Imaging adjustment method and device of intelligent AR display equipment and storage medium

Abstract

The invention relates to the technical field of AR / VR, and discloses an imaging adjustment method and device of intelligent AR display equipment and a storage medium, and the method comprises the following steps: obtaining binocular image data; extracting first eye center data and second eye center data from the binocular image data; calculating focus data according to the first eye center data and the second eye center data; acquiring picture center data of a current playing picture; calculating position difference data between the focus data and the picture center data; and adjusting the playing picture according to the position difference data. The method has the advantage of providing more comfortable and natural watching experience.

Description

Technical Field

[0001] The present application relates to the AR / VR field, and in particular to an imaging adjustment method, device and storage medium for an intelligent AR display device. Background Art

[0002] Traditional vision testing methods include testing with an eye chart or optometry. The eye chart is generally divided into a visual acuity chart and a hyperopia chart. The person being tested needs to respond accordingly according to the doctor's instructions, and the doctor makes a judgment based on the response results. Another method is optometry, which requires the use of a computer testing instrument for optometry examination, but the equipment is relatively expensive. This limits the convenience and popularity of vision testing.

[0003] With the development of science and technology, existing intelligent AR display devices, such as smart glasses, can test the eyesight of the eyes. The test uses the imaging in the glasses to interact with the user, thereby realizing the test of vision. However, since each person's eye structure is different, if some adjustments are not made according to the eye structure of different users, long-term use of smart glasses may lead to fatigue. Therefore, there is an urgent need for a solution that can relieve eye fatigue for different users. Summary of the invention

[0004] In order to provide a more comfortable and natural viewing experience, the present application provides an imaging adjustment method, device and storage medium for an intelligent AR display device.

[0005] On the one hand, the present application provides an imaging adjustment method for an intelligent AR display device, which adopts the following technical solution:

[0006] An imaging adjustment method for an intelligent AR display device comprises the following steps:

[0007] Acquire binocular image data;

[0008] Extracting first eye center data and second eye center data from the binocular image data;

[0009] Calculating focus data according to the first eye center data and the second eye center data;

[0010] Get the center data of the current playing screen;

[0011] Calculate the position difference data between the focus data and the picture center data; and adjust the playback picture according to the position difference data.

[0012] By adopting the above technical solution, by acquiring and calculating the first eye center data and the second eye center data, as well as the picture center data based on the currently playing picture, it is helpful to achieve real-time adjustment of the displayed picture to provide a more comfortable and more natural viewing experience, thereby helping to alleviate eye fatigue and reduce eye fatigue.

[0013] Optionally, the step of calculating the position difference data between the focus data and the picture center data further includes the following sub-steps:

[0014] Calculating the position coordinates of the focus data as first coordinates;

[0015] Calculate the position coordinates of the center data of the picture as the second coordinates;

[0016] Calculating a coordinate difference between the first coordinate and the second coordinate;

[0017] Obtaining the displacement of the content feature in the current playing picture within the next preset time period as the movement gain;

[0018] The position difference data is calculated according to the coordinate difference and the movement gain.

[0019] By adopting the above technical solution, the position difference data is combined with the current coordinate difference and the movement gain within a preset time period, and through more precise calculation, the properties of the picture can be more accurately adjusted, thereby helping to further provide a more comfortable and natural viewing experience.

[0020] Optionally, the step of adjusting the playback picture according to the position difference data further includes the following sub-steps:

[0021] The longer the adjustment distance corresponding to the position difference data is, the higher the frequency of adjusting the playback picture in the next preset time period is.

[0022] By adopting the above technical solution, if the position difference between the user's line of sight and the playback screen is large, in order to adjust the screen device to a more comfortable viewing position for the user as soon as possible, the adjustment frequency is increased, and the line of sight can be accurately adjusted to the playback screen in real time, ensuring that the user is always in a better viewing state, thereby further improving the viewing experience.

[0023] Optionally, the step of acquiring binocular image data further includes the following sub-steps:

[0024] The eye entity is photographed based on a position of the intelligent AR display device outside the display area to obtain a binocular image;

[0025] identifying eye features in the binocular images, wherein the eye features correspond one-to-one to eye entities;

[0026] If the number of the eye features is greater than one, the data of the binocular image is used as the binocular image data; otherwise, the image is re-photographed.

[0027] By adopting the above technical solution, the validity of the binocular image is ensured by counting the number of eye features in the binocular image. Otherwise, the image quality may be poor due to reasons such as light and angle, so re-shooting is required to provide a more accurate line of sight calculation, which helps to provide more accurate adjustment.

[0028] Optionally, the step of acquiring binocular image data further includes the following sub-steps:

[0029] The eye entity is photographed based on a position of the intelligent AR display device outside the display area to obtain a binocular image;

[0030] identifying eye features in the binocular images, wherein the eye features correspond one-to-one to eye entities;

[0031] If the number of the eye features is greater than one, calculating the image area of ​​the eye features;

[0032] If the difference between the image areas of the eye features is within a preset difference range, the data of the binocular image is used as the binocular image data; otherwise, the image is re-photographed.

[0033] By adopting the above technical solution, in order to further ensure the effectiveness of the binocular image, in addition to considering the number of eyes, the area differences corresponding to the eye features are also considered, such as the whites of the eyes, eye sockets and pupils. If the difference is too large, the quality of the binocular image obtained may not be very ideal, so it needs to be re-shot.

[0034] Optionally, the step of acquiring binocular image data further includes the following sub-steps:

[0035] The eye entity is photographed based on a position of the intelligent AR display device outside the display area to obtain a binocular image;

[0036] identifying eye features in the binocular images, wherein the eye features correspond one-to-one to eye entities;

[0037] If the number of the eye features is greater than one, calculating the image area of ​​the eye features;

[0038] The position of the eye feature having the largest image area is taken as the first position;

[0039] Taking the position of the eye feature having the second largest area in the image as the second position;

[0040] The direction vector from the first position to the second position is a first direction vector;

[0041] The direction vector from the shooting position to the first position is the second direction vector;

[0042] If the angle between the first direction vector and the second direction vector is smaller than a preset angle value, the data of the binocular image is used as the binocular image data; otherwise, the image is re-photographed.

[0043] By adopting the above technical solution, the effectiveness of judging binocular images is further improved, and the calculation of the position and direction vector of eye features is added; by calculating the position and direction vector of eye features and judging their angles, the line of sight direction is further refined to provide a more accurate line of sight estimation and adjustment method.

[0044] Optionally, the step of extracting the first eye center data and the second eye center data from the binocular image data further includes the following sub-steps:

[0045] Extracting pupil image data from the binocular image data;

[0046] If the number of pupils corresponding to the pupil image data is zero, reacquiring the binocular image data;

[0047] If the number of pupils corresponding to the pupil image data is one, the center data of the pupil image is used as the first eye center data, the white of the eye image of the eye for which the pupil image is not recognized is calculated, and the center data of the white of the eye image is used as the second eye center data;

[0048] If the number of pupils corresponding to the pupil image data is greater than one, the center data of the largest pupil image is used as the first eye center data, and the center data of the smallest pupil image is used as the second eye center data.

[0049] By adopting the above technical solution, the pupil image data in the binocular image is processed, and the eye center data is extracted more accurately for different situations, and adaptive processing is performed according to different situations, thereby improving the accuracy of line of sight estimation and adjustment.

[0050] Optionally, the step of extracting the first eye center data and the second eye center data from the binocular image data further includes the following sub-steps:

[0051] Extracting white-of-the-eye image data from the binocular image data;

[0052] Calculating orbital image data according to the white of eye image data;

[0053] If the number of eye sockets corresponding to the eye socket image data is zero, reacquire the binocular image data;

[0054] If the number of eye sockets corresponding to the eye socket image data is one, the center data of the eye socket image is used as the first eye center data, and the center data of the white of the eye image of the eye that has not been identified as the second eye center data;

[0055] If the number of eye sockets corresponding to the eye socket image data is greater than one, the center data of the largest eye socket image is used as the first eye center data, and the center data of the smallest eye socket image is used as the second eye center data.

[0056] By adopting the above technical solution, the eye socket image is calculated through the white of the eye image and processed according to the number of eye sockets, the eye center data is extracted more accurately, and adaptive processing is performed according to different situations, thereby improving the accuracy of line of sight estimation and adjustment.

[0057] On the other hand, the present application provides an imaging adjustment device for an intelligent AR display device, which adopts the following technical solution:

[0058] An imaging adjustment device for an intelligent AR display device comprises a processor, wherein a program of the imaging adjustment method for the intelligent AR display device is run in the processor.

[0059] On the other hand, the present application provides a storage medium, which adopts the following technical solution:

[0060] A storage medium stores a program of the imaging adjustment method of the above-mentioned intelligent AR display device.

[0061] In summary, the present application includes at least one of the following beneficial technical effects: making applicable imaging adjustments according to the structure of each user's glasses so that the imaged picture is located in the comfort zone of the user's vision area, thereby helping to relieve eye fatigue. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Figure 1 This is a step diagram of the imaging adjustment method of the intelligent AR display device of the present application.

[0063] Figure 2 It is a structural schematic diagram of the intelligent AR display device of the present application.

[0064] Figure 3 This is a schematic diagram of the focus of binocular images in the imaging adjustment method of the intelligent AR display device of the present application.

[0065] Figure 4This is a step diagram for calculating the position difference data between the focus data and the picture center data in the imaging adjustment method of the intelligent AR display device of the present application.

[0066] Figure 5 It is a schematic diagram of mobile gain in the imaging adjustment method of the intelligent AR display device of the present application.

[0067] Figure 6 This is a schematic diagram of an imaging adjustment method for an intelligent AR display device of the present application, in which the adjustment method is to magnify the imaging.

[0068] Figure 7 This is a sub-step diagram of the step of obtaining binocular image data in the imaging adjustment method of the intelligent AR display device of the present application.

[0069] Figure 8 This is a sub-step diagram of the step of obtaining binocular image data in the imaging adjustment method of the intelligent AR display device of the present application.

[0070] Fig. 9 This is a schematic diagram of a method for adjusting the imaging of an intelligent AR display device of the present application, in which the difference between the image areas of eye features is within a preset difference range.

[0071] Fig.10 This is a sub-step diagram of the step of obtaining binocular image data in the imaging adjustment method of the intelligent AR display device of the present application.

[0072] Fig.11 It is a schematic diagram of a first direction vector and a second direction vector in the imaging adjustment method of the intelligent AR display device of the present application.

[0073] Fig.12 It is a schematic diagram of the first direction vector and the second direction vector when there is a light spot in the imaging adjustment method of the intelligent AR display device of the present application.

[0074] Fig.13 This is a sub-step diagram of the step of extracting first eye center data and second eye center data from binocular image data in the imaging adjustment method of the intelligent AR display device of the present application.

[0075] Fig.14 It is a schematic diagram of the maximum and minimum pupil images in the imaging adjustment method of the intelligent AR display device of the present application.

[0076] Fig.15 This is a sub-step diagram of the step of extracting first eye center data and second eye center data from binocular image data in the imaging adjustment method of the intelligent AR display device of the present application.

[0077] Figure numerals: 1, camera; 2, light spot. DETAILED DESCRIPTION

[0078] Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although certain embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be construed as being limited to the embodiments set forth herein. On the contrary, these embodiments are provided to provide a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are only for exemplary purposes and are not intended to limit the scope of protection of the present disclosure.

[0079] It should also be noted that, for ease of description, only the parts related to the invention are shown in the drawings. In the absence of conflict, the embodiments and features in the embodiments of the present disclosure can be combined with each other.

[0080] It should be noted that the concepts such as "first" and "second" mentioned in the present disclosure are only used to distinguish different devices, modules or units, and are not used to limit the order or interdependence of the functions performed by these devices, modules or units.

[0081] It should be noted that the modifications of "one" and "plurality" mentioned in the present disclosure are illustrative rather than restrictive, and those skilled in the art should understand that unless otherwise clearly indicated in the context, it should be understood as "one or more".

[0082] The names of the messages or information exchanged between multiple devices in the embodiments of the present disclosure are only used for illustrative purposes and are not used to limit the scope of these messages or information.

[0083] The present application embodiment discloses an imaging adjustment method for an intelligent AR display device, referring to Figure 1 and Figure 2 and Figure 3 , including the following steps:

[0084] Obtain binocular image data: The image data of the user's eyes can be obtained through the camera 1 or an external input device, and the image data includes data such as the eye socket, eyeball, eye white, and pupil.

[0085] The first eye center data and the second eye center data are extracted from the binocular image data; the binocular image data is analyzed through image processing technology, such as edge detection, pupil recognition, etc., to determine the user's binocular position and center position.

[0086] The focus data is calculated based on the first eye center data and the second eye center data; the user's line of sight focus is simulated based on the position and direction of the user's eyes, and the specific implementation method is: through set calculation or machine learning algorithm.

[0087] The center data of the current playing picture is obtained; the center data of the current picture can be obtained by a sensor built into the imaging device or an external input device.

[0088] Calculate the position difference data between the focus data and the picture center data; calculate the position difference data through the focus of the line of sight and the position of the picture center, so as to facilitate the subsequent corresponding operation of adjusting the picture.

[0089] Adjust the playback screen according to the position difference data. By calculating the position difference data, the position, size or shape of the imaging screen can be adjusted. The specific adjustment method can be moving, scaling or rotating, so that the image is more in line with the user's visual focus and viewing angle.

[0090] By acquiring and calculating the first eye center data and the second eye center data, as well as the picture center data based on the currently playing picture, it helps to achieve real-time adjustment of the displayed picture to provide a more comfortable and natural viewing experience, thereby helping to relieve eye fatigue and reduce eye fatigue.

[0091] Reference Figure 4 and Figure 5 and Figure 6 , the step of calculating the position difference data between the focus data and the picture center data further includes the following sub-steps:

[0092] The position coordinates of the calculated focus data are the first coordinates; the calculation of the first coordinates can be achieved through geometric calculations or machine learning algorithms, corresponding to the position and direction of both eyes.

[0093] The position coordinates of the calculated screen center data are the second coordinates. The second coordinates can be calculated through geometric calculations or machine learning algorithms, corresponding to the coordinates of the current screen center position.

[0094] The coordinate difference between the first coordinate and the second coordinate is calculated; by calculating the coordinate difference between the first coordinate and the second coordinate, the relative position relationship between the visual focus of the user's eyes and the center of the playback screen is represented.

[0095] The displacement of the content features in the current playback screen within the next preset time period is obtained as the movement gain; the displacement within the next preset time period can be judged based on the screen of the current playback content within the preset time period. By analyzing the content features in the playback screen, such as feature points in the image or the trajectory of a moving object, the content position within the next preset time period can be predicted, and the predicted content can be used as the movement gain.

[0096] The position difference data is calculated based on the coordinate difference and the movement gain. The coordinate difference and the movement gain are combined to more accurately calculate the position difference data between the focus data and the center data of the picture. The position difference data can be used to adjust the position, size or shape of the playback picture, so that the image on the display device is more in line with the user's visual focus and viewing angle.

[0097] The position difference data is combined with the current coordinate difference and the movement gain within a preset time period, and through more precise calculation, the properties of the picture are more accurately adjusted, thereby helping to further provide a more comfortable and natural viewing experience.

[0098] The step of adjusting the playback picture according to the position difference data also includes the following sub-steps:

[0099] The farther the adjustment distance corresponding to the position difference data, the higher the frequency of adjustment of the playback picture in the next preset time period. After calculating the position difference data, the distance is adjusted according to the position difference data to determine the adjustment frequency of the playback picture in the next preset time period. If the adjustment distance is farther, the adjustment frequency of the playback picture in the next preset time period will be higher. For example, if the adjustment distance is 1mm (a closer distance) and the adjustment frequency is 10 times, then the distance adjusted each time is 0.1mm. When the adjustment distance is 2.5mm, the adjustment frequency can be set to 20 times. The higher the frequency, the smoother the imaging action looks, and it is not easy to cause fatigue.

[0100] If there is a large difference between the position of the user's line of sight and the playback screen, in order to adjust the screen device to a more comfortable viewing position for the user as quickly as possible, the adjustment frequency is increased, and the line of sight can be accurately adjusted to the playback screen in real time, ensuring that the user is always in a better viewing state, thereby further improving the viewing experience.

[0101] Reference Figure 2 and Figure 7 , the step of obtaining binocular image data also includes the following sub-steps:

[0102] The eye entity is photographed based on a position of the intelligent AR display device outside the display area to obtain a binocular image;

[0103] Identifying eye features in binocular images, wherein the eye features correspond one-to-one to eye entities;

[0104] If the number of eye features is greater than one, the data of the binocular image is used as binocular image data, otherwise it is re-shot. The binocular image is obtained by shooting the image of the eye entity, and the shooting position is the position where the smart AR display device is located outside the display area to avoid blocking the line of sight or occupying the viewing area of ​​the line of sight. It is generally on the left or right side of the wearable device relative to the two eye entities. Therefore, the characteristics of the photographed eyes are one large and one small, or one near and one far.

[0105] The validity of the binocular images is ensured by counting the number of eye features in the binocular images, otherwise the image quality may be poor due to lighting, angle, etc., so reshooting is required to provide a more accurate line of sight calculation, which helps to provide more accurate adjustment.

[0106] Reference Figure 8 and Fig. 9 , the step of obtaining binocular image data also includes the following sub-steps:

[0107] The eye entity is photographed based on a position of the intelligent AR display device outside the display area to obtain a binocular image;

[0108] Identifying eye features in binocular images, wherein the eye features correspond one-to-one to eye entities;

[0109] If the number of eye features is greater than one, then the image area of ​​the eye features is calculated;

[0110] If the difference between the image areas of the eye features is within the preset difference range, the data of the binocular images is used as binocular image data, otherwise the image is re-photographed. By calculating the image area of ​​the eye features, it is determined whether the difference corresponding to the area is within the preset range. If it is satisfied, it means that the quality of the binocular image acquisition is high. If it is not satisfied, there may be a larger or smaller spot 2, etc., and the image needs to be re-photographed.

[0111] In order to further ensure the effectiveness of binocular images, in addition to considering the number of eyes, the area differences corresponding to the eye features are also considered, such as the whites of the eyes, eyeballs, eye sockets and pupils. If the differences are too large, the quality of the binocular images obtained may not be very ideal, so they need to be re-shot.

[0112] Reference Fig.10 and Fig.11 , the step of obtaining binocular image data also includes the following sub-steps:

[0113] The eye entity is photographed based on a position of the intelligent AR display device outside the display area to obtain a binocular image;

[0114] Identifying eye features in binocular images, wherein the eye features correspond one-to-one to eye entities;

[0115] If the number of eye features is greater than one, then the image area of ​​the eye features is calculated;

[0116] The position of the eye feature with the largest image area is taken as the first position;

[0117] Taking the position of the eye feature having the second largest image area as the second position;

[0118] The direction vector from the first position to the second position is a first direction vector α;

[0119] The direction vector from the shooting position to the first position is the second direction vector β;

[0120] If the angle between the first direction vector and the second direction vector is less than the preset angle value, the binocular image data is used as binocular image data. Otherwise, if the angle of the light spot 2 does not meet the preset angle value, it needs to be re-shot. Fig.12 , if the number of recognized eye features is greater than one, calculate the image area of ​​each eye feature. Then, select the position of the eye feature with the largest image area as the first position, and select the position of the eye feature with the second largest image area as the second position. Next, calculate the direction vector from the first position to the second position, that is, the first direction vector. At the same time, calculate the direction vector from the shooting position to the first position, that is, the second direction vector. Finally, determine whether the angle between the first direction vector and the second direction vector is less than a preset angle value. If this condition is met, the data of this binocular image is used as binocular image data, otherwise reshoot.

[0121] To further improve the effectiveness of judging binocular images, the calculation of the eye feature position and direction vector is added; by calculating the position and direction vector of the eye feature and judging their angle, the line of sight direction is further refined to provide a more accurate line of sight estimation and adjustment method.

[0122] Reference Fig.13 and Fig.14 The step of extracting the first eye center data and the second eye center data from the binocular image data further includes the following sub-steps:

[0123] Extracting pupil image data from binocular image data;

[0124] If the number of pupils corresponding to the pupil image data is zero, the binocular image data is re-acquired; the pupil image data is extracted from the binocular image data. If there is no corresponding number of pupils in the pupil image data (i.e., the number is zero), the binocular image data is re-acquired. This is mainly to avoid generating erroneous data when the pupil is not recognized or the image quality is poor.

[0125] If the number of pupils corresponding to the pupil image data is one, the center data of the pupil image is used as the first eye center data, the white of the eye image of the eye whose pupil image is not recognized is calculated, and the center data of the white of the eye image is used as the second eye center data; if there is only one pupil in the pupil image data (i.e. the number is one), the center data of this pupil image is used as the first eye center data, and the white of the eye image of the eye whose pupil image is not recognized is calculated, and the center data of the white of the eye image is used as the second eye center data. The purpose of this design is to estimate the position of the second eye center data through the white of the eye image when there is only one pupil.

[0126] If the number of pupils corresponding to the pupil image data is greater than one, the center data of the largest pupil image is used as the first eye center data, and the center data of the smallest pupil image is used as the second eye center data. If there are multiple pupils in the pupil image data (i.e., the number is greater than one), the center data of the largest pupil image is used as the first eye center data, and the center data of the smallest pupil image is used as the second eye center data. In this way, the two most suitable pupils can be selected to extract the eye center data based on the difference in pupil size. At this time, there may be a second largest pupil image due to factors such as light interference, but the area of ​​the pupil is generally relatively small, and the interference of factors such as light mostly results in an area between the largest and the smallest. Therefore, directly selecting the center data of the smallest pupil image as the second eye center data is conducive to improving the accuracy of the judgment.

[0127] The processing of pupil image data in binocular images and different numbers of pupils can more accurately extract eye center data and perform adaptive processing according to different situations, thereby improving the accuracy of line of sight estimation and adjustment.

[0128] Reference Fig.15 The step of extracting the first eye center data and the second eye center data from the binocular image data further includes the following sub-steps:

[0129] Extracting eye white image data from binocular image data;

[0130] Calculate the orbital image data according to the white of eye image data;

[0131] If the number of eye sockets corresponding to the eye socket image data is zero, the binocular image data is re-acquired; the white of eye image data is extracted from the binocular image data, and the eye socket image data is calculated based on the white of eye image data. If there is no corresponding number of eye sockets in the eye socket image data (i.e., the number is zero), the binocular image data is re-acquired.

[0132] If the number of eye sockets corresponding to the eye socket image data is one, the center data of the eye socket image is used as the first eye center data, and the center data of the eye white image of the eye whose eye socket image is not recognized is used as the second eye center data; if there is only one eye socket in the eye socket image data (that is, the number is one), the center data of this eye socket image is used as the first eye center data, and the center data of the eye white image of the eye whose eye socket image is not recognized is used as the second eye center data. The purpose of this design is to estimate the position of the second eye center data through the eye white image of the eye whose eye socket is not recognized when there is only one eye socket.

[0133] If the number of eye sockets corresponding to the eye socket image data is greater than one, the center data of the largest eye socket image is used as the first eye center data, and the center data of the smallest eye socket image is used as the second eye center data. If there are multiple eye sockets in the eye socket image data (i.e., the number is greater than one), the center data of the largest eye socket image is used as the first eye center data, and the center data of the smallest eye socket image is used as the second eye center data. In this way, the most suitable two eye sockets can be selected based on the difference in eye socket size to extract eye center data.

[0134] The eye socket image is calculated from the white of the eye image and processed according to the number of eye sockets to more accurately extract the eye center data and perform adaptive processing according to different situations, thereby improving the accuracy of line of sight estimation and adjustment.

[0135] The present application also discloses an imaging adjustment device for an intelligent AR display device, including a processor, in which a program for the imaging adjustment method for the intelligent AR display device is running.

[0136] The present application also discloses a storage medium in real time, storing a program of the imaging adjustment method of the above-mentioned intelligent AR display device.

[0137] It should be noted that the computer-readable medium recorded in some embodiments of the present disclosure may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, 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 some embodiments of the present disclosure, a 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, device or device. In some embodiments of the present disclosure, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries a computer-readable program code. This propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The computer readable signal medium may also be any computer readable medium other than a computer readable storage medium, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. The program code contained on the computer readable medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (radio frequency), etc., or any suitable combination of the above.

[0138] In some embodiments, the client and the server may communicate using any currently known or future developed network protocol such as HTTP (HyperText Transfer Protocol), and may be interconnected with any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), an internet (e.g., the Internet), and a peer-to-peer network (e.g., an ad hoc peer-to-peer network), as well as any currently known or future developed network.

[0139] Computer program code for performing the operations of some embodiments of the present disclosure 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 cases involving a remote computer, the remote computer may be connected to the user's computer via 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).

[0140] 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 disclosure. 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 implementations as replacements, 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.

[0141] The functions described above herein may be performed at least in part by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), and the like.

[0142] The above descriptions are only some preferred embodiments of the present disclosure and an explanation of the technical principles used. Those skilled in the art should understand that the scope of the invention involved in the embodiments of the present disclosure is not limited to the technical solutions formed by a specific combination of the above-mentioned technical features, but should also cover other technical solutions formed by any combination of the above-mentioned technical features or their equivalent features without departing from the above-mentioned inventive concept. For example, the above-mentioned features are replaced with the technical features with similar functions disclosed in the embodiments of the present disclosure (but not limited to) and the technical solutions formed.

Claims

1. An imaging adjustment method for an intelligent AR display device, characterized in that: The steps include: Acquire binocular image data; Extracting first eye center data and second eye center data from the binocular image data; Calculating focus data according to the first eye center data and the second eye center data; Get the center data of the current playing screen; Calculating position difference data between the focus data and the picture center data; The playback picture is adjusted according to the position difference data.

2. The imaging adjustment method of the intelligent AR display device according to claim 1, characterized in that: The step of calculating the position difference data between the focus data and the picture center data further includes the following sub-steps: Calculating the position coordinates of the focus data as first coordinates; Calculate the position coordinates of the center data of the picture as the second coordinates; Calculating a coordinate difference between the first coordinate and the second coordinate; Obtaining the displacement of the content feature in the current playing picture within the next preset time period as the movement gain; The position difference data is calculated according to the coordinate difference and the movement gain.

3. The imaging adjustment method of the intelligent AR display device according to claim 1 or 2, characterized in that: The step of adjusting the playback picture according to the position difference data further includes the following sub-steps: The longer the adjustment distance corresponding to the position difference data is, the higher the frequency of adjusting the playback picture in the next preset time period is.

4. The imaging adjustment method of the intelligent AR display device according to claim 1 or 2, characterized in that: The step of obtaining binocular image data further includes the following sub-steps: The eye entity is photographed based on a position of the intelligent AR display device outside the display area to obtain a binocular image; identifying eye features in the binocular images, wherein the eye features correspond one-to-one to eye entities; If the number of the eye features is greater than one, the data of the binocular image is used as the binocular image data; otherwise, the image is re-photographed.

5. The imaging adjustment method of the intelligent AR display device according to claim 1 or 2, characterized in that: The step of obtaining binocular image data further includes the following sub-steps: The eye entity is photographed based on a position of the intelligent AR display device outside the display area to obtain a binocular image; identifying eye features in the binocular images, wherein the eye features correspond one-to-one to eye entities; If the number of the eye features is greater than one, calculating the image area of ​​the eye features; If the difference between the image areas of the eye features is within a preset difference range, the data of the binocular image is used as the binocular image data; otherwise, the image is re-photographed.

6. The imaging adjustment method of the intelligent AR display device according to claim 1 or 2, characterized in that: The step of obtaining binocular image data further includes the following sub-steps: The eye entity is photographed based on a position of the intelligent AR display device outside the display area to obtain a binocular image; identifying eye features in the binocular images, wherein the eye features correspond one-to-one to eye entities; If the number of the eye features is greater than one, calculating the image area of ​​the eye features; The position of the eye feature having the largest image area is taken as the first position; Taking the position of the eye feature having the second largest area in the image as the second position; The direction vector from the first position to the second position is a first direction vector; The direction vector from the shooting position to the first position is the second direction vector; If the angle between the first direction vector and the second direction vector is smaller than a preset angle value, the data of the binocular image is used as the binocular image data; otherwise, the image is re-photographed.

7. The imaging adjustment method of the intelligent AR display device according to claim 1 or 2, characterized in that: The step of extracting the first eye center data and the second eye center data from the binocular image data further includes the following sub-steps: Extracting pupil image data from the binocular image data; If the number of pupils corresponding to the pupil image data is zero, reacquiring the binocular image data; If the number of pupils corresponding to the pupil image data is one, the center data of the pupil image is used as the first eye center data, the white of the eye image of the eye for which the pupil image is not recognized is calculated, and the center data of the white of the eye image is used as the second eye center data; If the number of pupils corresponding to the pupil image data is greater than one, the center data of the largest pupil image is used as the first eye center data, and the center data of the smallest pupil image is used as the second eye center data.

8. The imaging adjustment method of the intelligent AR display device according to claim 1 or 2, characterized in that: The step of extracting the first eye center data and the second eye center data from the binocular image data further includes the following sub-steps: Extracting white-of-the-eye image data from the binocular image data; Calculating orbital image data according to the white of eye image data; If the number of eye sockets corresponding to the eye socket image data is zero, reacquire the binocular image data; If the number of eye sockets corresponding to the eye socket image data is one, the center data of the eye socket image is used as the first eye center data, and the center data of the white of the eye image of the eye that has not been identified as the second eye center data; If the number of eye sockets corresponding to the eye socket image data is greater than one, the center data of the largest eye socket image is used as the first eye center data, and the center data of the smallest eye socket image is used as the second eye center data.

9. An imaging adjustment device for an intelligent AR display device, characterized in that: It includes a processor, in which a program of the imaging adjustment method of the intelligent AR display device according to any one of claims 1 to 8 is run.

10. A storage medium, characterized in that: A program storing the imaging adjustment method of the intelligent AR display device as described in any one of claims 1 to 8.

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