HUD dynamic distortion determination method, device, equipment, system and medium

Abstract

The embodiment of the invention discloses a method, a device, equipment and a system for determining dynamic distortion of an HUD (Head Up Display), and a medium. The method comprises the following steps: acquiring a lattice diagram corresponding to each eye point in an eye box; for each eye point and the lattice diagram corresponding to the eye point, determining a camera pixel deviation corresponding to the eye point according to a relative position coordinate of the eye point relative to a target eye point in the eye box, a reference position coordinate of the target eye point and a pixel number in the lattice diagram; for each pixel point in the lattice diagram, determining a first lattice coordinate corresponding to the pixel point based on the lattice coordinate of the pixel point and the camera pixel deviation corresponding to the corresponding eye point, the first lattice coordinate being a lattice coordinate after the deviation of the pixel point is eliminated; determining the dynamic distortion of the pixel point based on the first dot matrix coordinate and the dot matrix coordinate of the target pixel point in the dot matrix diagram; and the dynamic distortion of the corresponding eye spots of the lattice diagram is determined based on the dynamic distortion of each pixel point, so that accurate measurement of the dynamic distortion of the HUD is realized.

Description

Technical Field

[0001] The embodiments of the present disclosure relate to the field of image processing technology, and in particular to a method, device, equipment, system and medium for determining dynamic distortion of a HUD. Background Art

[0002] Head-up display is an optical display system that is projected into the driver's field of vision and affects driving safety, so the optical effect is crucial. Since the performance of dynamic distortion greatly affects the experience and is mainly subjective, an accurate value is needed to judge the dynamic distortion of HUD for optimization of dynamic distortion and test acceptance. In the past, HUD dynamic distortion mainly relied on subjective experience or manually moving the camera to shoot and measure, which was slow and inefficient. The next test would have to be repeated, with poor stability and no guaranteed accuracy. Summary of the invention

[0003] The embodiments of the present disclosure provide a method, device, equipment, system and medium for determining the dynamic distortion of a HUD, thereby achieving accurate measurement of the dynamic distortion of the HUD.

[0004] In a first aspect, a method for determining a dynamic distortion of a HUD is provided, the method comprising:

[0005] Obtain the dot map corresponding to each eye point in the eye box;

[0006] For each eye point and the dot map corresponding to the eye point, determine the camera pixel deviation corresponding to the eye point according to the relative position coordinates of the eye point relative to the target eye point in the eye box, the reference position coordinates of the target eye point, and the number of pixels in the dot map;

[0007] For each pixel in the dot map, determine a first dot matrix coordinate corresponding to the pixel based on the dot matrix coordinate of the pixel and the camera pixel deviation corresponding to the corresponding eye point, where the first dot matrix coordinate is the dot matrix coordinate of the pixel after the deviation is eliminated; determine the dynamic distortion of the pixel based on the first dot matrix coordinate and the dot matrix coordinate of the target pixel in the dot map;

[0008] The dynamic distortion of the eye point corresponding to the dot pattern is determined based on the dynamic distortion of each pixel point.

[0009] In a second aspect, a device for determining dynamic distortion of a HUD is provided, comprising:

[0010] A dot matrix acquisition module is used to acquire dot matrix images corresponding to each eye point in the eye box;

[0011] a camera pixel deviation determination module, for each eye point and the dot map corresponding to the eye point, determining the camera pixel deviation corresponding to the eye point according to the relative position coordinates of the eye point relative to the target eye point in the eye box, the reference position coordinates of the target eye point, and the number of pixels in the dot map;

[0012] A pixel point dynamic distortion determination module, for each pixel point in the dot map, determines a first dot matrix coordinate corresponding to the pixel point based on the dot matrix coordinate of the pixel point and the camera pixel deviation corresponding to the corresponding eye point, wherein the first dot matrix coordinate is the dot matrix coordinate of the pixel point after the deviation is eliminated; and determines the dynamic distortion of the pixel point based on the first dot matrix coordinate and the dot matrix coordinate of the target pixel point in the dot map;

[0013] The dynamic distortion determination module is used to determine the dynamic distortion of the eye point corresponding to the dot pattern based on the dynamic distortion of each pixel point.

[0014] In a third aspect, an electronic device is provided, including:

[0015] at least one processor; and

[0016] a memory communicatively connected to the at least one processor; wherein,

[0017] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the method for determining the dynamic distortion of the HUD as described in the first aspect above.

[0018] In a fourth aspect, a system for determining dynamic distortion of a HUD is provided, wherein the system comprises a multi-axis robotic arm, a binocular camera, a head-up display HUD test bench, and the electronic device as described in the third aspect above;

[0019] Wherein, the head-up display HUD test bench comprises: a windshield bracket, a head-up display HUD bracket and a head-up display HUD;

[0020] The windshield bracket is used to adjust the windshield angle so that the test chart can be projected onto the windshield;

[0021] The head-up display HUD bracket is used to adjust the head-up display HUD to a preset test gear position;

[0022] The windshield bracket and the head-up display (HUD) bracket are installed at preset positions, and the preset positions are determined based on driving data.

[0023] In a fifth aspect, a computer-readable storage medium is provided, on which a computer program is stored, and when the program is executed by a processor, the method for determining the dynamic distortion of the HUD as described in the first aspect above is implemented.

[0024] In a sixth aspect, a computer program product is provided, the computer program product comprising a computer program, and the computer program, when executed by a processor, implements the method for determining the dynamic distortion of the HUD as described in the first aspect above.

[0025] The embodiments of the present disclosure disclose a method, apparatus, device, system and medium for determining the dynamic distortion of a HUD, including: obtaining a dot matrix corresponding to each eye point in an eye box; for each eye point and the dot matrix corresponding to the eye point, determining the camera pixel deviation corresponding to the eye point according to the relative position coordinates of the eye point relative to the target eye point in the eye box, the reference position coordinates of the target eye point, and the number of pixels in the dot matrix; for each pixel point in the dot matrix, determining the first dot matrix coordinate corresponding to the pixel point based on the dot matrix coordinates of the pixel point and the camera pixel deviation corresponding to the corresponding eye point, the first dot matrix coordinate being the dot matrix coordinate after the deviation of the pixel point is eliminated; determining the dynamic distortion of the pixel point based on the first dot matrix coordinate and the dot matrix coordinates of the target pixel point in the dot matrix; and determining the dynamic distortion of the eye point corresponding to the dot matrix based on the dynamic distortion of each pixel point. This technical solution corrects each pixel in the dot map through the camera pixel deviation to obtain the first dot map coordinates, and determines the dynamic distortion of the pixel based on the dot map coordinates of the target pixel in the dot map and the first dot map coordinates, thereby achieving accurate measurement of the dynamic distortion of the HUD.

[0026] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present disclosure, nor is it intended to limit the scope of the embodiments of the present disclosure. Other features of the embodiments of the present disclosure will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the embodiments of the present disclosure. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0028] Figure 1 is a flow chart of a method for determining dynamic distortion of a HUD provided in Embodiment 1 of the present disclosure;

[0029] Figure 2 This is a schematic diagram of eye point dynamic distortion provided by the first embodiment of the present disclosure;

[0030] Figure 3 is a schematic diagram of a dot matrix provided in Embodiment 1 of the present disclosure;

[0031] Figure 4 is a schematic diagram of the execution process of a method for determining dynamic distortion of a HUD provided in the first embodiment of the present disclosure;

[0032] Figure 5 is a schematic diagram of a HUD imaging process provided by Embodiment 1 of the present disclosure;

[0033] Figure 6 is a schematic diagram of various eye points in an eye box provided in Embodiment 1 of the present disclosure;

[0034] Figure 7 This is a structural diagram of a device for determining dynamic distortion of a HUD provided in Embodiment 2 of the present disclosure.

[0035] Figure 8 is a structural schematic diagram of an electronic device provided in Embodiment 3 of the present disclosure;

[0036] Fig. 9 is a structural schematic diagram of a system for determining dynamic distortion of a HUD provided in a fourth embodiment of the present disclosure;

[0037] Fig.10 is a schematic diagram of a windshield bracket provided in a fourth embodiment of the present disclosure;

[0038] Fig.11 is a schematic diagram of a HUD windshield on a windshield bracket provided in a fourth embodiment of the present disclosure;

[0039] Fig.12 is a schematic diagram of a HUD bracket provided in Embodiment 4 of the present disclosure;

[0040] Fig.13 It is a schematic diagram of a multi-axis robotic arm provided in Embodiment 4 of the present disclosure. DETAILED DESCRIPTION

[0041] In order to enable those skilled in the art to better understand the solutions of the embodiments of the present disclosure, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are only embodiments of a part of the embodiments of the present disclosure, rather than all of the embodiments. Based on the embodiments in the embodiments of the present disclosure, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the embodiments of the present disclosure.

[0042] It should be noted that the terms "first", "second", etc. in the specification and claims of the embodiments of the present disclosure and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present disclosure described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product, or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products, or devices.

[0043] Embodiment 1

[0044] Figure 1 This is a flow chart of a method for determining the dynamic distortion of a HUD provided in the first embodiment of the present disclosure. This embodiment is applicable to the case where the dynamic distortion of a HUD is determined. The method can be executed by a device for determining the dynamic distortion of a HUD. The device for determining the dynamic distortion of a HUD can be implemented in the form of hardware and / or software. The device for determining the dynamic distortion of a HUD can be configured in an electronic device, and the electronic device includes but is not limited to a computer, a terminal, a server, and other devices with data processing capabilities. Figure 1 As shown, the method includes:

[0045] S110, obtaining a dot map corresponding to each eye point in the eye box.

[0046] In this embodiment, the eye box can be an area in the optical system where the observer's eyes can move, and within this area, the observer can still see the complete image. The eye point is a specific position in the eye box, such as: the eye point can be the center of the eye box or a specific observation point. A dot map is a chart that displays discrete data in units of dots, and each color of dots represents a specific category and is combined in a matrix form. Specifically, a dot map corresponding to different eye point positions in the eye box can be obtained.

[0047] S120, for each eye point and the dot map corresponding to the eye point, determine the camera pixel deviation corresponding to the eye point according to the relative position coordinates of the eye point relative to the target eye point in the eye box, the reference position coordinates of the target eye point, and the number of pixels in the dot map.

[0048] In this embodiment, for any eye point in the eye box, the relative position coordinates of the eye point relative to the target eye point in the eye box and the reference position coordinates of the target eye point can be determined. The reference position coordinates of the target eye point and the relative position coordinates of each eye point relative to the target eye point in the eye box can be obtained in the process of collecting the dot matrix.

[0049] It should be noted that the target eye point can be a central eye point or a comparison eye point. The central eye point can be the central eye point of the eye box, and the comparison eye point can be an eye point randomly selected from the eye box. The comparison eye point is different from the eye point corresponding to the relative position coordinate. For example, the relative position coordinate of the eye point can be expressed as (X i ,Y i ), when the target eye point is the center eye point, the coordinates of the target eye point can be (0,0); when the target eye point is the comparison eye point, the coordinates of the target eye point can be (X d ,Y d ).

[0050] It can be known that after obtaining the relative position coordinates of the eye point, the camera pixel deviation corresponding to the eye point can be determined according to the relative position coordinates of the eye point relative to the target eye point in the eye box, the reference position coordinates of the target eye point, and the number of pixels in the dot map. The number of pixels can be the number of the smallest units used to represent image details in an image. The number of pixels is determined based on the camera parameters of the binocular camera. In a binocular camera system, the number of pixels can be determined based on the camera parameters of the binocular camera, such as the number of pixels can be determined based on the resolution and parameters of the camera. The camera pixel deviation can refer to the deviation between the actual eye point position and the target eye point position, expressed in pixels. This deviation can be used to calibrate and adjust the camera system to ensure that the same imaging effect as the target eye point position is obtained at the actual eye point position.

[0051] S130. For each pixel in the dot map, determine the first dot coordinates corresponding to the pixel based on the dot coordinates of the pixel and the camera pixel deviation corresponding to the corresponding eye point, where the first dot coordinates are the dot coordinates after the deviation of the pixel is eliminated; determine the dynamic distortion of the pixel based on the first dot coordinates and the dot coordinates of the target pixel in the dot map.

[0052] Specifically, after obtaining the camera pixel deviation corresponding to each eye point, for each pixel point in the dot map, the first dot coordinate corresponding to the pixel point can be determined based on the dot coordinate of the pixel point and the camera pixel deviation corresponding to the corresponding eye point, and the first dot coordinate is the dot coordinate after eliminating the deviation of the pixel point. The dot coordinate of the pixel point can be obtained through the dot map.

[0053] Exemplarily, the dot map A1 corresponding to the eye point A includes multiple pixel points x. For any pixel point x1, the dot map coordinates of the pixel point x1 can be corrected by the camera pixel deviation corresponding to the eye point A to obtain the first dot map coordinates of the pixel point x1 after the deviation is eliminated.

[0054] For example, the camera pixel deviation can be expressed as Lx, Ly. Wherein Lx can be the pixel deviation of the camera on the horizontal axis, and Ly can be the pixel deviation of the camera on the vertical axis. The coordinates of each pixel point can be expressed as (x j ,y j ), the first point coordinate can be expressed as: EPi_Pj(x j -Lx,y j +Ly).

[0055] Specifically, after the first dot matrix coordinates are determined, the dynamic distortion of the pixel point may be determined based on the first dot matrix coordinates and the dot matrix coordinates of the target pixel point in the dot matrix, wherein the target pixel point may be the central pixel point in the dot matrix.

[0056] S140: Determine the dynamic distortion of the eye point corresponding to the dot pattern based on the dynamic distortion of each pixel point.

[0057] Specifically, according to the dynamic distortion corresponding to multiple pixels, the dynamic distortion corresponding to each pixel in the dot matrix can be determined, and the dynamic distortion of the eye point corresponding to the dot matrix can be determined based on the dynamic distortion of each pixel. For example, the average value of the dynamic distortion corresponding to each pixel in the dot matrix can be taken as the dynamic distortion of the eye point corresponding to the dot matrix; or the maximum value of the dynamic distortion corresponding to each pixel in the dot matrix can be taken as the dynamic distortion of the eye point corresponding to the dot matrix. Figure 2 A schematic diagram of eye point dynamic distortion provided in this embodiment is shown in FIG. Figure 2 As shown, the green eye point represents the target eye point, and the red eye point is the eye point that needs to calculate dynamic distortion.

[0058] It should be explained that after the dynamic distortion is determined, a detailed test report can be generated based on the determination results of the dynamic distortion. The dynamic distortion index can be set to directly determine which eye points and HUD virtual images do not meet the dynamic standards and which have larger dynamic distortions, which is helpful for analyzing the distribution of dynamic distortion and optimizing the optical path of HUD design.

[0059] The present embodiment provides a method for determining the dynamic distortion of a HUD, comprising: obtaining a dot matrix corresponding to each eye point in an eye box; for each eye point and the dot matrix corresponding to the eye point, determining the camera pixel deviation corresponding to the eye point according to the relative position coordinates of the eye point relative to the target eye point in the eye box, the reference position coordinates of the target eye point, and the number of pixels in the dot matrix; for each pixel point in the dot matrix, determining the first dot matrix coordinate corresponding to the pixel point based on the dot matrix coordinates of the pixel point and the camera pixel deviation corresponding to the corresponding eye point, wherein the first dot matrix coordinate is the dot matrix coordinate after the deviation of the pixel point is eliminated; determining the dynamic distortion of the pixel point based on the first dot matrix coordinate and the dot matrix coordinates of the target pixel point in the dot matrix; determining the dynamic distortion of the eye point corresponding to the dot matrix based on the dynamic distortion of each pixel point, thereby realizing accurate measurement of the dynamic distortion of the HUD.

[0060] As an optional implementation manner of this embodiment, determining the camera pixel deviation corresponding to the eye point according to the relative position coordinates of the eye point relative to the target eye point in the eye box, the reference position coordinates of the target eye point, and the number of pixels in the dot map includes:

[0061] 1) determining the eye point position deviation according to the relative position coordinates of the eye point relative to the target eye point in the eye box, the reference position coordinates of the target eye point and the number of pixels; the eye point position deviation is the position deviation of the eye point relative to the target eye point;

[0062] Specifically, the eye point position deviation can be determined according to the relative position coordinates of the eye point relative to the target eye point in the eye box, the reference position coordinates of the target eye point and the number of pixels. The eye point position deviation can be the position deviation of the eye point relative to the target eye point.

[0063] For example, the relative position coordinates of the eye point relative to the target eye point in the eye box can be expressed as (X i ,Y i ), if the target eye point is the center eye point, the reference position coordinate can be expressed as (0,0), and the eye point position deviation can be expressed as: (X i -0,Y i -0); if the target eye point is the comparison eye point, the reference position coordinate can be expressed as (X d ,Y d ), the eye point position deviation can be expressed as: (X i -X d ,Y i -Y d ).

[0064] 2) Determine the camera pixel deviation based on the eye point position deviation.

[0065] Specifically, after the eye point position deviation is determined, the camera pixel deviation can be determined based on the eye point position deviation and the number of pixels. For example, the number of pixels can be expressed as L. If the eye point position deviation is:

[0066] (X i -0,Y i -0), the camera pixel deviation can be expressed as: Lx = (X i -0)*L,Ly=(Y i -0)*L; if the target eye point is the comparison eye point, the eye point position deviation is: (X i -X d ,Y i -Y d ), the camera pixel deviation can be expressed as: Lx = (X i -X d )*L,Ly=(Y i-Y d )*L. Wherein, Lx can be the pixel deviation of the camera on the horizontal axis, and Ly can be the pixel deviation of the camera on the vertical axis.

[0067] As an optional implementation of this embodiment, the determining the dynamic distortion of the pixel based on the first lattice coordinates and the lattice coordinates of the target pixel in the lattice map includes:

[0068] 1) determining the offset pixel and the offset distance of the pixel point relative to the target pixel point based on the first dot matrix coordinates and the dot matrix coordinates of the target pixel point in the dot matrix map;

[0069] In this embodiment, the target pixel point may be the central pixel point in the dot matrix, and the target pixel point may be expressed as: EPc_Pj(X j ,Y j ). Based on the first lattice coordinates and the lattice coordinates of the target pixel point, an offset pixel and an offset distance of the pixel point relative to the target pixel point are determined.

[0070] Exemplarily, the first lattice coordinates can be expressed as: EPi_Pj(x j -Lx,y j +Ly), the offset pixel can be expressed as: dx = x j -Lx-X j ,dy=y j +Ly-Y j ; where dx can be the horizontal offset in pixels and dy can be the vertical offset in pixels. The offset distance can be expressed as:

[0071] 2) Determine the dynamic distortion of the pixel point according to the offset pixel and the offset distance corresponding to the pixel point.

[0072] Specifically, after the offset pixels and the offset distance are determined, the dynamic distortion of the pixel point may be determined according to the offset pixels and the offset distance corresponding to the pixel point.

[0073] As an optional implementation of this embodiment, the offset pixels include horizontal offset pixels and vertical offset pixels; the dynamic distortion includes horizontal dynamic distortion, vertical dynamic distortion and dynamic distortion percentage;

[0074] The step of determining the dynamic distortion of the pixel point according to the offset pixel and the offset distance corresponding to the pixel point includes:

[0075] 1) Determine the actual offset distance based on the horizontal offset pixels, the vertical offset pixels and the preset physical distance of the pixel points in the dot matrix; the actual offset distance includes the horizontal offset distance and the vertical offset distance; the preset physical distance is the physical distance of the pixel points corresponding to the real world.

[0076] In this embodiment, the preset physical distance can be a pre-set physical distance in the real world corresponding to a single pixel. The actual offset distance is determined based on the horizontal offset pixel, the vertical offset pixel, and the preset physical distance of the pixel in the dot map. The actual offset distance includes the horizontal offset distance and the vertical offset distance. Exemplarily, the horizontal offset distance can be expressed as Δx, the vertical offset distance can be expressed as Δy, and the preset physical distance can be expressed as m, then: Δx=dx*m, Δy=dy*m. Among them, dx can be a horizontal offset pixel, and dy can be a vertical offset pixel.

[0077] 2) Determine the dynamic distortion based on the actual offset distance and the camera parameters of the binocular camera, where the dynamic distortion includes horizontal dynamic distortion and vertical dynamic distortion;

[0078] It can be known that the actual offset distance includes a horizontal offset distance and a vertical offset distance. The horizontal dynamic distortion is determined based on the horizontal offset distance and the camera parameters of the binocular camera, wherein the camera parameters of the binocular camera can be the focal length of the binocular camera. Exemplarily, the horizontal dynamic distortion can be expressed as Bx, then: Bx = arctan (Δx / f); the vertical dynamic distortion can be expressed as By, then: By = arctan (Δy / f), wherein f can be expressed as the focal length of the binocular camera.

[0079] 3) Determine the dynamic distortion percentage based on the offset distance and the preset length.

[0080] Specifically, the dynamic distortion percentage can be determined according to the offset distance and the preset length. The preset length can be a preset length, such as: the preset length can be half of the diagonal length of the dot matrix coordinates of the dot matrix, and the coordinate range of the dot matrix is ​​(x 1 ,y 1 ) to (x n ,y n ). The diagonal length D of the lattice can be calculated using the Euclidean distance formula: Then the half length PD of the diagonal of the lattice coordinates is: PD=D / 2.

[0081] For example, the dynamic distortion percentage can be expressed as Bb, then:

[0082] Bb=(ΔH / PD)*100%

[0083] Here, ΔH may be an offset distance.

[0084] As an optional implementation of this embodiment, the method for determining the dynamic distortion of the HUD provided in this embodiment obtains a dot matrix corresponding to each eye point in the eye box, including:

[0085] 1) Use the robotic arm to control the binocular camera to move to the center eye point of the eye box, and adjust the robotic arm to the preset posture.

[0086] Specifically, the robot arm is used to control the binocular camera to move to the center eye point of the eye box, and the binocular camera is adjusted to a preset posture, wherein the preset posture may be a pre-set posture.

[0087] 2) Adjust the head-up display HUD to the preset test position, and project the test chart onto the windshield to obtain a virtual image of the test chart; based on the preset step path, use the robotic arm to control the binocular camera to move in the eye box, and shoot the virtual image to obtain the dot matrix corresponding to each eye point in the eye box.

[0088] Specifically, the height gear of the HUD can be adjusted to a preset test gear, and the test card can be projected onto the windshield. The preset test gear refers to adjusting the HUD system to a specific setting state, which is pre-defined for standardized testing. The windshield can be a windshield, and the test card can be a pre-established standard card. The test card can be a card containing a specific pattern or mark, which is used to evaluate the imaging quality of the HUD system. Projecting the test card onto the windshield will form a virtual image in the driver's field of view. The virtual image refers to the virtual image of the test card formed on the windshield.

[0089] Continuing from the above description, the preset step size refers to the stepping distance of the robot arm when moving the binocular camera, that is, the specific distance of each movement. Exemplarily, the preset step size can be 65x25mm. The robot arm is an automated device that can accurately control the position and movement. By controlling the binocular camera to move in the eye box through the robot arm, it can be ensured that the camera shoots virtual images at different positions of the eye box to obtain the dot matrix corresponding to each eye point in the eye box. Figure 3 A schematic diagram of a dot matrix provided in this embodiment.

[0090] Figure 4 A schematic diagram of the execution process of a method for determining the dynamic distortion of a HUD provided in this embodiment is shown in FIG. Figure 4As shown, first formulate a HUD dynamic distortion test standard chart, UI display area dot chart (configurable dot number); HUD test bench includes: windshield bracket, HUD bracket and HUD, the windshield bracket, HUD bracket and HUD are established in the same three-dimensional coordinate system, and the three-dimensional coordinates of each part of the bench are obtained according to the theoretical 3D data; start the HUD automated bench program, and automatically position the optical test bench: the HUD automated bench automatically positions the windshield and HUD bracket according to the actual vehicle data, the robotic arm moves the binocular camera to the theoretical eye position, and starts the binocular camera program; the robotic arm controls the binocular camera to move to the center eye position (the center position of the eye box), adjusts to the calibration posture (the preset posture can make the camera perpendicular to the plane where the HUD virtual image is located), adjusts the HUD height gear to the test gear, and can also test the virtual image distance (Virtual Image Distance, VID) data at the center eye position; Figure 5 A schematic diagram of a HUD imaging process provided for this embodiment, the observer sees a virtual image through the windshield, and the HUD shoots the virtual image through the windshield. Project the test chart, the robotic arm can control the camera to maintain the calibration posture, and cooperate with the binocular camera to move to the test eye position, the robotic arm cooperates with the binocular camera to move up and down, left and right in the eye box plane according to the specified step (adjustable step) within the eye box range, note that the movement direction of the camera must be consistent with the horizontal and vertical lines of the camera field of view, and deviation in the direction will lead to inaccurate data for eliminating distance calculation. And control the HUD to automatically project the chart corresponding to the test item, and control the binocular camera to shoot the virtual image. Repeat the virtual image photos at each eye point EPi (the default camera has no lens distortion), and record the coordinates Xi and Yi (relative to the center eye position) of the eye point. According to the method for determining the dynamic distortion of the HUD provided in this embodiment (automatic test report program), the dynamic distortion is determined, and a test report and unqualified eye points are automatically generated.

[0091] Figure 6 This is a schematic diagram of the eye points in the eye box provided in this embodiment. The size of the eye box is 130x50mm, and the preset step size is 65x25mm, so there will be 9 eye points (X1, Y1) to (X9, Y9) in a 3x3 arrangement.

[0092] Embodiment 2

[0093] Figure 7 is a structural schematic diagram of a device for determining dynamic distortion of a HUD provided in Embodiment 2 of the present disclosure; Figure 7 As shown, the device includes: a bitmap acquisition module 210, a camera pixel deviation determination module 220, a pixel point dynamic distortion determination module 230, and a dynamic distortion determination module 240.

[0094] Wherein, the dot map acquisition module 210 acquires the dot map corresponding to each eye point in the eye box;

[0095] The camera pixel deviation determining module 220 determines, for each eye point and the dot map corresponding to the eye point, the camera pixel deviation corresponding to the eye point according to the relative position coordinates of the eye point relative to the target eye point in the eye box, the reference position coordinates of the target eye point, and the number of pixels in the dot map;

[0096] The pixel point dynamic distortion determination module 230 determines, for each pixel point in the dot map, a first dot matrix coordinate corresponding to the pixel point based on the dot matrix coordinate of the pixel point and the camera pixel deviation corresponding to the corresponding eye point, wherein the first dot matrix coordinate is the dot matrix coordinate of the pixel point after the deviation is eliminated; and determines the dynamic distortion of the pixel point based on the first dot matrix coordinate and the dot matrix coordinate of the target pixel point in the dot map;

[0097] The dynamic distortion determination module 240 is used to determine the dynamic distortion of the eye point corresponding to the dot pattern based on the dynamic distortion of each pixel point.

[0098] Embodiment 2 of the present disclosure provides a device for determining the dynamic distortion of a HUD, thereby achieving accurate measurement of the dynamic distortion of the HUD.

[0099] Furthermore, the camera pixel deviation determination module 220 is further configured to:

[0100] Determine an eye point position deviation according to the relative position coordinates of the eye point relative to the target eye point in the eye box, the reference position coordinates of the target eye point and the number of pixels; the eye point position deviation is the position deviation of the eye point relative to the target eye point;

[0101] The camera pixel deviation is determined according to the eye point position deviation.

[0102] Furthermore, the pixel point dynamic distortion determination module 230 further includes:

[0103] An offset pixel and offset distance determining unit, configured to determine an offset pixel and an offset distance of the pixel relative to the target pixel based on the first dot matrix coordinates and the dot matrix coordinates of the target pixel in the dot matrix;

[0104] The first dynamic distortion determination unit is used to determine the dynamic distortion of the pixel point according to the offset pixel and the offset distance corresponding to the pixel point.

[0105] Further, the offset pixels include horizontal offset pixels and vertical offset pixels; the dynamic distortion includes horizontal dynamic distortion, vertical dynamic distortion and dynamic distortion percentage;

[0106] The first dynamic distortion determination unit is further configured to:

[0107] Determine the actual offset distance based on the horizontal offset pixels, the vertical offset pixels and the preset physical distance of the pixel points in the bitmap; the actual offset distance includes the horizontal offset distance and the vertical offset distance; the preset physical distance is the physical distance of the pixel points corresponding to the real world;

[0108] Determining the dynamic distortion based on the actual offset distance and the camera parameters of the binocular camera, wherein the dynamic distortion includes horizontal dynamic distortion and vertical dynamic distortion;

[0109] The dynamic distortion percentage is determined according to the offset distance and a preset length.

[0110] Furthermore, the dot map acquisition module 210 is also used for:

[0111] Using a robotic arm to control the binocular camera to move to the center eye point of the eye box, and adjusting the robotic arm to a preset posture;

[0112] The head-up display HUD is adjusted to a preset test position, and the test chart is projected onto the windshield to obtain a virtual image of the test chart; based on a preset step path, a robotic arm is used to control the binocular camera to move in the eye box, and the virtual image is photographed to obtain a dot matrix corresponding to each eye point in the eye box.

[0113] The device for determining the dynamic distortion of the HUD provided in the embodiments of the present disclosure can execute the method for determining the dynamic distortion of the HUD provided in any embodiment of the embodiments of the present disclosure, and has the corresponding functional modules and beneficial effects of the execution method.

[0114] Embodiment 3

[0115] Figure 8 A schematic diagram of the structure of an electronic device 10 that can be used to implement an embodiment of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the embodiments of the present disclosure described and / or claimed herein.

[0116] like Figure 8As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0117] A number of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0118] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microprocessor, etc. The processor 11 executes the various methods and processes described above, such as a method for determining the dynamic distortion of the HUD.

[0119] In some embodiments, the method for determining the dynamic distortion of the HUD may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the method for determining the dynamic distortion of the HUD described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to perform the method for determining the dynamic distortion of the HUD in any other appropriate manner (e.g., by means of firmware).

[0120] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0121] The computer programs for implementing the methods of the embodiments of the present disclosure may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine as a stand-alone software package and partially on a remote machine, or entirely on a remote machine or server.

[0122] In the context of the disclosed embodiments, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, device, or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0123] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0124] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0125] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0126] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps recorded in the embodiments of the present disclosure can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solutions of the embodiments of the present disclosure can be achieved, and this document does not limit this.

[0127] The above specific implementations do not constitute a limitation on the protection scope of the embodiments of the present disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the embodiments of the present disclosure shall be included in the protection scope of the embodiments of the present disclosure.

[0128] The embodiments of the present disclosure also provide a computer program product, including a computer program and / or instructions, which, when executed by a processor, implements a method for determining the dynamic distortion of the HUD as provided in any embodiment of the present application.

[0129] In the process of implementation, the computer program product can be written in one or more programming languages ​​or a combination thereof to write computer program codes for performing the operation of the disclosed embodiments, the programming languages ​​including object-oriented programming languages, such as Java, Smalltalk, C++, and also including conventional procedural programming languages, such as "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as an independent software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computer (e.g., using an Internet service provider to connect through the Internet).

[0130] Note that the above are only preferred embodiments of the embodiments of the present disclosure and the technical principles used. Those skilled in the art will understand that the embodiments of the present disclosure are not limited to the specific embodiments herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the protection scope of the embodiments of the present disclosure. Therefore, although the embodiments of the present disclosure are described in more detail through the above embodiments, the embodiments of the present disclosure are not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the embodiments of the present disclosure, and the scope of the embodiments of the present disclosure is determined by the scope of the attached claims.

[0131] Embodiment 4

[0132] Embodiment 4 of the present disclosure further provides a system for determining the dynamic distortion of a HUD, the system comprising a multi-axis robotic arm, a binocular camera, a head-up display (HUD) test bench, and the electronic device as described in Embodiment 3 above; wherein the head-up display (HUD) test bench comprises: a windshield bracket, a head-up display (HUD) bracket, and a head-up display (HUD); the windshield bracket is used to adjust the windshield angle so that the test chart is projected onto the windshield; the head-up display (HUD) bracket is used to adjust the head-up display (HUD) to a preset test position; the windshield bracket and the head-up display (HUD) bracket are installed at a preset position, and the preset position is determined based on driving data.

[0133] Specifically, Fig. 9 This is a structural diagram of a system 40 for determining dynamic distortion of a HUD provided in Embodiment 4 of the present disclosure. Fig. 9 As shown, the system includes: a multi-axis mechanical arm 401, a binocular camera 402, a HUD test bench 403 and an electronic device 404. The HUD test bench 403 includes: a windshield bracket 4031, a HUD bracket 4032 and a HUD 4033. Fig.10 A schematic diagram of a windshield bracket provided in this embodiment, Fig.11 Schematic diagram of the HUD windshield on the windshield bracket, such as Fig.10 , Fig.11 As shown, the windshield bracket is used to adjust the windshield angle so that the test chart can be projected onto the windshield. The windshield bracket can be adapted to windshields of different vehicle models and can be programmably adjusted to different angles. Fig.12 A schematic diagram of a HUD bracket provided in this embodiment, such as Fig.12 As shown, the HUD bracket can move in three directions, XYZ, to adapt to different positions (including the co-pilot position), and can be moved to different coordinate positions. Fig.13 A schematic diagram of a multi-axis robotic arm provided in this embodiment, such as Fig.13 As shown, the multi-axis robotic arm can move accurately in the world coordinate system and the camera coordinate system, and cooperate with the camera to shoot tests at different positions.

[0134] The system for determining the dynamic distortion of a HUD provided in the fourth embodiment can be used to execute the method for determining the dynamic distortion of a HUD provided in any of the above embodiments, and has corresponding functions and beneficial effects.

Claims

1. A method for determining dynamic distortion of a HUD, characterized in that: include: Obtain the dot map corresponding to each eye point in the eye box; For each eye point and the dot map corresponding to the eye point, determine the camera pixel deviation corresponding to the eye point according to the relative position coordinates of the eye point relative to the target eye point in the eye box, the reference position coordinates of the target eye point, and the number of pixels in the dot map; For each pixel in the dot map, determine a first dot matrix coordinate corresponding to the pixel based on the dot matrix coordinate of the pixel and the camera pixel deviation corresponding to the corresponding eye point, where the first dot matrix coordinate is the dot matrix coordinate of the pixel after the deviation is eliminated; determine the dynamic distortion of the pixel based on the first dot matrix coordinate and the dot matrix coordinate of the target pixel in the dot map; The dynamic distortion of the eye point corresponding to the dot pattern is determined based on the dynamic distortion of each pixel point.

2. The method according to claim 1, characterized in that The step of determining the camera pixel deviation corresponding to the eye point according to the relative position coordinates of the eye point relative to the target eye point in the eye box, the reference position coordinates of the target eye point, and the number of pixels in the dot map comprises: Determine an eye point position deviation according to the relative position coordinates of the eye point relative to the target eye point in the eye box, the reference position coordinates of the target eye point and the number of pixels; the eye point position deviation is the position deviation of the eye point relative to the target eye point; The camera pixel deviation is determined according to the eye point position deviation.

3. The method according to claim 1, characterized in that The determining the dynamic distortion of the pixel point based on the first lattice coordinates and the lattice coordinates of the target pixel point in the lattice map includes: Determine the offset pixel and offset distance of the pixel point relative to the target pixel point based on the first dot matrix coordinates and the dot matrix coordinates of the target pixel point in the dot matrix map; The dynamic distortion of the pixel point is determined according to the offset pixel and the offset distance corresponding to the pixel point.

4. The method according to claim 3, characterized in that The offset pixels include horizontal offset pixels and vertical offset pixels; the dynamic distortion includes horizontal dynamic distortion, vertical dynamic distortion and dynamic distortion percentage; The determining the dynamic distortion of the pixel point according to the offset pixel and the offset distance corresponding to the pixel point includes: Determine the actual offset distance based on the horizontal offset pixels, the vertical offset pixels and the preset physical distance of the pixel points in the bitmap; the actual offset distance includes the horizontal offset distance and the vertical offset distance; the preset physical distance is the physical distance of the pixel points corresponding to the real world; Determining the dynamic distortion based on the actual offset distance and camera parameters of the binocular camera, wherein the dynamic distortion includes horizontal dynamic distortion and vertical dynamic distortion; The dynamic distortion percentage is determined according to the offset distance and a preset length.

5. The method according to claim 1, characterized in that Get the dot map corresponding to each eye point in the eye box, including: Using a robotic arm to control the binocular camera to move to the center eye point of the eye box, and adjusting the robotic arm to a preset posture; The head-up display HUD is adjusted to a preset test position, and the test chart is projected onto the windshield to obtain a virtual image of the test chart; based on a preset step path, a robotic arm is used to control the binocular camera to move in the eye box, and the virtual image is photographed to obtain a dot matrix corresponding to each eye point in the eye box.

6. A device for determining dynamic distortion of a HUD, characterized in that: include: A dot matrix acquisition module is used to acquire dot matrix images corresponding to each eye point in the eye box; a camera pixel deviation determination module, for each eye point and the dot map corresponding to the eye point, determining the camera pixel deviation corresponding to the eye point according to the relative position coordinates of the eye point relative to the target eye point in the eye box, the reference position coordinates of the target eye point, and the number of pixels in the dot map; A pixel point dynamic distortion determination module, for each pixel point in the dot map, determines a first dot matrix coordinate corresponding to the pixel point based on the dot matrix coordinate of the pixel point and the camera pixel deviation corresponding to the corresponding eye point, wherein the first dot matrix coordinate is the dot matrix coordinate of the pixel point after the deviation is eliminated; and determines the dynamic distortion of the pixel point based on the first dot matrix coordinate and the dot matrix coordinate of the target pixel point in the dot map; The dynamic distortion determination module is used to determine the dynamic distortion of the eye point corresponding to the dot pattern based on the dynamic distortion of each pixel point.

7. An electronic device, characterized in that: include: at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the method for determining the dynamic distortion of the HUD as described in any one of claims 1-5.

8. A system for determining dynamic distortion of a HUD, characterized in that: The system comprises a multi-axis robotic arm, a binocular camera, a head-up display (HUD) test bench, and the electronic device as claimed in claim 7; Wherein, the head-up display HUD test bench comprises: a windshield bracket, a head-up display HUD bracket and a head-up display HUD; The windshield bracket is used to adjust the windshield angle so that the test chart can be projected onto the windshield; The head-up display HUD bracket is used to adjust the head-up display HUD to a preset test gear position; The windshield bracket and the head-up display (HUD) bracket are installed at preset positions, and the preset positions are determined based on driving data.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method for determining the dynamic distortion of the HUD as described in any one of claims 1 to 5 is implemented.

10. A computer program product, characterized in that The computer program product comprises a computer program, which, when executed by a processor, implements the method for determining the dynamic distortion of the HUD according to any one of claims 1 to 5.

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