Optimal object distance detection method, system and device, electronic equipment and storage medium

Abstract

The invention discloses an optimal object distance detection method, system and device, electronic equipment and a storage medium, and relates to the technical field of VR products, and the disclosed optimal object distance detection method comprises the steps: obtaining first images generated by a light source target under different image distances, and determining a first target image in each first image, the first image is an image generated when the light source target penetrates through the to-be-detected VR product; after it is detected that the optical reticle is placed, second images generated by the optical reticle under different image distances are obtained, a second target image is determined in the second images, and the second images are images generated when the light source target penetrates through the to-be-detected VR product and the optical reticle; and calculating the actual optimal object distance of the to-be-measured VR product according to the image distances corresponding to the first target image and the second target image and the distance between the optical reticle and the to-be-measured VR product. The technical scheme of the invention aims to solve the technical problem of how to measure the actual optimal object distance of the VR product.

Description

Technical Field

[0001] The present application relates to the field of VR product technology, and in particular to an optimal object distance detection method, system, device, electronic device and storage medium. Background Art

[0002] In the production process of VR (Virtual Reality) products, screen calibration and assembly are key steps. However, usually, errors will occur during the calibration and assembly process of the screen, resulting in the inability to clearly image the assembled VR product even at the set optimal object distance.

[0003] Nowadays, VR products can be imaged clearly by compensating for the object distance. Specifically, for a batch of VR products, the object distance can be compensated by 0.1% to 1%, and then the compensated object distance with the clearest imaging can be selected as the target object distance to compensate for the object distance of all VR products. However, the errors corresponding to different VR products are different. Therefore, the traditional method of compensating for the target object distance is difficult to adapt to all VR products, and it is also difficult to make all VR products have clear images.

[0004] Therefore, how to measure the actual optimal object distance of the VR product to compensate for the actual optimal object distance of the VR product is a technical problem that needs to be solved by those skilled in the art. Summary of the invention

[0005] The main purpose of this application is to provide an optimal object distance detection method, system, device, electronic device and storage medium, aiming to solve the technical problem of how to measure the actual optimal object distance of VR products.

[0006] To achieve the above objectives, the present application proposes an optimal object distance detection method, which includes:

[0007] Acquire first images respectively generated by the light source target at different image distances, and determine a first target image in each of the first images according to the clarity corresponding to each of the first images, wherein the first image is an image generated by the light source target through the VR product to be tested;

[0008] After detecting that the optical graticule is placed, obtaining second images respectively generated by the optical graticule at different image distances, and determining a second target image in each second image according to the clarity corresponding to each second image, wherein the second image is an image generated by the light source target through the VR product to be tested and the optical graticule;

[0009] The actual optimal object distance of the VR product to be tested is calculated according to the image distances corresponding to the first target image and the second target image, respectively, and the distance between the optical graticule and the VR product to be tested.

[0010] In one embodiment, the step of calculating the actual optimal object distance of the VR product to be tested according to the image distances corresponding to the first target image and the second target image, and the distance between the optical graticule and the VR product to be tested, comprises:

[0011] Calculating a difference between an image distance corresponding to the first target image and an image distance corresponding to the second target image;

[0012] The distance between the optical graticule and the VR product to be tested is added to the difference to obtain the actual optimal object distance of the VR product to be tested.

[0013] In one embodiment, the method further comprises:

[0014] Acquire optical simulation data of the VR product to be tested, and determine a set object distance corresponding to the VR product to be tested based on the optical simulation data;

[0015] When it is detected that the distance between the VR product to be tested and the preset light source target is equal to the set object distance, the step of acquiring the first images generated by the light source target at different image distances is executed, and determining the first target image in each of the first images according to the clarity corresponding to each of the first images.

[0016] In one embodiment, the step of acquiring the second images respectively generated by the optical graticule at different image distances comprises:

[0017] Obtaining the distance between the optical graticule and the VR product to be tested;

[0018] When it is detected that the distance is within a preset distance range, second images respectively generated by the optical graticule at different image distances are acquired.

[0019] In one embodiment, the step of determining the first target image in each of the first images according to the clarity corresponding to each of the first images comprises:

[0020] Calculating first definitions corresponding to the first images, and taking a first image corresponding to the highest definition among the first definitions as a first target image;

[0021] The step of determining the second target image in each of the second images according to the clarity corresponding to each of the second images comprises:

[0022] The second definition corresponding to each of the second images is calculated, and the second image corresponding to the highest definition among the second definitions is used as the second target image.

[0023] In one embodiment, after the step of calculating the actual optimal object distance of the VR product to be tested according to the image distances corresponding to the first target image and the second target image, and the distance between the optical graticule and the VR product to be tested, the method further includes:

[0024] Determining whether the actual optimal object distance is within a preset object distance range;

[0025] If it is determined that the actual optimal object distance is within the object distance range, determining a middle value of the object distance range, and determining the thickness to be compensated based on a difference between the middle value and the actual optimal object distance;

[0026] If it is determined that the actual optimal object distance is not within the object distance range, the VR product to be tested is regarded as a defective product, and prompt information is output based on the defective product.

[0027] In addition, to achieve the above-mentioned purpose, the present application also proposes an optimal object distance detection system, the optimal object distance detection system comprising:

[0028] A first image processing module, used to obtain first images respectively generated by the light source target at different image distances, and determine a first target image in each of the first images according to the clarity corresponding to each of the first images, wherein the first image is an image generated by the light source target through the VR product to be tested;

[0029] A second image processing module is used to obtain second images respectively generated by the optical graticule at different image distances after detecting that the optical graticule is placed, and determine a second target image in each of the second images according to the clarity corresponding to each of the second images, wherein the second image is an image generated by the light source target through the VR product to be tested and the optical graticule;

[0030] The object distance calculation module is used to calculate the actual optimal object distance of the VR product to be tested according to the image distances corresponding to the first target image and the second target image, and the distance between the optical graticule and the VR product to be tested.

[0031] In addition, to achieve the above-mentioned purpose, the present application also proposes an optimal object distance detection device, which includes a slide rail and a light source target, a first load-bearing tooling, a second load-bearing tooling and an image acquisition device sequentially arranged on the slide rail;

[0032] The light source target is used to output the light source required for detecting the optimal object distance;

[0033] The first carrying fixture is used to carry the VR product to be tested;

[0034] The second carrying fixture is used for carrying the optical graticule;

[0035] The image acquisition device is used to obtain first images generated by the light source target at different image distances, and after detecting that the optical graticule is placed, obtain second images generated by the optical graticule at different image distances; it is also used to determine the first target image in each of the first images according to the clarity corresponding to each of the first images, and to determine the second target image in each of the second images according to the clarity corresponding to each of the second images; it is also used to calculate the actual optimal object distance of the VR product to be tested according to the image distances corresponding to the first target image and the second target image, and the distance between the optical graticule and the VR product to be tested.

[0036] In addition, to achieve the above-mentioned purpose, the present application also proposes an electronic device, which includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the optimal object distance detection method as described above.

[0037] In addition, to achieve the above-mentioned purpose, the present application also proposes a storage medium, which is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the optimal object distance detection method as described above are implemented.

[0038] In the embodiment of the present application, by acquiring first images respectively generated by the light source target at different image distances, and determining a first target image in each first image according to the clarity corresponding to each first image, the first image is an image generated by the light source target through the VR product to be tested; after detecting that the optical grating plate is placed, acquiring second images respectively generated by the optical grating plate at different image distances, and determining a second target image in each second image according to the clarity corresponding to each second image, the second image is an image generated by the light source target through the VR product to be tested and the optical grating plate, and the optical grating plate can be respectively present when there is no optical grating plate and when there is an optical grating plate. On the premise of , images corresponding to different image distances are obtained; then the clearest first target image and the clearest second target image can be determined based on the clarity standard; then the actual optimal object distance of the VR product to be tested is calculated according to the image distances corresponding to the first target image and the second target image, as well as the distance between the optical graticule and the VR product to be tested. The distance moved for clear imaging can be determined based on the difference between the image distance corresponding to the first target image and the image distance corresponding to the second target image, and the actual optimal object distance of the VR product to be tested can be determined according to the moved distance and the distance between the optical graticule and the VR product to be tested.

[0039] This application is based on the object-image conjugation principle, and exchanges the object plane and the image plane while keeping the conjugate distance unchanged, so that the image plane of the light source target and the optical graticule can be used as the object plane of the VR product to be tested. Furthermore, this application obtains the object distance at which the VR product to be tested can be clearly imaged under different conditions by respectively determining the first target image and the second target image under the conditions of the absence and presence of an optical graticule. Therefore, the actual optimal object distance of the VR product can be indirectly calculated based on the object distance at which the image is clearly imaged when there is no optical graticule, the object distance at which the image is clearly imaged when there is an optical graticule, and the distance between the optical graticule and the VR product to be tested. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0041] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0042] Figure 1 This is a schematic diagram of the overall device of the optimal object distance detection device of the present application;

[0043] Figure 2A schematic diagram of the device for acquiring a first image of the optimal object distance detection device of the present application;

[0044] Figure 3 A schematic diagram of an optical graticule in the optimal object distance detection device of the present application;

[0045] Figure 4 A schematic diagram of a flow chart provided for the first embodiment of the optimal object distance detection method of the present application;

[0046] Figure 5 This is a schematic diagram of the module structure of the optimal object distance detection system according to an embodiment of the present application;

[0047] Figure 6 Schematic diagram of the device structure of the hardware operating environment involved in the optimal object distance detection method in the embodiment of the present application.

[0048] Description of Figure Numbers:

[0049] 100: slide rail; 200: light source target; 300: first load-bearing tooling; 400: second load-bearing tooling; 500: image acquisition device.

[0050] The purpose, features and advantages of this application will be further described in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0051] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.

[0052] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0053] In the production process of VR products, screen calibration and assembly are key steps. However, usually, errors will occur during the calibration and assembly process, resulting in the inability to clearly image the assembled VR product even at the set optimal object distance.

[0054] Nowadays, VR products can be imaged clearly by compensating for the object distance. Specifically, for a batch of VR products, the object distance can be compensated by 0.1% to 1%, and then the compensated object distance with the clearest imaging can be selected as the target object distance to compensate for the object distance of all VR products. However, the errors corresponding to different VR products are different. Therefore, the traditional method of compensating for the target object distance is difficult to adapt to all VR products, and it is also difficult to make all VR products have clear images.

[0055] Therefore, how to measure the actual optimal object distance of the VR product to compensate for the actual optimal object distance of the VR product is a technical problem that needs to be solved by those skilled in the art.

[0056] In order to solve the above problems, the present application obtains first images respectively generated by the light source target at different image distances, and determines a first target image in each first image according to the clarity corresponding to each first image, wherein the first image is an image generated by the light source target through the VR product to be tested; after detecting that the optical grating plate is placed, obtains second images respectively generated by the optical grating plate at different image distances, and determines a second target image in each second image according to the clarity corresponding to each second image, wherein the second image is an image generated by the light source target through the VR product to be tested and the optical grating plate, and the second image can be respectively obtained when there is no optical grating plate and when there is an optical grating plate. Based on the premise of using the optical graticule, images corresponding to different image distances can be obtained; then the clearest first target image and the clearest second target image can be determined based on the clarity standard; then the actual optimal object distance of the VR product to be tested is calculated according to the image distances corresponding to the first target image and the second target image, and the distance between the optical graticule and the VR product to be tested, and the distance moved for clear imaging can be determined based on the difference between the image distance corresponding to the first target image and the image distance corresponding to the second target image, and then the actual optimal object distance of the VR product to be tested can be determined according to the moved distance and the distance between the optical graticule and the VR product to be tested.

[0057] This application is based on the object-image conjugation principle, and exchanges the object plane and the image plane while keeping the conjugate distance unchanged, so that the image plane of the light source target and the optical graticule can be used as the object plane of the VR product to be tested. Furthermore, this application obtains the object distance at which the VR product to be tested can be clearly imaged under different conditions by respectively determining the first target image and the second target image under the conditions of the absence and presence of an optical graticule. Therefore, the actual optimal object distance of the VR product can be indirectly calculated based on the object distance at which the image is clearly imaged when there is no optical graticule, the object distance at which the image is clearly imaged when there is an optical graticule, and the distance between the optical graticule and the VR product to be tested.

[0058] Please refer to Figure 1 , Figure 1 The schematic diagram of the optimal object distance detection device of the present application is as follows. The optimal object distance detection device includes: a slide rail 100 and a light source target 200, a first load-bearing fixture 300, a second load-bearing fixture 400 and an image acquisition device 500 sequentially arranged on the slide rail 100;

[0059] The light source target 200 is used to output the light source required for detecting the optimal object distance;

[0060] The first carrying fixture 300 is used to carry the VR product to be tested;

[0061] The second carrying fixture 400 is used for carrying the optical graticule;

[0062] The image acquisition device 500 is used to obtain the first images generated by the light source target 200 at different image distances, and after detecting that the optical graticule is placed, obtain the second images generated by the optical graticule at different image distances; it is also used to determine the first target image in each of the first images according to the clarity corresponding to each of the first images, and to determine the second target image in each of the second images according to the clarity corresponding to each of the second images; it is also used to calculate the actual optimal object distance of the VR product to be tested according to the image distances corresponding to the first target image and the second target image, and the distance between the optical graticule and the VR product to be tested.

[0063] It is understandable that the above-mentioned image acquisition device has the general data processing function of a processor, so the image acquisition device in the above-mentioned optimal object distance detection device can process the image and calculate the actual optimal object distance. In a feasible implementation, the above-mentioned image acquisition device can also be connected to an external processor or computer, and the steps of the optimal object distance detection method of the present application are executed by the processor or computer.

[0064] Furthermore, the schematic diagram of the optimal object distance detection device when acquiring the first image is as follows: Figure 2 As shown. Among them, Figure 2 and Figure 1 In contrast, no optical graticule is provided. In this embodiment, the distance between the light source target and the VR product to be tested is fixed, the image acquisition device can move on the slide rail, and, during the movement of the image acquisition device, an image will be captured and the distance (image distance) between the image acquisition device and the VR product to be tested when the image is captured will be saved.

[0065] Further, in a feasible implementation manner, the schematic diagram of the optical graticule is as follows: Figure 3 It should be noted that in other scenarios with the ability to measure the optimal object distance, the specific pattern of the optical graticule can be set according to demand, and this application does not limit this.

[0066] It should be noted that the execution subject of the optimal object distance detection method of the present application can be an electronic device with data processing, network communication and program running functions, such as a processor, a computer, an image acquisition device, etc. The following takes an image acquisition device as an example to illustrate various embodiments of the optimal object distance detection method of the present application.

[0067] Based on the optimal object distance detection device proposed above, the present application embodiment provides an optimal object distance detection method, referring to Figure 4 , Figure 4 Schematic diagram of the flow chart of the first embodiment of the optimal object distance detection method of the present application.

[0068] In this embodiment, the optimal object distance detection method includes steps S10 to S30:

[0069] Step S10, obtaining first images respectively generated by the light source target at different image distances, and determining a first target image in each of the first images according to the clarity corresponding to each of the first images, wherein the first image is an image generated by the light source target through the VR product to be tested;

[0070] Step S20, after detecting that the optical graticule is placed, obtaining second images respectively generated by the optical graticule at different image distances, and determining a second target image in each of the second images according to the clarity corresponding to each of the second images, wherein the second image is an image generated by the light source target through the VR product to be tested and the optical graticule;

[0071] In this embodiment, the light source target will emit parallel light, and the parallel light can form an image on the image acquisition device after passing through the VR product to be tested. The image acquisition device can move on the slide rail, so that images with different image distances can be obtained without the presence of an optical graticule. That is, each first image is obtained. Further, after each first image is obtained, an optical graticule can be placed on the second carrying tooling between the VR product to be tested and the image acquisition device, and then the image acquisition device still moves on the slide rail and takes images, so that each second image can be obtained.

[0072] It is understandable that the range of movement of the image acquisition device on the slide rail can be preset, and the present application does not limit the range of movement of the image acquisition device on the slide rail.

[0073] It is understandable that the purpose of measuring the optimal object distance in this application is to allow VR products to have clear images. Therefore, after obtaining each image, the clarity of each image needs to be evaluated in order to determine the clearest image.

[0074] Therefore, for each first image and each second image, the clarity corresponding to each image can be evaluated respectively, and then the first target image can be determined in each first image according to the clarity, and the second target image can be determined in each second image according to the clarity.

[0075] In a feasible implementation manner, the above step S10 may include:

[0076] Step S101, calculating the first definition corresponding to each of the first images, and taking the first image corresponding to the highest definition among the first definitions as the first target image;

[0077] The above step S20 may include:

[0078] Step S201 : calculating the second definition corresponding to each of the second images, and taking the second image corresponding to the highest definition among the second definitions as the second target image.

[0079] It should be noted that the first clarity refers to the clarity corresponding to the first image, and the second clarity refers to the clarity corresponding to the second image. The clarity can be determined by light intensity or by a Laplace operator, and the present application does not limit the calculation method of the clarity.

[0080] In this embodiment, the present application determines the clearest image under different conditions by definition, so as to facilitate the subsequent calculation of the actual optimal object distance according to the image distances corresponding to the clearest images under different conditions.

[0081] Step S30, calculating the actual optimal object distance of the VR product to be tested according to the image distances corresponding to the first target image and the second target image, respectively, and the distance between the optical graticule and the VR product to be tested.

[0082] It can be understood that the first target image is obtained under the premise that there is no optical grating plate, so the image distance corresponding to the first target image is usually greater than the image distance corresponding to the second target image. That is to say, after adding the optical grating plate, the image acquisition device needs to move in the direction biased towards the VR product to be tested, so that the optical grating plate can be clearly imaged under the premise that the optical grating plate exists. Therefore, according to the image distance corresponding to the first target image and the image distance corresponding to the second target image, the distance moved by the image acquisition device can be determined. Then, since the light between the VR product to be tested and the optical grating plate is still parallel light, the distance between the VR product to be tested and the optical grating plate is actually also part of the object distance of the VR product to be tested. Therefore, the actual optimal object distance of the VR product to be tested can be calculated based on the distance moved by the image acquisition device and the distance between the VR product to be tested and the optical grating plate.

[0083] In a feasible implementation manner, the above step S30 includes:

[0084] Step S301, calculating the difference between the image distance corresponding to the first target image and the image distance corresponding to the second target image;

[0085] It can be understood that the difference value can represent the distance that the image acquisition device moves on the slide rail in a scenario where the first target image is converted into the second target image.

[0086] Step S302, adding the distance between the optical graticule and the VR product to be tested to the difference value to obtain the actual optimal object distance of the VR product to be tested.

[0087] Exemplarily, when the image distance corresponding to the first target image is d1, the image distance corresponding to the second target image is d2, and the distance between the optical graticule and the VR product to be tested is s, the expression of the actual optimal object distance of the VR product to be tested is: d1-d2+s.

[0088] In the embodiment of the present application, by acquiring first images respectively generated by the light source target at different image distances, and determining a first target image in each first image according to the clarity corresponding to each first image, the first image is an image generated by the light source target through the VR product to be tested; after detecting that the optical grating plate is placed, acquiring second images respectively generated by the optical grating plate at different image distances, and determining a second target image in each second image according to the clarity corresponding to each second image, the second image is an image generated by the light source target through the VR product to be tested and the optical grating plate, and the optical grating plate can be respectively present when there is no optical grating plate and when there is an optical grating plate. On the premise of , images corresponding to different image distances are obtained; then the clearest first target image and the clearest second target image can be determined based on the clarity standard; then the actual optimal object distance of the VR product to be tested is calculated according to the image distances corresponding to the first target image and the second target image, as well as the distance between the optical graticule and the VR product to be tested. The distance moved for clear imaging can be determined based on the difference between the image distance corresponding to the first target image and the image distance corresponding to the second target image, and the actual optimal object distance of the VR product to be tested can be determined according to the moved distance and the distance between the optical graticule and the VR product to be tested.

[0089] The present application is based on the object-image conjugation principle, and exchanges the object plane and the image plane while keeping the conjugate distance unchanged, so that the image plane of the light source target and the optical graticule can be used as the object plane of the VR product to be tested. Furthermore, the present application obtains the object distance at which the VR product to be tested can be clearly imaged under different conditions by respectively determining the first target image and the second target image under the conditions of the absence and presence of the optical graticule. Thus, the actual optimal object distance of the VR product can be indirectly calculated based on the object distance at which the image is clearly imaged when there is no optical graticule, the object distance at which the image is clearly imaged when there is an optical graticule, and the distance between the optical graticule and the VR product to be tested.

[0090] Further, based on the above-mentioned first embodiment of the optimal object distance detection method of the present application, a second embodiment of the optimal object distance detection method of the present application is proposed. In this embodiment, the method further includes:

[0091] Step S100, obtaining optical simulation data of the VR product to be tested, and determining a set object distance corresponding to the VR product to be tested based on the optical simulation data;

[0092] It should be noted that optical simulation data includes various types, such as ray tracing data, beam propagation data, optical characteristic parameter data, etc. The set object distance is the distance between the light source target and the VR product to be tested, under the premise that the light emitted by the light source target can form a clear and accurate virtual image in front of the user's eyes after passing through the VR product to be tested. The set object distance can be directly determined through optical simulation data, and this application will not be repeated here.

[0093] Step S200, when it is detected that the distance between the VR product to be tested and the preset light source target is equal to the set object distance, execute the step of acquiring the first images generated by the light source target at different image distances, and determining the first target image in each of the first images according to the clarity corresponding to each of the first images.

[0094] It is understandable that the set object distances corresponding to different VR products to be tested may be different. Therefore, when detecting the actual optimal object distance, it is necessary to detect whether the distance between the current VR product to be tested and the light source target is equal to the corresponding set object distance. If they are equal, the subsequent steps of calculating the optimal object distance can be performed.

[0095] In the present application, before measuring the actual optimal object distance, the accuracy of the actual optimal object distance measurement is ensured by comparing the set object distance of the current VR product to be tested and the distance between the VR product to be tested and the light source target, thereby avoiding the technical problem of errors in the optimal object distance measurement caused by distance mismatch.

[0096] Furthermore, based on the above-mentioned first embodiment and / or second embodiment of the optimal object distance detection method of the present application, a third embodiment of the optimal object distance detection method of the present application is proposed.

[0097] In this embodiment, the above step S10 includes:

[0098] Step S102, obtaining the distance between the optical graticule and the VR product to be tested;

[0099] Step S103, when it is detected that the distance is within a preset distance range, obtaining second images respectively generated by the optical graticule at different image distances.

[0100] It is understandable that a distance measuring sensor may be pre-set on a tooling that carries the optical graticule or the VR product to be tested, so that the distance between the optical graticule and the VR product to be tested may be conveniently obtained based on the distance measuring sensor.

[0101] The above-mentioned preset distance range refers to the distance interval used to limit the position of the optical graticule. Specifically, assuming that the distance range is [1cm, 3cm], the distance between the optical graticule and the VR product to be tested should be guaranteed to be within the interval of [1cm, 3cm].

[0102] It should be noted that if the position of the optical graticule exceeds the distance range, there is a problem that the image acquisition device cannot clearly image no matter how it is moved. Therefore, in order to avoid this problem, after detecting that the placement of the optical graticule is completed, the present application can judge the compliance of the position of the optical graticule by the distance range to reduce the probability of error in the actual optimal object distance measurement.

[0103] Furthermore, based on the above-mentioned embodiments of the optimal object distance detection method of the present application, a fourth embodiment of the optimal object distance detection method of the present application is proposed.

[0104] In this embodiment, after the above step S30, the method further includes:

[0105] Step S40, determining whether the actual optimal object distance is within a preset object distance range;

[0106] It is understandable that after obtaining the actual optimal object distance of the VR product, in order to facilitate clear imaging for each VR product, it is possible to determine whether the actual optimal object distance is within the object distance range, so as to determine whether the object distance at which the VR product can clearly image can be increased from the actual optimal object distance to the optimal imaging object distance set when the VR product leaves the factory by thickening the pressure-sensitive adhesive or thinning the pressure-sensitive adhesive.

[0107] In a feasible implementation, the object distance range may be determined according to the object distance for optimal imaging set when the VR product leaves the factory. For example, when the object distance for optimal imaging set when the VR product leaves the factory is R, the object distance range may be [R-10%R, R+10%R].

[0108] Step S50, if it is determined that the actual optimal object distance is within the object distance range, determining a middle value of the object distance range, and determining a thickness to be compensated based on a difference between the middle value and the actual optimal object distance;

[0109] It should be noted that the thickness to be compensated refers to the thickness of the pressure-sensitive adhesive being thickened or thinned.

[0110] In this embodiment, the middle value of the object distance range can be used as a standard to determine the thickness that needs to be compensated for the actual optimal object distance. Thus, the object distance can be compensated based on the pressure-sensitive adhesive corresponding to the thickness to be compensated.

[0111] Step S60: If it is determined that the actual optimal object distance is not within the object distance range, the VR product to be tested is regarded as a defective product, and prompt information is output based on the defective product.

[0112] It is understandable that if it is detected that the actual optimal object distance is not within the object distance range, it means that it is difficult or takes a long time to compensate for the actual optimal object distance. Therefore, VR products whose actual optimal object distance is not within the object distance range can be regarded as defective products, and the identification, type number and other information of the defective product can be output to prompt the user.

[0113] In this embodiment, the present application can quickly determine whether the current VR product meets the requirements of object distance compensation by means of numerical comparison by determining whether the actual optimal object distance is within a preset object distance range, thereby facilitating rapid screening of VR products that meet the requirements of object distance compensation, thereby improving the efficiency of object distance compensation of VR products.

[0114] It should be noted that the above examples are only used to understand the present application and do not constitute a limitation on the optimal object distance detection method of the present application. More simple transformations based on this technical concept are all within the protection scope of the present application.

[0115] This application also provides an optimal object distance detection system, please refer to Figure 5 , the optimal object distance detection system comprises:

[0116] The first image processing module 10 is used to obtain first images respectively generated by the light source target at different image distances, and determine a first target image in each of the first images according to the clarity corresponding to each of the first images, wherein the first image is an image generated by the light source target through the VR product to be tested;

[0117] The second image processing module 20 is used to obtain second images respectively generated by the optical graticule at different image distances after detecting that the optical graticule is placed, and determine a second target image in each of the second images according to the clarity corresponding to each of the second images, wherein the second image is an image generated by the light source target through the VR product to be tested and the optical graticule;

[0118] The object distance calculation module 30 is used to calculate the actual optimal object distance of the VR product to be tested according to the image distances corresponding to the first target image and the second target image, and the distance between the optical graticule and the VR product to be tested.

[0119] In one embodiment, the object distance calculation module 30 is further used for:

[0120] Calculating a difference between an image distance corresponding to the first target image and an image distance corresponding to the second target image;

[0121] The distance between the optical graticule and the VR product to be tested is added to the difference to obtain the actual optimal object distance of the VR product to be tested.

[0122] In one embodiment, the optimal object distance detection system further includes:

[0123] An object distance detection module, used to obtain optical simulation data of the VR product to be tested, and determine a set object distance corresponding to the VR product to be tested based on the optical simulation data;

[0124] The adapter module is used to execute the steps of acquiring the first images generated by the light source target at different image distances when it is detected that the distance between the VR product to be tested and the preset light source target is equal to the set object distance, and determining the first target image in each of the first images according to the clarity corresponding to each of the first images.

[0125] In one embodiment, the first image processing module 10 is further configured to:

[0126] Obtaining the distance between the optical graticule and the VR product to be tested;

[0127] When it is detected that the distance is within a preset distance range, second images respectively generated by the optical graticule at different image distances are acquired.

[0128] In one embodiment, the first image processing module 10 is further configured to:

[0129] Calculating first definitions corresponding to the first images, and taking a first image corresponding to the highest definition among the first definitions as a first target image;

[0130] In one embodiment, the second image processing module 20 is further configured to:

[0131] The second definition corresponding to each of the second images is calculated, and the second image corresponding to the highest definition among the second definitions is used as the second target image.

[0132] In one embodiment, the optimal object distance detection system further includes:

[0133] An object distance compensation detection module, used to determine whether the actual optimal object distance is within a preset object distance range;

[0134] a thickness determination module, configured to determine a middle value of the object distance range if it is determined that the actual optimal object distance is within the object distance range, and determine a thickness to be compensated based on a difference between the middle value and the actual optimal object distance;

[0135] The defective product determination module is used to treat the VR product to be tested as a defective product if it is determined that the actual optimal object distance is not within the object distance range, and output prompt information based on the defective product.

[0136] The optimal object distance detection system provided by the present application adopts the optimal object distance detection method in the above embodiment, which can solve the technical problem of how to measure the actual optimal object distance of VR products. Compared with the prior art, the beneficial effects of the optimal object distance detection system provided by the present application are the same as the beneficial effects of the optimal object distance detection method provided by the above embodiment, and other technical features of the optimal object distance detection system are the same as the features disclosed in the above embodiment method, which will not be repeated here.

[0137] The present application provides an electronic device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the optimal object distance detection method in the above-mentioned embodiment 1.

[0138] Reference below Figure 6 , which shows a schematic diagram of the structure of an electronic device suitable for implementing an embodiment of the present application. Figure 6 The electronic device shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0139] like Figure 6As shown, the electronic device may include a processing device 1001 (e.g., a central processing unit, a graphics processor, etc.), which may perform various appropriate actions and processes according to a program stored in a read-only memory (ROM: Read Only Memory) 1002 or a program loaded from a storage device 1003 to a random access memory (RAM: Random Access Memory) 1004. In RAM1004, various programs and data required for the operation of the electronic device are also stored. The processing device 1001, ROM1002, and RAM1004 are connected to each other via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Generally, the following systems may be connected to the I / O interface 1006: an input device 1007 including, for example, a touch screen, a touch pad, an image sensor, etc.; an output device 1008 including, for example, a liquid crystal display (LCD: Liquid Crystal Display); a storage device 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009. The communication device 1009 may allow the electronic device to communicate with other devices wirelessly or by wire to exchange data. Although the electronic device with various systems is shown in the figure, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems can be implemented or have instead.

[0140] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0141] The electronic device provided by the present application adopts the optimal object distance detection method in the above embodiment, which can solve the technical problem of how to measure the actual optimal object distance of VR products. Compared with the prior art, the beneficial effects of the electronic device provided by the present application are the same as the beneficial effects of the optimal object distance detection method provided by the above embodiment, and the other technical features in the electronic device are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0142] It should be understood that the various parts disclosed in this application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0143] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0144] The present application provides a computer-readable storage medium having computer-readable program instructions (ie, computer programs) stored thereon, and the computer-readable program instructions are used to execute the optimal object distance detection method in the above-mentioned embodiment.

[0145] The computer-readable storage medium provided in the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, systems or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, 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 above. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination of the above.

[0146] The computer-readable storage medium may be included in the electronic device, or may exist independently without being installed in the electronic device.

[0147] The computer-readable storage medium carries one or more programs. When the one or more programs are executed by the electronic device, the electronic device: obtains first images generated by the light source target at different image distances, and determines a first target image in each first image according to the clarity corresponding to each first image; the first image is an image generated by the light source target through the VR product to be tested; after detecting that the optical graticule is placed, obtains second images generated by the optical graticule at different image distances, and determines a second target image in each second image according to the clarity corresponding to each second image; the second image is an image generated by the light source target through the VR product to be tested and the optical graticule; calculates the actual optimal object distance of the VR product to be tested according to the image distances corresponding to the first target image and the second target image, and the distance between the optical graticule and the VR product to be tested.

[0148] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate 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 may 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 may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0149] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0150] The modules involved in the embodiments described in this application may be implemented by software or hardware, wherein the name of the module does not constitute a limitation on the unit itself in some cases.

[0151] The readable storage medium provided in this application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned optimal object distance detection method, and can solve the technical problem of how to measure the actual optimal object distance of VR products. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as the beneficial effects of the optimal object distance detection method provided in the above-mentioned embodiment, and will not be repeated here.

[0152] The present application also provides a computer program product, including a computer program, which implements the steps of the optimal object distance detection method as described above when the computer program is executed by a processor.

[0153] The computer program product provided in this application can solve the technical problem of how to measure the actual optimal object distance of VR products. Compared with the prior art, the beneficial effects of the computer program product provided in this application are the same as the beneficial effects of the optimal object distance detection method provided in the above embodiment, which will not be repeated here.

[0154] The above descriptions are only some embodiments of the present application, and are not intended to limit the patent scope of the present application. All equivalent structural changes made using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect applications in other related technical fields are included in the patent protection scope of the present application.

Claims

1. An optimal object distance detection method, characterized in that: The optimal object distance detection method comprises: Acquire first images respectively generated by the light source target at different image distances, and determine a first target image in each of the first images according to the clarity corresponding to each of the first images, wherein the first image is an image generated by the light source target through the VR product to be tested; After detecting that the optical graticule is placed, obtaining second images respectively generated by the optical graticule at different image distances, and determining a second target image in each second image according to the clarity corresponding to each second image, wherein the second image is an image generated by the light source target through the VR product to be tested and the optical graticule; The actual optimal object distance of the VR product to be tested is calculated according to the image distances corresponding to the first target image and the second target image, respectively, and the distance between the optical graticule and the VR product to be tested.

2. The optimal object distance detection method according to claim 1, characterized in that: The step of calculating the actual optimal object distance of the VR product to be tested according to the image distances corresponding to the first target image and the second target image, and the distance between the optical graticule and the VR product to be tested, comprises: Calculating a difference between an image distance corresponding to the first target image and an image distance corresponding to the second target image; The distance between the optical graticule and the VR product to be tested is added to the difference to obtain the actual optimal object distance of the VR product to be tested.

3. The optimal object distance detection method according to claim 1, characterized in that: The method further comprises: Acquire optical simulation data of the VR product to be tested, and determine a set object distance corresponding to the VR product to be tested based on the optical simulation data; When it is detected that the distance between the VR product to be tested and the preset light source target is equal to the set object distance, the step of acquiring the first images generated by the light source target at different image distances is executed, and determining the first target image in each of the first images according to the clarity corresponding to each of the first images.

4. The optimal object distance detection method according to claim 1, characterized in that: The step of acquiring the second images respectively generated by the optical graticule at different image distances comprises: Obtaining the distance between the optical graticule and the VR product to be tested; When it is detected that the distance is within a preset distance range, second images respectively generated by the optical graticule at different image distances are acquired.

5. The optimal object distance detection method as claimed in claim 1, characterized in that: The step of determining the first target image in each of the first images according to the clarity corresponding to each of the first images comprises: Calculating first definitions corresponding to the first images, and taking a first image corresponding to the highest definition among the first definitions as a first target image; The step of determining the second target image in each of the second images according to the clarity corresponding to each of the second images comprises: The second definition corresponding to each of the second images is calculated, and the second image corresponding to the highest definition among the second definitions is used as the second target image.

6. The optimal object distance detection method according to any one of claims 1 to 5, characterized in that: After the step of calculating the actual optimal object distance of the VR product to be tested according to the image distances corresponding to the first target image and the second target image, and the distance between the optical graticule and the VR product to be tested, the method further includes: Determining whether the actual optimal object distance is within a preset object distance range; If it is determined that the actual optimal object distance is within the object distance range, determining a middle value of the object distance range, and determining the thickness to be compensated based on a difference between the middle value and the actual optimal object distance; If it is determined that the actual optimal object distance is not within the object distance range, the VR product to be tested is regarded as a defective product, and prompt information is output based on the defective product.

7. An optimal object distance detection system, characterized in that: The optimal object distance detection system comprises: A first image processing module, used to obtain first images respectively generated by the light source target at different image distances, and determine a first target image in each of the first images according to the clarity corresponding to each of the first images, wherein the first image is an image generated by the light source target through the VR product to be tested; A second image processing module is used to obtain second images respectively generated by the optical graticule at different image distances after detecting that the optical graticule is placed, and determine a second target image in each of the second images according to the clarity corresponding to each of the second images, wherein the second image is an image generated by the light source target through the VR product to be tested and the optical graticule; The object distance calculation module is used to calculate the actual optimal object distance of the VR product to be tested according to the image distances corresponding to the first target image and the second target image, and the distance between the optical graticule and the VR product to be tested.

8. An optimal object distance detection device, characterized in that: The optimal object distance detection device comprises a slide rail and a light source target, a first load-bearing fixture, a second load-bearing fixture and an image acquisition device arranged in sequence on the slide rail; The light source target is used to output the light source required for detecting the optimal object distance; The first carrying fixture is used to carry the VR product to be tested; The second carrying fixture is used for carrying the optical graticule; The image acquisition device is used to obtain first images generated by the light source target at different image distances, and determine a first target image in each of the first images according to the clarity corresponding to each of the first images, wherein the first image is an image generated by the light source target through the VR product to be tested; it is also used to obtain second images generated by the optical graticule at different image distances after detecting that the placement of the optical graticule is completed, and determine a second target image in each of the second images according to the clarity corresponding to each of the second images, wherein the second image is an image generated by the light source target through the VR product to be tested and the optical graticule; it is also used to calculate the actual optimal object distance of the VR product to be tested according to the image distances corresponding to the first target image and the second target image, and the distance between the optical graticule and the VR product to be tested.

9. An electronic device, characterized in that: The electronic device comprises: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the optimal object distance detection method according to any one of claims 1 to 6.

10. A storage medium, characterized in that: The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the optimal object distance detection method according to any one of claims 1 to 6 are implemented.

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