment of the present application;

[0051] Figure 2 A schematic diagram of an equivalent angle in an evaluation method for simulating HUD binocular parallax based on an AR device provided in an embodiment of the present application;

[0052] Figure 3 A schematic diagram of an initial disparity distance of a binocular image center point in an evaluation method for simulating HUD binocular disparity based on an AR device provided in an embodiment of the present application;

[0053] Figure 4 A schematic diagram of the equivalent focal plane imaging principle of an evaluation method for simulating HUD binocular parallax based on an AR device provided in an embodiment of the present application;

[0054] Figure 5 A schematic diagram of an evaluation method for simulating HUD binocular parallax based on an AR device in a simulated distortion mode provided in an embodiment of the present application;

[0055] Figure 6 A schematic diagram of an evaluation method for simulating HUD binocular parallax based on an AR device in a fixed distortion mode provided in an embodiment of the present application;

[0056] Figure 7 A block diagram of a device for evaluating an AR device simulating HUD binocular parallax according to an embodiment of the present application. DETAILED DESCRIPTION

[0057] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0058] It should be noted that the terms "including" and "having" and any variations thereof in the embodiments of the present application and the accompanying drawings are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device comprising a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units that are not listed, or may optionally include other steps or units that are inherent to these processes, methods, products or devices.

[0059] Figure 1 A flow chart of an evaluation method for simulating HUD binocular parallax based on an AR device provided in an embodiment of the present application is provided. The method can be applied to electronic devices. The method mainly includes:

[0060] S110: When the tester wears an augmented reality (AR) device and simulates the human eye's gaze projected onto a target focal plane, determine the initial parallax distance of the center points of the binocular images on the focal plane of the AR device screen according to the tester's pupil distance, the initial imaging distance of the head-up display (HUD) to be tested, and the initial imaging distance of the AR device.

[0061] Among them, the imaging distance from the human eye to the target focal plane is the initial imaging distance of the HUD to be tested.

[0062] Augmented reality technology is a technology that cleverly integrates virtual information with the real world. It widely uses multimedia, three-dimensional modeling, real-time tracking and registration, intelligent interaction, sensing and other technical means to simulate computer-generated text, images, three-dimensional models, music, videos and other virtual information, and apply them to the real world. The two types of information complement each other, thereby achieving "enhancement" of the real world. The AR device of the embodiment of the present application can be AR glasses, AR all-in-one machines, smart glasses and other devices that use the principle of projecting different images on the left and right screens to create binocular parallax effects, which are not specifically limited here. In order to eliminate the influence of the initial imaging distance of the AR device on the evaluation results, it is necessary to confirm the relevant optical indicators of the AR device and the HUD to be tested in advance. The optical indicators that can be directly obtained by the AR device include binocular resolution, single-eye screen width pixels, single-eye screen height pixels, diagonal field of view, initial imaging distance, display area screen aspect ratio, etc., among which at least the optical indicators that need to be obtained include single-eye screen width pixels, single-eye screen height pixels, and initial imaging distance. The optical indicators that can be directly obtained by the HUD to be tested include diagonal field of view, initial imaging distance, aspect ratio of the display area, etc. Among them, at least the optical indicators that need to be obtained include the initial imaging distance. For AR devices with the same optical indicators, their optical indicators usually only need to be confirmed once.

[0063] Since the difference in the human eye's depth perception of the HUD image is caused by the change in horizontal parallax, and the size of the parallax is also determined by the separation distance between the binocular observation points, in order to ensure the accuracy of the test results, it is necessary to obtain the tester's pupil distance before the test.

[0064] After confirming these basic optical indicators and the tester's pupil distance, the initial parallax distance of the binocular image center point on the focal plane of the AR device screen can be calculated based on the tester's pupil distance and these optical indicators. The specific implementation process includes steps A1-A3:

[0065] A1. Calculate the first equivalent angle of the HUD to be tested according to the pupil distance and the initial imaging distance of the HUD to be tested, and calculate the second equivalent angle of the AR device according to the pupil distance and the initial imaging distance of the AR device.

[0066] The first equivalent angle is the angle between the first line segment and the second line segment when no image data is input, the image data includes a binocular standard image and distortion data, or the image data includes a second binocular distorted image sequence, the first line segment is a line segment passing through the midpoint of the binocular image center point on the target focal plane and the center point of the left eye pupil, the second line segment is a line segment passing through the midpoint of the binocular image center point on the target focal plane and the center point of the right eye pupil; the second equivalent angle is the angle between the third line segment and the fourth line segment, the third line segment is a line segment passing through the midpoint of the calibrated position of the binocular image center point and the center point of the left eye pupil, the fourth line segment is a line segment passing through the midpoint of the calibrated position of the binocular image center point and the center point of the right eye pupil. Figure 2 The first equivalent angle is θ0, the second equivalent angle is θ1, the first line segment is O1P0, the second line segment is O2P0, the third line segment is O1P1, and the fourth line segment is O2P1.

[0067] Specifically, the first equivalent angle of the HUD to be tested may be calculated according to the first formula, and the second equivalent angle of the AR device may be calculated according to the second formula;

[0068] Among them, the first formula includes:

[0069]

[0070] The second formula includes:

[0071]

[0072] Among them, θ0 represents the first equivalent angle, PD represents the pupil distance, which is usually 64mm by default, and Z0 represents the initial imaging distance of the HUD to be tested. For details, please refer to Figure 2 , θ1 represents the second equivalent angle, Z1 represents the initial imaging distance of the AR device, for details, see Figure 2 .

[0073] A2. Calculate the binocular equivalent angle when the human eye is projected onto the target focal plane based on the first equivalent angle and the second equivalent angle.

[0074] The binocular equivalent angle is the angle between the fifth line segment and the sixth line segment. The fifth line segment is a line segment passing through the midpoint of the left and right pupil centers and the marked position of the left eye. The sixth line segment is a line segment passing through the midpoint of the left and right pupil centers and the marked position of the right eye. Figure 3 As shown, the equivalent angle between the binocular points is θ2, the fifth line segment is O3P2, and the sixth line segment is O3P3.

[0075] Figure 4 This is a schematic diagram of the equivalent focal plane imaging principle in the evaluation method based on AR device simulation HUD binocular parallax, see Figure 4 , to simulate the actual imaging distance of the HUD test product, the corresponding equivalent angle is the first equivalent angle θ0 mentioned above, and the parallax increment generated by the initial imaging distance of the AR device needs to be offset, and the corresponding equivalent angle is the second equivalent angle θ1 mentioned above, and the binocular eye point equivalent angle θ2 when projected to the target focal plane is calculated. Among them, Figure 4 The θ0 and θ1 in Figure 2 The θ0 and θ1 in are equivalent angles determined according to geometric relationships. Figure 4 The θ2 in Figure 3 Here, θ2 is also an equivalent angle determined by the geometric relationship.

[0076] Specifically, the equivalent angle of the binocular points when projected onto the target focal plane can be calculated according to the third formula;

[0077] Among them, the third formula includes:

[0078]

[0079] Wherein, θ2 represents the equivalent angle between the two eyes.

[0080] A3. Calculate the initial parallax distance of the binocular image center points on the focal plane of the AR device screen based on the binocular point equivalent angle.

[0081] like Figure 3 As shown, the initial parallax distance of the center points of the binocular images on the focal plane of the AR device screen refers to d in the figure, that is, the length of the line segment P2P3.

[0082] Specifically, the initial parallax distance of the center points of the binocular images on the focal plane of the AR device screen can be calculated according to the fourth formula;

[0083] Among them, the fourth formula includes:

[0084]

[0085] Wherein, d represents the initial parallax distance, and S' represents the average distance between two adjacent pixels on the AR device screen, and the unit can be mm / pixel.

[0086] S120: Determine a calibration position of a binocular image center point on a focal plane of the AR device screen according to an initial parallax distance, a number of pixels of a monocular screen width of the AR device, and a number of pixels of a monocular screen height of the AR device.

[0087] The working principle of AR devices is to simulate binocular parallax effect by projecting different images on the left and right screens. When testing HUD, the positions of the center points of the left and right eye images on the left and right screens are calibrated through the built-in program. The coordinate values ​​of the center points of the binocular images are used as the calibration positions after the initial parallax distance d calculated above is calculated to offset the imaging distance increment generated by the AR device. The calibration positions of the binocular image centers include the calibration positions of the left eye image center points and the calibration positions of the right eye image center points.

[0088] Specifically, the calibrated position of the center point of the binocular image on the focal plane of the AR device screen can be calculated according to the fifth formula, where the calibrated position of the center point of the binocular image includes the horizontal and vertical coordinate calibrated position of the center point of the left eye image and the horizontal and vertical coordinate calibrated position of the center point of the right eye image;

[0089] Among them, the fifth formula includes:

[0090]

[0091] Among them, x l and l They represent the horizontal and vertical calibration positions of the center point of the left eye image, respectively. r and r They represent the horizontal and vertical calibration positions of the center point of the right eye image, respectively. X represents the width of the single-eye screen of the AR device in pixels. Y represents the height of the single-eye screen of the AR device in pixels. d represents the initial parallax distance.

[0092] S130: Acquire a target binocular distorted image sequence after the alignment calibration position, and sequentially project each binocular distorted image in the target binocular distorted image sequence to the left and right screens of the AR device to implement binocular parallax evaluation of the HUD to be tested.

[0093] Among them, the specific implementation methods of obtaining the target binocular distorted image sequence after the alignment calibration position may include at least the following two methods:

[0094] First method:

[0095] When the simulated distortion mode is started, the center point of the binocular standard image is aligned to the calibration position, and multiple parallax distance changes caused by the distortion are calculated according to the distortion data. The position of the center point of each first binocular distorted image is determined according to the initial parallax distance, each parallax distance change, the number of pixels of the monocular screen width of the AR device, and the number of pixels of the monocular screen height of the AR device. According to the binocular standard image after the calibration position is aligned and the positions of the center points of the multiple first binocular distorted images, a first binocular distorted image sequence including multiple first binocular distorted images is generated, and the first binocular distorted image sequence is determined as the target binocular distorted image sequence.

[0096] The simulated distortion mode can be understood as a mode that uses distortion data to simulate binocular distortion images. The binocular standard image is an image in which the left and right eye images are identical and not distorted. The distortion data includes the distortion angle, the distortion range, the transformation step size, and the test duration.

[0097] like Figure 5 As shown, after the tester wears the AR device, the electronic device that executes the evaluation method of the present application can confirm the optical indicators of the AR device and the pupil distance of the tester by communicating with the AR device. The staff on the electronic device side (which may include the tester) can also input the optical indicators of the HUD to be tested in the electronic device. The electronic device calculates the initial parallax distance of the center point of the binocular image on the focal plane of the AR device screen and the calibrated position of the center point of the binocular image. The tester turns on the simulated distortion mode and inputs a binocular standard image to the AR device. The electronic device aligns the center point of the binocular standard image to the calibrated position. The tester inputs distortion data to the electronic device. The electronic device calculates multiple parallax distance changes based on the distortion data, and generates multiple positions of the center points of the first binocular distorted images based on the multiple parallax distance changes. Finally, a first binocular distorted image sequence is generated. According to the configured evaluation frequency, each first binocular distorted image is sequentially projected to the left and right screens of the AR device. The binocular parallax of the HUD to be tested is evaluated through the image effect observed by the tester on the AR device screen.

[0098] The unit of the parallax distance change is pixel value pixel, the parallax distance change may be a positive value or a negative value, and when the first binocular distorted image is generated according to the parallax distance change, the right eye standard image can be kept unchanged, and the center point coordinates of the left eye standard image can be continuously changed according to different parallax distance changes, or the left eye standard image can be kept unchanged, and the center point coordinates of the right eye standard image can be continuously changed according to different parallax distance changes. When the right eye standard image remains unchanged and the coordinates of the center point of the left eye standard image change continuously according to different parallax distance changes, the horizontal coordinate calibration position and the vertical coordinate calibration position of the center point of the left eye image in the fifth formula can be respectively superimposed by Δd, while the horizontal coordinate calibration position and the vertical coordinate calibration position of the center point of the right eye image remain unchanged, so as to obtain the position of the center point of the first binocular distorted image; when the left eye standard image remains unchanged and the coordinates of the center point of the right eye standard image change continuously according to different parallax distance changes, the horizontal coordinate calibration position and the vertical coordinate calibration position of the center point of the right eye image in the fifth formula can be respectively superimposed by Δd, while the horizontal coordinate calibration position and the vertical coordinate calibration position of the center point of the left eye image remain unchanged, so as to obtain the position of the center point of the first binocular distorted image. Wherein, Δd refers to the parallax distance change.

[0099] The electronic device of the embodiment of the present application automatically displays an image with corresponding binocular parallax according to the distortion data configured by the user, which is convenient for testing the acceptable range and acceptance limit of the binocular parallax of the human eye and verifying the human eye's acceptance of industry-specified standards.

[0100] Second method:

[0101] When the fixed distortion mode is started, a pre-generated second binocular distorted image sequence with binocular parallax is obtained, and each second binocular distorted image in the second binocular distorted image sequence is aligned to a calibration position to obtain a second binocular distorted image sequence aligned to the calibration position, and the second binocular distorted image sequence aligned to the calibration position is determined as a target binocular distorted image sequence.

[0102] After the HUD sample is produced, a binocular camera can be used to take pictures of environmental information through different positions of the HUD (for example, the HUD can be divided into multiple positions according to the nine-square grid) to obtain a second binocular distorted image sequence with binocular parallax. Of course, a second binocular distorted image sequence with real binocular parallax can also be produced in external simulation software. Therefore, the fixed distortion mode can be understood as a mode of directly generating binocular distorted images using a hardware device or software device that can generate distortion.

[0103] like Figure 6As shown, after the tester wears the AR device, the electronic device that executes the evaluation method of the present application can confirm the optical indicators of the AR device and the pupil distance of the tester by communicating with the AR device. The staff on the electronic device side (which may include the tester) can also input the optical indicators of the HUD to be tested in the electronic device. The electronic device calculates the initial parallax distance of the center points of the binocular images on the focal plane of the AR device screen and the calibrated position of the center points of the binocular images. The tester turns on the fixed distortion mode and inputs a second binocular distortion image sequence to the electronic device. The electronic device aligns each second binocular distortion image in the second binocular distortion image sequence with the calibrated position, and projects each second binocular distortion image to the left and right screens of the AR device in turn according to the configured evaluation frequency. The binocular parallax of the HUD to be tested is evaluated through the image effect observed by the tester on the AR device screen.

[0104] The embodiment of the present application can evaluate the binocular parallax actually generated by the HUD product. Due to the optical characteristics of the head-up display, the binocular parallax between different points of the left and right eye images being evaluated is inconsistent. Generally, the binocular parallax in the middle area is small, and the binocular parallax in the surrounding area is large. Therefore, it is necessary to use a binocular camera to shoot a group of left and right eye images on the actual head-up display product in advance, or to create left and right eye images with real binocular parallax in external simulation software. It is suitable for quickly simulating and displaying the effect of the optical design of the HUD product, reducing R&D time and cost.

[0105] In summary, different methods of obtaining the target binocular distortion image sequence correspond to different binocular parallax evaluation methods. After the calibration position of the binocular image center point on the focal plane of the AR device screen, if the HUD sample to be tested has not been produced, the first method can be used for evaluation, so as to adjust the parameter information in the production process of the HUD to be tested according to the evaluation results. If the HUD sample to be tested is produced, the second method can be used for evaluation, so as to determine whether the HUD to be tested needs to be further adjusted according to the evaluation.

[0106] It should be noted that the first binocular distorted image sequence and the second binocular distorted image sequence are binocular distorted image sequences generated by two methods, so the "first" and "second" here are only used to distinguish the names, and there is no order of precedence, and the first binocular distorted image sequence and the second binocular distorted image sequence can be collectively referred to as the "target binocular distorted image sequence". Similarly, in order to distinguish images in different sequences, the images in the first binocular distorted image sequence can be called the first binocular distorted image, and the images in the second binocular distorted image sequence can be called the second binocular distorted image, and there is no order of precedence between the first binocular distorted image and the second binocular distorted image.

[0107] The evaluation method based on the AR device simulating HUD binocular parallax provided in the embodiment of the present application can, when the tester wears an AR (Augmented Reality) device and simulates the human eye's gaze projected to the target focal plane (the imaging distance of the target focal plane is the initial imaging distance of the HUD to be tested), first determine the initial parallax distance of the binocular image center point on the AR device screen focal plane according to the tester's pupil distance, the initial imaging distance of the HUD to be tested and the initial imaging distance of the AR device, and then determine the calibration position of the binocular image center point on the AR device screen focal plane according to the initial parallax distance, the number of pixels of the monocular screen width of the AR device and the number of pixels of the monocular screen height of the AR device, and then obtain the target binocular distorted image sequence after aligning the calibration position, and by sequentially projecting each target binocular distorted image in the target binocular distorted image sequence to the left and right screens of the AR device, the binocular parallax of the HUD to be tested can be evaluated. It can be seen from this that the embodiment of the present application can use the left and right screens of the AR device to project different images, thereby generating a binocular parallax effect and giving the HUD a sense of spatial depth. In order to obtain accurate and reliable test results, eliminate the influence of the test subject and test equipment on the evaluation results, and quantify the correlation between binocular parallax and the subjective perception of the human eye, compared with the binocular parallax test method using test benches and test vehicles, it has the advantages of low testing cost, flexibility, convenience, strong controllability and good versatility.

[0108] In addition, the embodiment of the present application can also obtain the target binocular distorted image sequence after alignment and calibration by two methods:

[0109] One method includes: first aligning the center point of a binocular standard image to a calibration position, then generating a first binocular distorted image sequence with different binocular image center points according to distortion data and the binocular standard image, and determining the first binocular distorted image sequence as a target binocular distorted image sequence; another method includes: directly acquiring a pre-generated second binocular distorted image sequence with binocular parallax, and aligning each second binocular distorted image in the second binocular distorted image sequence to the calibration position, so as to obtain a second binocular distorted image sequence aligned to the calibration position, and determining the second binocular distorted image sequence aligned to the calibration position as the target binocular distorted image sequence.

[0110] Among them, the first method automatically displays images with corresponding binocular parallax according to the distortion data configured by the user, which is convenient for testing the acceptable range and acceptance limit of binocular parallax for the human eye, and checking the human eye's acceptance of industry-specified standards. The second method is suitable for quickly simulating and displaying the effects of the optical design of HUD products, reducing R&D time and costs.

[0111] Based on the above embodiments, the present application embodiment provides an evaluation device based on AR device simulating HUD binocular parallax, such as Figure 7 As shown, the device comprises:

[0112] The parallax distance determining unit 210 is used to determine the initial parallax distance of the center points of the binocular images on the focal plane of the AR device screen according to the pupil distance of the tester, the initial imaging distance of the head-up display HUD to be tested, and the initial imaging distance of the augmented reality AR device, when the tester wears the AR device and simulates the human eye's gaze projected onto the target focal plane, wherein the imaging distance from the human eye to the target focal plane is the initial imaging distance of the HUD to be tested;

[0113] A calibration unit 220 is used to determine a calibration position of a binocular image center point on a focal plane of the AR device screen according to the initial parallax distance, the number of pixels of a monocular screen width of the AR device, and the number of pixels of a monocular screen height of the AR device;

[0114] An acquisition unit 230 is used to acquire a target binocular distorted image sequence after aligning the calibration position;

[0115] The evaluation unit 240 is used to evaluate the binocular parallax of the HUD to be tested by sequentially projecting each binocular distorted image in the target binocular distorted image sequence to the left and right screens of the AR device.

[0116] In a possible implementation manner, the parallax distance determining unit 210 includes:

[0117] a first calculation module, configured to calculate a first equivalent angle of the HUD to be tested according to the pupil distance and the initial imaging distance of the HUD to be tested, and to calculate a second equivalent angle of the AR device according to the pupil distance and the initial imaging distance of the AR device;

[0118] A second calculation module, used for calculating the binocular point equivalent angle when the human eye is projected onto the target focal plane according to the first equivalent angle and the second equivalent angle;

[0119] The third calculation module is used to calculate the initial parallax distance of the binocular image center point on the focal plane of the AR device screen according to the binocular point equivalent angle.

[0120] In a possible implementation, the first equivalent angle is the angle between the first line segment and the second line segment when no image data is input, the first line segment is a line segment passing through the midpoint of the center points of the binocular images on the target focal plane and the center point of the left pupil, and the second line segment is a line segment passing through the midpoint of the center points of the binocular images on the target focal plane and the center point of the right pupil; and / or,

[0121] The second equivalent angle is the angle between the third line segment and the fourth line segment, the third line segment is a line segment passing through the midpoint of the calibrated position of the binocular image center point and the center point of the left eye pupil, and the fourth line segment is a line segment passing through the midpoint of the calibrated position of the binocular image center point and the center point of the right eye pupil; and / or,

[0122] The binocular point equivalent angle is the angle between the fifth line segment and the sixth line segment, the fifth line segment is a line segment passing through the midpoint of the left and right pupil center points and the left eye calibration position, and the sixth line segment is a line segment passing through the midpoint of the left and right pupil center points and the right eye calibration position.

[0123] In a possible implementation, the acquisition unit 230 includes: a first acquisition module or a second acquisition module;

[0124] The first acquisition module is configured to align the center point of the binocular standard image to the calibration position when the simulated distortion mode is started, calculate multiple parallax distance changes caused by the distortion according to the distortion data, determine the position of the center point of each first binocular distorted image according to the initial parallax distance, each of the parallax distance changes, the number of pixels of the width of a single eye screen of the AR device, and the number of pixels of the height of a single eye screen of the AR device, generate a first binocular distorted image sequence including multiple first binocular distorted images according to the binocular standard image after aligning the calibration position and the positions of the center points of the multiple first binocular distorted images, and determine the first binocular distorted image sequence as the target binocular distorted image sequence, wherein the binocular standard image is an image in which the left and right eye images are the same and are not distorted;

[0125] The second acquisition module is used to acquire a pre-generated second binocular distorted image sequence with binocular parallax when the fixed distortion mode is started, and align each second binocular distorted image in the second binocular distorted image sequence with the calibration position to obtain the second binocular distorted image sequence aligned with the calibration position, and determine the second binocular distorted image sequence aligned with the calibration position as the target binocular distorted image sequence.

[0126] In a possible implementation, the distortion data includes a distortion angle, a distortion range, a transformation step, and a test duration.

[0127] The evaluation device based on the AR device simulating HUD binocular parallax provided in the embodiment of the present application can, when the tester wears an AR (Augmented Reality) device and simulates the human eye's gaze projected to the target focal plane (the imaging distance of the target focal plane is the initial imaging distance of the HUD to be tested), first determine the initial parallax distance of the binocular image center point on the AR device screen focal plane according to the tester's pupil distance, the initial imaging distance of the HUD to be tested and the initial imaging distance of the AR device, and then determine the calibration position of the binocular image center point on the AR device screen focal plane according to the initial parallax distance, the number of pixels of the monocular screen width of the AR device and the number of pixels of the monocular screen height of the AR device, and then obtain the target binocular distorted image sequence after aligning the calibration position, and by sequentially projecting each target binocular distorted image in the target binocular distorted image sequence to the left and right screens of the AR device, the binocular parallax of the HUD to be tested can be evaluated. It can be seen from this that the embodiment of the present application can use the left and right screens of the AR device to project different images, thereby generating a binocular parallax effect and giving the HUD a sense of spatial depth. In order to obtain accurate and reliable test results, eliminate the influence of the test subject and test equipment on the evaluation results, and quantify the correlation between binocular parallax and the subjective perception of the human eye, compared with the binocular parallax test method using test benches and test vehicles, it has the advantages of low testing cost, flexibility, convenience, strong controllability and good versatility.

[0128] In addition, the embodiment of the present application can also obtain the target binocular distorted image sequence after alignment and calibration by two methods:

[0129] One method includes: first aligning the center point of a binocular standard image to a calibration position, then generating a first binocular distorted image sequence with different binocular image center points according to distortion data and the binocular standard image, and determining the first binocular distorted image sequence as a target binocular distorted image sequence; another method includes: directly acquiring a pre-generated second binocular distorted image sequence with binocular parallax, and aligning each second binocular distorted image in the second binocular distorted image sequence to the calibration position, so as to obtain a second binocular distorted image sequence aligned to the calibration position, and determining the second binocular distorted image sequence aligned to the calibration position as the target binocular distorted image sequence.

[0130] Among them, the first method automatically displays images with corresponding binocular parallax according to the distortion data configured by the user, which is convenient for testing the acceptable range and acceptance limit of binocular parallax for the human eye, and checking the human eye's acceptance of industry-specified standards. The second method is suitable for quickly simulating and displaying the effects of the optical design of HUD products, reducing R&D time and costs.

[0131] Based on the above method embodiments, another embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon, and when the program is executed by a processor, the method described in any of the above method embodiments is implemented.

[0132] Based on the above method embodiment, another embodiment of the present application provides an electronic device, the electronic device comprising:

[0133] one or more processors;

[0134] a storage device for storing one or more programs,

[0135] When the one or more programs are executed by the one or more processors, the one or more processors implement the method described in any of the above method embodiments.

[0136] Based on the above method embodiments, another embodiment of the present application provides a computer program product, which includes instructions. When the instructions are executed on a computer or a processor, the computer or the processor executes the method described in any of the above method embodiments.

[0137] The above virtual device embodiments and physical device embodiments correspond to the method embodiments and have the same technical effects as the method embodiments. For specific descriptions, please refer to the method embodiments. The device embodiments are obtained based on the method embodiments. For specific descriptions, please refer to the method embodiment section, which will not be repeated here. A person of ordinary skill in the art can understand that the accompanying drawings are only schematic diagrams of one embodiment, and the modules or processes in the accompanying drawings are not necessarily required to implement the present application.

[0138] Those skilled in the art can understand that the modules in the device in the embodiment can be distributed in the device in the embodiment according to the description of the embodiment, or can be changed accordingly and located in one or more devices different from the embodiment. The modules in the above embodiment can be combined into one module, or can be further divided into multiple sub-modules.

[0139] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these 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 application.

Claims

1. A method for evaluating HUD binocular parallax based on AR device simulation, characterized in that: The method comprises: When the tester wears an augmented reality (AR) device and simulates the human eye's gaze projected onto the target focal plane, the initial parallax distance of the center points of the binocular images on the focal plane of the AR device screen is determined according to the tester's pupil distance, the initial imaging distance of the head-up display (HUD) to be tested, and the initial imaging distance of the AR device, wherein the imaging distance from the human eye to the target focal plane is the initial imaging distance of the HUD to be tested; Determine a calibration position of a binocular image center point on a focal plane of the AR device screen according to the initial parallax distance, the number of pixels of a monocular screen width of the AR device, and the number of pixels of a monocular screen height of the AR device; A target binocular distorted image sequence after aligning the calibration position is obtained, and each binocular distorted image in the target binocular distorted image sequence is sequentially projected to the left and right screens of the AR device to achieve binocular parallax evaluation of the HUD to be tested.

2. The method according to claim 1, characterized in that According to the pupil distance of the tester, the initial imaging distance of the head-up display HUD to be tested and the initial imaging distance of the AR device, the initial parallax distance of the center point of the binocular image on the focal plane of the AR device screen is determined, including: Calculating a first equivalent angle of the HUD to be tested according to the pupil distance and the initial imaging distance of the HUD to be tested, and calculating a second equivalent angle of the AR device according to the pupil distance and the initial imaging distance of the AR device; Calculating the binocular point equivalent angle when a person's eyes are projected onto the target focal plane according to the first equivalent angle and the second equivalent angle; The initial parallax distance of the binocular image center point on the focal plane of the AR device screen is calculated according to the binocular point equivalent angle.

3. The method according to claim 2, characterized in that The first equivalent angle is the angle between the first line segment and the second line segment when no image data is input, the first line segment is a line segment passing through the midpoint of the center points of the binocular images on the target focal plane and the center point of the left pupil, and the second line segment is a line segment passing through the midpoint of the center points of the binocular images on the target focal plane and the center point of the right pupil; and / or, The second equivalent angle is the angle between the third line segment and the fourth line segment, the third line segment is a line segment passing through the midpoint of the calibrated position of the binocular image center point and the center point of the left eye pupil, and the fourth line segment is a line segment passing through the midpoint of the calibrated position of the binocular image center point and the center point of the right eye pupil; and / or, The binocular point equivalent angle is the angle between the fifth line segment and the sixth line segment, the fifth line segment is a line segment passing through the midpoint of the left and right pupil center points and the left eye calibration position, and the sixth line segment is a line segment passing through the midpoint of the left and right pupil center points and the right eye calibration position.

4. The method according to any one of claims 1 to 3, characterized in that Acquiring a target binocular distorted image sequence aligned with the calibrated position, comprising: When the simulated distortion mode is started, the center point of the binocular standard image is aligned to the calibration position, and multiple parallax distance changes caused by the distortion are calculated according to the distortion data. The position of the center point of each first binocular distorted image is determined according to the initial parallax distance, each of the parallax distance changes, the number of pixels of the monocular screen width of the AR device, and the number of pixels of the monocular screen height of the AR device. According to the binocular standard image after the calibration position is aligned and the positions of the center points of the multiple first binocular distorted images, a first binocular distorted image sequence including multiple first binocular distorted images is generated, and the first binocular distorted image sequence is determined as the target binocular distorted image sequence, wherein the binocular standard image is an image in which the left and right eye images are the same and are not distorted.

5. The method according to claim 4, characterized in that The distortion data includes distortion angle, distortion range, transformation step length and test duration.

6. The method according to any one of claims 1 to 3, characterized in that: Acquiring a target binocular distorted image sequence aligned with the calibrated position, comprising: When the fixed distortion mode is started, a pre-generated second binocular distorted image sequence with binocular parallax is obtained, and after each second binocular distorted image in the second binocular distorted image sequence is aligned to the calibration position, the second binocular distorted image sequence aligned to the calibration position is obtained, and the second binocular distorted image sequence aligned to the calibration position is determined as the target binocular distorted image sequence.

7. An evaluation device for simulating HUD binocular parallax based on AR equipment, characterized in that: The device comprises: A parallax distance determination unit is used to determine the initial parallax distance of the center points of the binocular images on the focal plane of the AR device screen according to the pupil distance of the tester, the initial imaging distance of the head-up display HUD to be tested and the initial imaging distance of the AR device, when the tester wears an augmented reality AR device and simulates the human eye's gaze projected onto the target focal plane, wherein the imaging distance from the human eye to the target focal plane is the initial imaging distance of the HUD to be tested; A calibration unit, configured to determine a calibration position of a binocular image center point on a focal plane of the AR device screen according to the initial parallax distance, a number of pixels of a monocular screen width of the AR device, and a number of pixels of a monocular screen height of the AR device; An acquisition unit, used for acquiring a target binocular distorted image sequence after aligning the calibration position; The evaluation unit is used to evaluate the binocular parallax of the HUD to be tested by sequentially projecting each binocular distorted image in the target binocular distorted image sequence to the left and right screens of the AR device.

8. The device according to claim 7, characterized in that The parallax distance determining unit comprises: a first calculation module, configured to calculate a first equivalent angle of the HUD to be tested according to the pupil distance and the initial imaging distance of the HUD to be tested, and to calculate a second equivalent angle of the AR device according to the pupil distance and the initial imaging distance of the AR device; A second calculation module, used for calculating the binocular point equivalent angle when the human eye is projected onto the target focal plane according to the first equivalent angle and the second equivalent angle; The third calculation module is used to calculate the initial parallax distance of the binocular image center point on the focal plane of the AR device screen according to the binocular point equivalent angle.

9. The device according to claim 7 or 8, characterized in that The acquisition unit includes: a first acquisition module or a second acquisition module; The first acquisition module is configured to align the center point of the binocular standard image to the calibration position when the simulated distortion mode is started, calculate multiple parallax distance changes caused by the distortion according to the distortion data, determine the position of the center point of each first binocular distorted image according to the initial parallax distance, each of the parallax distance changes, the number of pixels of the width of a single eye screen of the AR device, and the number of pixels of the height of a single eye screen of the AR device, generate a first binocular distorted image sequence including multiple first binocular distorted images according to the binocular standard image after aligning the calibration position and the positions of the center points of the multiple first binocular distorted images, and determine the first binocular distorted image sequence as the target binocular distorted image sequence, wherein the binocular standard image is an image in which the left and right eye images are the same and are not distorted; The second acquisition module is used to, when the fixed distortion mode is started and when the target binocular distorted image sequence includes a second binocular distorted sequence, acquire a pre-generated second binocular distorted image sequence with binocular parallax, align each second binocular distorted image in the second binocular distorted image sequence with the calibration position, obtain the second binocular distorted image sequence aligned with the calibration position, and determine the second binocular distorted image sequence aligned with the calibration position as the target binocular distorted image sequence.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

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