View refraction uniformity analysis method and system in close-range working environment, computer equipment and storage medium

Abstract

The invention provides a visual field refraction uniformity analysis method and system for a close-range working environment, computer equipment and a storage medium, and the method comprises the steps: converting the depth value of each pixel in a depth image of a target environment into a distance-to-eye depth value, and then converting the distance-to-eye depth value into a diopter, thereby obtaining a diopter image of the target environment; determining a defocus value of each pixel in the diopter image to obtain a defocus image of the target environment; obtaining a defocus image of a visual field area in the target environment defocus image to serve as a first defocus image of the visual field area; and performing two-dimensional integration on the defocus value of each pixel in the first defocus image to obtain a second defocus image of the view field area so as to determine the refractive uniformity of the view field area. According to the method, the calculation of the peripheral defocus distribution of the close-range working environment is realized, and the method can be used for judging the peripheral defocus size and refraction uniformity of the eye fixation point in various close-range working environments, so that a method basis is provided for measurement calculation and research in related fields.

Description

Technical Field

[0001] The present invention belongs to the technical field of image processing, and particularly relates to a method, a system, a computer device and a storage medium for analyzing the refractive uniformity of the field of view in a close working environment. Background Art

[0002] A close working environment refers to an environment where learning or work needs to be completed at a relatively close distance for a long time with a relatively fixed posture, such as a school desk in a classroom, a writing desk at home, an office workbench, etc. Long-term high-intensity close vision work during school age is also a recognized risk factor for myopia. Therefore, the research on the eye visual conditions of teenagers during close work is crucial for myopia prevention and control.

[0003] Defocus is a situation where some parts of an image are blurred or unclear. A defocus map is an image representing the defocus degree of different regions in an image. According to the thin lens model, the structure of the eye can be simplified and represented by a lens, a diaphragm, and an imaging plane. When working, the lens focuses on the focal point where the fixation point is located, and the object at this focal distance forms a clear image on the imaging plane (i.e., the retina). Objects closer or farther than the focal point will produce blurred retinal images. Peripheral defocus exists in the range of the human eye imaging except for the fixation point. The greater the defocus degree, the worse the refractive uniformity, and the more unfavorable it is for the normal development of the human eye. Current research finds that when viewing objects, the greater the hyperopic defocus degree in the peripheral visual field, the worse the refractive uniformity of the working environment, and the easier it is to accelerate the development of myopia. However, in current research, the refractive uniformity cannot be directly measured, which limits the research on environmental exposure and eye development or other related fields.

[0004] In recent years, many scholars have also used sensors to quantify the visual task distance and peripheral defocus distribution. In 2017, M. Gu et al. statistically analyzed the defocus blur that occurs naturally in the human eye using an eye tracker and observed the defocus rules in different visual field regions. et al. quantified the defocus amount in different indoor scenes using an RGB depth sensor and an eye tracker; in 2020, Choi et al. used a static three-dimensional (3D) distance sensor to quantify the peripheral defocus distribution related to the home close working environment. However, these studies did not consider the actual close working environment or the true visual distance or defocus situation of the eyes during actual work. Therefore, how to obtain the true defocus distribution in the close working environment to judge the refractive uniformity is an urgent problem for those skilled in the art. Summary of the Invention

[0005] The present invention provides a method, system, computer device and storage medium for analyzing the refractive uniformity of the visual field in a near working environment, so as to solve the problem that the actual near working environment or the true visual distance or defocus condition of the eyes in actual work is not considered in the prior art.

[0006] In a first aspect, the present invention provides a method for analyzing the refractive uniformity of the visual field in a near working environment, including:

[0007] Obtain a depth image of the target environment captured by a depth camera;

[0008] Convert the depth value of each pixel in the depth image into a depth value from the eye; wherein, the equivalent position of the depth camera, the equivalent position of the human eye, and the fixation point of the human eye in the target environment are on the same straight line;

[0009] Convert the depth value from the eye of each pixel into a diopter to obtain a diopter map of the target environment;

[0010] Determine the defocus value of each pixel in the diopter map according to the diopter of the pixel corresponding to the fixation point and the diopters of the remaining pixels in the diopter map, so as to obtain a defocus map of the target environment;

[0011] Obtain the defocus map of the visual field area in the defocus map of the target environment as the first defocus map of the visual field area; wherein, the visual field area is centered on the fixation point;

[0012] Perform two-dimensional integration on the defocus value of each pixel in the first defocus map to obtain a second defocus map of the visual field area, so as to determine the refractive uniformity of the visual field area.

[0013] Optionally, the conversion of the depth value of each pixel in the depth image into a depth value from the eye includes:

[0014] Convert the pixel coordinates of each pixel in the depth image into three-dimensional coordinates; wherein, the fixation point coordinates in the three-dimensional coordinate system are (x0, y0, z0), and the equivalent position coordinates of the depth camera are (x0, y0, 0);

[0015] Determine the angle between the line connecting the depth camera to each pixel in the depth image and the line connecting the depth camera to the fixation point in the three-dimensional coordinate system;

[0016] Convert the angle between the line connecting the depth camera to each pixel in the depth image and the line connecting the depth camera to the fixation point into radians;

[0017] Calculate the depth value from the eye of each pixel according to the following formula:

[0018]

[0019] Among them, h is the depth value from the eye to the target pixel in the depth image; d is the distance between the lens of the depth camera and the human eye; k is the depth value of the target pixel in the depth image measured by the depth camera; α rad is the radian corresponding to the angle between the line connecting the depth camera to the target pixel in the depth image and the line connecting the depth camera to the fixation point.

[0020] Optionally, the determining the defocus value of each pixel in the diopter map according to the diopter of the pixel corresponding to the fixation point and the diopters of the remaining pixels in the diopter map to obtain the defocus map of the target environment includes:

[0021] Obtaining the diopter of each pixel in the diopter map of the target environment;

[0022] Taking the difference between the diopter of the target pixel and the diopter of the fixation point as the defocus value of the target pixel;

[0023] Mapping the diopter map to a color image according to the defocus value of each pixel in the diopter map to obtain the defocus map of the target environment.

[0024] Optionally, the performing two-dimensional integration on the defocus value of each pixel in the first defocus map to obtain the second defocus map of the visual field region includes:

[0025] Performing two-dimensional integration on the defocus value of each pixel in the first defocus map according to the following formula:

[0026] S = ∫∫|ΔD|dx1dy1;

[0027] where S is the two-dimensional integral value of the defocus value ΔD of the target pixel in the first defocus map; (x1, y1) is the coordinate of the target pixel in the first defocus map.

[0028] In a second aspect, the present invention provides a visual field refractive uniformity analysis system for a close working environment, including:

[0029] A first acquisition module, configured to acquire a depth image of a target environment captured by a depth camera;

[0030] A first conversion module, configured to convert the depth value of each pixel in the depth image into a depth value from the eye; wherein, the equivalent position of the depth camera, the equivalent position of the human eye, and the fixation point of the human eye in the target environment are on the same straight line;

[0031] A second conversion module, configured to convert the depth value from the eye of each pixel into a diopter to obtain a diopter map of the target environment;

[0032] A determination module, configured to determine the defocus value of each pixel in the diopter map according to the diopter of the pixel corresponding to the fixation point and the diopters of the remaining pixels in the diopter map to obtain a defocus map of the target environment;

[0033] A second acquisition module, configured to acquire a defocus map of a visual field region in a target environment defocus map as a first defocus map of the visual field region; wherein, the visual field region is centered on a fixation point;

[0034] An integration module, configured to perform two-dimensional integration on the defocus values of each pixel in the first defocus map to obtain a second defocus map of the visual field region, so as to determine the refractive uniformity of the visual field region.

[0035] Optionally, the first conversion module includes:

[0036] A first conversion unit, configured to convert the pixel coordinates of each pixel in the depth image into three-dimensional coordinates; wherein, the fixation point coordinates in the three-dimensional coordinate system are (x0, y0, z0), and the equivalent position coordinates of the depth camera are (x0, y0, 0);

[0037] A first determination unit, configured to determine, in the three-dimensional coordinate system, the angle between the line connecting the depth camera to each pixel in the depth image and the line connecting the depth camera to the fixation point;

[0038] A second conversion unit, configured to convert the angle between the line connecting the depth camera to each pixel in the depth image and the line connecting the depth camera to the fixation point into radians;

[0039] A first calculation unit, configured to calculate the depth value from the eye of each pixel according to the following formula:

[0040]

[0041] wherein, h is the depth value from the eye of the target pixel in the depth image; d is the distance between the lens of the depth camera and the human eye; k is the depth value of the target pixel measured by the depth camera in the depth image; α rad is the radian corresponding to the angle between the line connecting the depth camera to the target pixel in the depth image and the line connecting the depth camera to the fixation point.

[0042] Optionally, the determination module includes:

[0043] An acquisition unit, configured to acquire the diopter of each pixel in the diopter map of the target environment;

[0044] A second determination unit, configured to use the difference between the diopter of the target pixel and the diopter of the fixation point as the defocus value of the target pixel;

[0045] A mapping unit, configured to map the diopter map into a color image according to the defocus value of each pixel in the diopter map to obtain the defocus map of the target environment.

[0046] Optionally, the integration module includes:

[0047] A second calculation unit, configured to perform two-dimensional integration on the defocus value of each pixel in the first defocus map according to the following formula:

[0048] S = ∫∫|ΔD|dx1dy1;

[0049] where S is the two-dimensional integration value of the defocus value ΔD of the target pixel in the first defocus map; (x1, y1) is the coordinate of the target pixel in the first defocus map.

[0050] In a third aspect, the present invention provides a computer device, including a processor and a memory; wherein, when the processor executes the computer program stored in the memory, the steps of the method for analyzing the vision refractive uniformity in a close working environment described in the first aspect are implemented.

[0051] In a fourth aspect, the present invention provides a computer-readable storage medium for storing a computer program; when the computer program is executed by a processor, the steps of the method for analyzing the vision refractive uniformity in a close working environment described in the first aspect are implemented.

[0052] The present invention provides a method, a system, a computer device and a storage medium for analyzing the vision refractive uniformity in a close working environment. In the method, a depth camera is used to collect depth images of the environment for analysis, measure the blur distribution caused by defocus at each point in the vision during close fixation work, understand the defocus distribution in the close working environment, and the result is output as an environmental defocus distribution map with the fixation point as a reference. By integrating the defocus amount of the image, the size and refractive uniformity of the environmental defocus distribution can be directly judged. The smaller the integration value, the better the refractive uniformity represented by the image. Moreover, the present invention can process pictures in batches simultaneously, with high calculation efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] In order to more clearly illustrate the technical solutions of the present invention, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only the embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0054] Figure 1 It is a schematic flowchart of a method for analyzing the vision refractive uniformity in a close working environment provided by an embodiment of the present invention;

[0055] Figure 2 It is a schematic diagram of an environmental scene photograph provided by an embodiment of the present invention;

[0056] Figure 3 It is an environmental distance-to-eye depth map provided by an embodiment of the present invention;

[0057] Figure 4 It is a diopter map provided by an embodiment of the present invention;

[0058] Figure 5 It is the environmental defocus distribution map provided by the embodiment of the present invention;

[0059] Figure 6 It is the 30° central visual field defocus map provided by the embodiment of the present invention;

[0060] Figure 7 It is a schematic structural diagram of a visual field refractive uniformity analysis system for a near - distance working environment provided by the embodiment of the present invention. Detailed implementation manners

[0061] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without making creative efforts belong to the scope of protection of the present invention.

[0062] Embodiment 1

[0063] As Figure 1 shown, this embodiment provides a method for analyzing the visual field refractive uniformity of a near - distance working environment, including:

[0064] Step 101, obtain the depth image of the target environment captured by the depth camera.

[0065] In this step, taking the working station as the research environment scene, analyze the refractive uniformity of the area around the eye fixation point during work. Place the KinectV2 in the manner shown Figure 2 to ensure that the KinectV2 camera, the human eye, and the fixation point are on the same straight line. Use a meter stick to measure and ensure that the distance between the KinectV2 camera and the human eye is a fixed value d, and capture the depth map of the original environment (i.e., the working station); use MATLAB software to adjust the image pixels to a unified size (424×512) and save it in 16 - bit grayscale format.

[0066] For the depth - missing areas caused by specular reflection or occlusion, use the pixel filtering method to fill them. The specific operation is to traverse all pixels in the RGB - D depth image (16 - bit png format) of the KinectV2, fill the '0' depth value with the statistical mode of the surrounding 25 values, and finally obtain 424·512 depth values depth and save them as the original depth matrix data.

[0067] Step 102, convert the depth value of each pixel in the depth image into the depth value from the eye; wherein, the equivalent position of the depth camera, the equivalent position of the human eye, and the fixation point of the human eye in the target environment are on the same straight line.

[0068] In this step, the Kinect SDK function is called through MATLAB to convert the unit of the original depth value from mm (millimeter) to m (meter), and the effective depth range is defined as: 0 < k < 4.5 m.

[0069] Traverse the original depth matrix, and for each pixel point (x, y), perform the following: establish a three-dimensional coordinate system, convert the pixel coordinates to three-dimensional coordinates (x’, y’, z’), set the fixation point coordinates as (x0, y0, z0), and the equivalent coordinates of KinectV2 as (x0, y0, 0), and calculate the vector from each pixel point to KinectV2.

[0070] Use the dot function and the norm function to calculate the vector and modulus of each pixel point, and then use the acos function to calculate the angle α between the line connecting KinectV2 to each pixel point and the line connecting KinectV2 to the fixation point, and then convert the angle to radians: α rad = απ / 180.

[0071] Exemplarily, this step includes:

[0072] Convert the pixel coordinates of each pixel in the depth image to three-dimensional coordinates; among them, the fixation point coordinates in the three-dimensional coordinate system are (x0, y0, z0), and the equivalent position coordinates of the depth camera are (x0, y0, 0).

[0073] Determine the angle between the line connecting the depth camera to each pixel in the depth image and the line connecting the depth camera to the fixation point in the three-dimensional coordinate system.

[0074] Convert the angle between the line connecting the depth camera to each pixel in the depth image and the line connecting the depth camera to the fixation point to radians.

[0075] Calculate the depth value from the eye for each pixel according to the following formula:

[0076]

[0077] where h is the depth value from the eye of the target pixel in the depth image; d is the distance between the lens of the depth camera and the human eye; k is the depth value of the target pixel in the depth image measured by the depth camera; α rad is the radian corresponding to the angle between the line connecting the depth camera to the target pixel in the depth image and the line connecting the depth camera to the fixation point.

[0078] Save the calculation result to the matrix h(x, y), save the matrix as an excel file and draw the actual depth map from the eye through the function, as Figure 3 shown.

[0079] Step 103: Convert the depth value from the eye of each pixel to diopters to obtain the diopter map of the target environment.

[0080] In this step, based on the thin lens model, the diopter D = 1 / h of each pixel is calculated to generate a diopter matrix D(x, y), which is then normalized to the 0-255 gray scale range to generate an image, as Figure 4 shown.

[0081] Step 104: Determine the defocus value of each pixel in the diopter map according to the diopter of the pixel corresponding to the fixation point and the diopters of the remaining pixels in the diopter map, so as to obtain the defocus map of the target environment.

[0082] Exemplarily, this step includes:

[0083] Obtain the diopter of each pixel in the diopter map of the target environment.

[0084] Take the difference between the diopter of the target pixel and the diopter of the fixation point as the defocus value of the target pixel, that is, ΔD = D - D0; D is the defocus value of the target pixel; in this step, the target pixel also includes the pixel corresponding to the fixation point; D0 is the diopter of the fixation point; a positive ΔD indicates hyperopic defocus, and a negative ΔD indicates myopic defocus.

[0085] Map the diopter map to a color image according to the defocus value of each pixel in the diopter map (through MATLAB code) to obtain the defocus map of the target environment, and label a legend on the right side of the defocus map of the target environment, as Figure 5 shown, and at the same time output the environmental defocus value data.

[0086] Step 105: Obtain the defocus map of the visual field area in the defocus map of the target environment as the first defocus map of the visual field area; wherein, the visual field area is centered on the fixation point.

[0087] In this step, the human eye fixation point is set as the reference point, and the visual field area is extracted. The angular range of the visual field can be set artificially according to actual needs.

[0088] Step 106: Perform two-dimensional integration on the defocus value of each pixel in the first defocus map to obtain the second defocus map of the visual field area to determine the refractive uniformity of the visual field area.

[0089] Use the built-in trapz function in MATLAB to perform two-dimensional integration on the defocus value of the central visual field. Exemplarily, perform two-dimensional integration on the defocus value of each pixel in the first defocus map according to the following formula:

[0090] S = ∫∫|ΔD|dx1dy1.

[0091] where S is the two-dimensional integral value of the defocus value ΔD of the target pixel in the first defocus map; (x1, y1) is the coordinate of the target pixel in the first defocus map.

[0092] Export the visual defocus data, output the mean value and integral value for analyzing refractive uniformity, and generate a defocus (distribution) map of the visual field area, as Figure 6 shown.

[0093] In this embodiment, the average value of the defocus value in the central visual field area is analyzed as: -0.00012D, and the integral value of the diopter in the central visual field is: -0.92D·deg 2 , the defocus amount in the visual environment is small, and the refractive uniformity is good. This embodiment illustrates the effectiveness of the numerical calculation of defocus in a near-work environment.

[0094] In summary, this embodiment provides a method for analyzing the refractive uniformity of the visual field in a near-work environment. The depth image of the environment is collected by a depth camera for analysis, and the blur distribution caused by defocus at each point in the visual field during near-fixation work is measured to understand the defocus distribution in the near-work environment. The result is output as a defocus map of the environment with the fixation point as a reference. By integrating the defocus amount of the image, the size and refractive uniformity of the environmental defocus distribution can be directly judged. The smaller the integral value, the smaller the defocus degree of the visual field represented by the image, and the better the refractive uniformity. Moreover, the present invention can process images in batches simultaneously, with high calculation efficiency.

[0095] Embodiment 2

[0096] Based on the same inventive concept as Embodiment 1, this embodiment provides a system for analyzing the refractive uniformity of the visual field in a near-work environment. Since the principle of solving problems by this system is similar to that of the method for analyzing the refractive uniformity of the visual field in the near-work environment described above, the implementation of this system can refer to the implementation of the method for analyzing the refractive uniformity of the visual field in the near-work environment.

[0097] As Figure 7 shown, the system for analyzing the refractive uniformity of the visual field in a near-work environment includes:

[0098] The first acquisition module 10 is used to acquire the depth image of the target environment captured by the depth camera.

[0099] The first conversion module 20 is used to convert the depth value of each pixel in the depth image into the depth value from the eye; wherein, the equivalent position of the depth camera, the equivalent position of the human eye, and the fixation point of the human eye in the target environment are located on the same straight line.

[0100] The second conversion module 30 is used to convert the depth value from the eye of each pixel into the diopter to obtain the diopter map of the target environment.

[0101] The determination module 40 is used to determine the defocus value of each pixel in the diopter map according to the diopter of the pixel corresponding to the fixation point and the diopters of the remaining pixels in the diopter map, so as to obtain the defocus map of the target environment.

[0102] A second acquisition module 50, configured to acquire a defocus map of a visual field area in the target environment defocus map as a first defocus map of the visual field area; wherein, the visual field area is centered on the fixation point.

[0103] An integration module 60, configured to perform two-dimensional integration on the defocus values of each pixel in the first defocus map to obtain a second defocus map of the visual field area, so as to determine the refractive uniformity of the visual field area.

[0104] Exemplarily, the first conversion module includes:

[0105] A first conversion unit, configured to convert the pixel coordinates of each pixel in the depth image into three-dimensional coordinates; wherein, the fixation point coordinates in the three-dimensional coordinate system are (x0, y0, z0), and the equivalent position coordinates of the depth camera are (x0, y0, 0).

[0106] A first determination unit, configured to determine, in the three-dimensional coordinate system, the angle between the line connecting the depth camera to each pixel in the depth image and the line connecting the depth camera to the fixation point.

[0107] A second conversion unit, configured to convert the angle between the line connecting the depth camera to each pixel in the depth image and the line connecting the depth camera to the fixation point into radians.

[0108] A first calculation unit, configured to calculate the eye-depth value of each pixel according to the following formula:

[0109]

[0110] wherein, h is the eye-depth value of the target pixel in the depth image; d is the distance between the lens of the depth camera and the human eye; k is the depth value of the target pixel measured by the depth camera in the depth image; α rad is the radian corresponding to the angle between the line connecting the depth camera to the target pixel in the depth image and the line connecting the depth camera to the fixation point.

[0111] Exemplarily, the determination module includes:

[0112] An acquisition unit, configured to acquire the diopter of each pixel in the diopter map of the target environment.

[0113] A second determination unit, configured to use the difference between the diopter of the target pixel and the diopter of the fixation point as the defocus value of the target pixel.

[0114] A mapping unit, configured to map the diopter map into a color image according to the defocus value of each pixel in the diopter map to obtain the defocus map of the target environment.

[0115] Exemplarily, the integration module includes:

[0116] A second calculation unit for performing two-dimensional integration on the defocus value of each pixel in the first defocus map according to the following formula:

[0117] S = ∫∫|ΔD|dx1dy1.

[0118] Where S is the two-dimensional integral value of the defocus value ΔD of the target pixel in the first defocus map; (x1, y1) is the coordinate of the target pixel in the first defocus map.

[0119] For the more specific working processes of the above various modules, reference can be made to the corresponding content disclosed in Embodiment 1, and details will not be elaborated here.

[0120] Embodiment 3

[0121] This embodiment provides a computer device including a processor and a memory; wherein, when the processor executes the computer program stored in the memory, the steps of the method for analyzing the vision refractive uniformity in a close working environment described in Embodiment 1 are implemented.

[0122] For the more specific process of the above method, reference can be made to the corresponding content disclosed in Embodiment 1, and details will not be elaborated here.

[0123] Embodiment 4

[0124] This embodiment provides a computer-readable storage medium for storing a computer program; when the computer program is executed by a processor, the steps of the method for analyzing the vision refractive uniformity in a close working environment described in Embodiment 1 are implemented.

[0125] For the more specific process of the above method, reference can be made to the corresponding content disclosed in Embodiment 1, and details will not be elaborated here.

[0126] Embodiment 5

[0127] This embodiment provides a computer program product including computer-executable instructions or a computer program. When the computer-executable instructions or the computer program are executed by a processor, the steps of the method for analyzing the vision refractive uniformity in a close working environment described in Embodiment 1 are implemented.

[0128] For the more specific process of the above method, reference can be made to the corresponding content disclosed in Embodiment 1, and details will not be elaborated here.

[0129] In this specification, the various embodiments are described in a progressive manner. Each embodiment focuses on the differences from other embodiments, and the same or similar parts among the embodiments can be referred to each other. For the systems, devices, storage media, and computer program products disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the descriptions are relatively simple, and the relevant parts can be referred to the description of the method part.

[0130] Those skilled in the art can clearly understand that the technology in the embodiments of the present invention can be implemented by means of software plus a necessary general hardware platform. Based on such an understanding, the technical solutions in the embodiments of the present invention, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in various embodiments or some parts of the embodiments of the present invention.

[0131] In some embodiments, the computer-executable instructions can be in the form of a program, software, software module, script, or code, written in any form of programming language (including compiled or interpreted languages, or declarative or procedural languages), and can be deployed in any form, including being deployed as an independent program or being deployed as a module, component, subroutine, or other unit suitable for use in a computing environment.

[0132] As an example, the computer-executable instructions may or may not correspond to files in the file system, and can be stored as part of a file that stores other programs or data. For example, they can be stored in one or more scripts in a Hyper Text Markup Language (HTML) document, stored in a single file dedicated to the program in question, or stored in multiple cooperating files (for example, files that store one or more modules, subroutines, or code portions).

[0133] As an example, the computer-executable instructions can be deployed to be executed on one electronic device, or on multiple electronic devices located at one location, or on multiple electronic devices distributed at multiple locations and interconnected through a communication network.

[0134] The present invention has been described in detail above in conjunction with specific embodiments and exemplary examples, but these descriptions should not be construed as limiting the present invention. Those skilled in the art understand that without departing from the spirit and scope of the present invention, various equivalent substitutions, modifications, or improvements can be made to the technical solutions and their implementation manners of the present invention, and all of these fall within the scope of the present invention. The protection scope of the present invention is subject to the appended claims.

[0135] The present invention has been described in detail above in conjunction with specific embodiments and exemplary examples. However, these descriptions should not be construed as limiting the present invention. Those skilled in the art understand that, without departing from the spirit and scope of the present invention, various equivalent substitutions, modifications or improvements can be made to the technical solutions of the present invention and their implementation manners, and all of these fall within the scope of the present invention. The protection scope of the present invention shall be subject to the appended claims.

Claims

1. A method for analyzing the refractive uniformity of the visual field in a close working environment, characterized in that: include: Obtain a depth image of the target environment captured by a depth camera; Convert the depth value of each pixel in the depth image into a depth value from the eye; wherein the equivalent position of the depth camera, the equivalent position of the human eye, and the gaze point of the human eye in the target environment are located on the same straight line; The depth value of each pixel from the eye is converted into diopter to obtain a diopter map of the target environment; Determine a defocus value of each pixel in the refractive index map according to the refractive index of the pixel corresponding to the gaze point and the refractive index of the remaining pixels in the refractive index map to obtain a defocus map of the target environment; Obtaining a defocus map of the field of view area in the defocus map of the target environment as a first defocus map of the field of view area; wherein the field of view area is centered on the gaze point; The defocus value of each pixel in the first defocus map is two-dimensionally integrated to obtain a second defocus map of the visual field area to determine the refractive uniformity of the visual field area.

2. The method for analyzing the uniformity of refractive index of a visual field according to claim 1, characterized in that: The step of converting the depth value of each pixel in the depth image into a distance-to-eye depth value comprises: Convert the pixel coordinates of each pixel in the depth image into three-dimensional coordinates; where the gaze point coordinates in the three-dimensional coordinate system are (x0, y0, z0), and the equivalent position coordinates of the depth camera are (x0, y0, 0); Determine the angle between the line from the depth camera to each pixel in the depth image and the line from the depth camera to the gaze point in the three-dimensional coordinate system; Convert the angle between the line connecting the depth camera to each pixel in the depth image and the line connecting the depth camera to the gaze point into radians; The depth value of each pixel from the eye is calculated according to the following formula: Where h is the depth value of the target pixel in the depth image from the eye; d is the distance between the depth camera lens and the human eye; k is the depth value of the target pixel in the depth image measured by the depth camera; α rad The angle between the line from the depth camera to the target pixel in the depth image and the line from the depth camera to the gaze point corresponds to the radian.

3. The method for analyzing the uniformity of refractive power of a visual field according to claim 1, characterized in that: The method of determining the defocus value of each pixel in the refractive index map according to the refractive index of the pixel corresponding to the gaze point and the refractive index of the remaining pixels in the refractive index map to obtain a defocus map of the target environment includes: Obtaining the diopter of each pixel in the diopter map of the target environment; The difference between the diopter of the target pixel and the diopter of the fixation point is taken as the defocus value of the target pixel; The diopter map is mapped into a color image according to the defocus value of each pixel in the diopter map to obtain a defocus map of the target environment.

4. The method for analyzing the refractive uniformity of the visual field according to claim 1, characterized in that: The step of performing two-dimensional integration on the defocus value of each pixel in the first defocus map to obtain a second defocus map of the visual field area to determine the refractive uniformity of the visual field area includes: The defocus value of each pixel in the first defocus map is integrated in two dimensions according to the following formula: S = ∫∫|ΔD|dx1dy1; Wherein, S is the two-dimensional integral value of the defocus value ΔD of the target pixel in the first defocus image; (x1, y1) is the coordinate of the target pixel in the first defocus image.

5. A visual field refractive uniformity analysis system for a close working environment, characterized in that: include: A first acquisition module is used to acquire a depth image of a target environment captured by a depth camera; A first conversion module, configured to convert a depth value of each pixel in the depth image into a depth value from an eye; wherein the equivalent position of the depth camera, the equivalent position of the human eye, and the gaze point of the human eye in the target environment are located on the same straight line; A second conversion module is used to convert the depth value of each pixel from the eye into diopter to obtain a diopter map of the target environment; A determination module, used to determine the defocus value of each pixel in the refractive index map according to the refractive index of the pixel corresponding to the gaze point and the refractive index of the remaining pixels in the refractive index map, so as to obtain a defocus map of the target environment; A second acquisition module is used to acquire a defocus map of a visual field area in a defocus map of a target environment as a first defocus map of the visual field area; wherein the visual field area is centered on the gaze point; The integration module is used to perform two-dimensional integration on the defocus value of each pixel in the first defocus map to obtain a second defocus map of the visual field area to determine the refractive uniformity of the visual field area.

6. The visual field refractive uniformity analysis system according to claim 5, characterized in that: The first conversion module comprises: A first conversion unit is used to convert the pixel coordinates of each pixel in the depth image into three-dimensional coordinates; wherein the coordinates of the gaze point in the three-dimensional coordinate system are (x0, y0, z0), and the equivalent position coordinates of the depth camera are (x0, y0, 0); A first determining unit, configured to determine, in a three-dimensional coordinate system, an angle between a line connecting the depth camera to each pixel in the depth image and a line connecting the depth camera to a gaze point; A second conversion unit, configured to convert an angle between a line connecting the depth camera to each pixel in the depth image and a line connecting the depth camera to the gaze point into radians; The first calculation unit is used to calculate the distance from the eye value of each pixel according to the following formula: Where h is the depth value of the target pixel in the depth image from the eye; d is the distance between the depth camera lens and the human eye; k is the depth value of the target pixel in the depth image measured by the depth camera; α rad The angle between the line from the depth camera to the target pixel in the depth image and the line from the depth camera to the gaze point corresponds to the radian.

7. The visual field refractive uniformity analysis system according to claim 5, characterized in that: The determination module comprises: An acquisition unit, used for acquiring the diopter of each pixel in the diopter map of the target environment; A second determining unit, configured to use a difference between the diopter of the target pixel and the diopter of the gaze point as a defocus value of the target pixel; The mapping unit is used to map the diopter map into a color image according to the defocus value of each pixel in the diopter map to obtain a defocus map of the target environment.

8. The visual field refractive uniformity analysis system according to claim 5, characterized in that: The integration module comprises: The second calculation unit is used to perform a two-dimensional integration of the defocus value of each pixel in the first defocus map according to the following formula: S = ∫∫|ΔD|dx1dy1; Wherein, S is the two-dimensional integral value of the defocus value ΔD of the target pixel in the first defocus image; (x1, y1) is the coordinate of the target pixel in the first defocus image.

9. A computer device, characterized in that: It comprises a processor and a memory; wherein, when the processor executes the computer program stored in the memory, the steps of the method for analyzing the refractive uniformity of the visual field in a close-range working environment described in any one of claims 1 to 4 are implemented.

10. A computer-readable storage medium, characterized in that: Used to store computer programs; when the computer programs are executed by a processor, the steps of the method for analyzing the refractive uniformity of the visual field in a close-range working environment according to any one of claims 1 to 4 are implemented.

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