A two-dimensional code payment method and a two-dimensional code payment system in a weak light environment

Abstract

The application relates to a two-dimensional code payment method in a weak light environment and a two-dimensional code payment method. The two-dimensional code payment method of the application is applied to a mobile terminal with a front camera and a rear camera, and is characterized in that the two-dimensional code payment method comprises the following steps: a starting triggering step, wherein the front camera of the mobile terminal is started under the condition that the rear camera captures a two-dimensional code in a weak light environment; a payment willingness judging step, wherein whether the user has payment willingness is judged based on the change of the pupil image captured by the front camera and the light quantity detected by the front camera; and a payment executing step, wherein a payment operation is completed based on the two-dimensional code in response to the judgment result that the user has payment willingness. According to the application, the user payment willingness can be judged, and the target two-dimensional code selected by the user can be determined from multiple two-dimensional codes.

Description

Technical Field

[0001] This invention relates to mobile payment technology, and in particular to a QR code payment method and system for use in low-light environments. Background Technology

[0002] The convenience of QR code payment can be challenged in certain environments. Low-light environments are a typical scenario that affects the success rate of scanning and user experience, such as open-air parking lots at night, poorly lit underground garages, and vending machines at night.

[0003] In low-light environments, users typically need to turn on their phone's flashlight to illuminate the QR code when making a payment via mobile phone. However, often before shopping, users may need to check information such as product category, price, discounts, and payment instructions, which is usually located next to the payment QR code. Currently, in low-light environments, users typically open the scanning function within a payment app and tap the flashlight on the scanning interface to make the payment. During the scanning process, if the phone's camera captures multiple QR codes, the user selects the correct one from the available options on the screen.

[0004] In other words, existing technologies cannot determine a user's payment intention in low-light environments. Furthermore, if the camera captures multiple QR codes, the user needs to manually select the payment QR code on their phone screen, which cannot be automated, resulting in reduced payment efficiency and a poor payment experience. Summary of the Invention

[0005] In order to solve the problems in the prior art, the present invention aims to provide a QR code payment method and a QR code payment system in low light environment that can determine the user's willingness to pay.

[0006] Building upon this, the aim is to provide a QR code payment method and system for low-light environments that can also identify the target QR code selected by the user from multiple QR codes.

[0007] This invention discloses a QR code payment method for low-light environments, applicable to mobile terminals equipped with front-facing and rear-facing cameras, characterized in that the QR code payment method includes the following steps: The triggering step is initiated when the rear camera captures the QR code in a low-light environment, and then the front camera of the mobile terminal is activated. The payment intention determination step determines whether the user has the intention to pay based on changes in the user's pupil image captured by the front-facing camera and the amount of light detected by the front-facing camera; and The payment execution step, in response to the judgment result that the user has the intention to pay, completes the payment operation based on the QR code.

[0008] Optionally, in the payment intention determination step, if the pupil in the pupil image continuously shrinks for a specified time and the amount of light entering the eye is greater than a preset first specified threshold, it is determined that the user has the intention to pay.

[0009] Optionally, in the payment intention determination step, if the pupil in the pupil image becomes smaller and then larger again and the amount of light entering the eye is less than a pre-set second predetermined threshold, it is determined that the user has the intention to pay.

[0010] Optionally, in the payment intention determination step, the user's willingness to pay is determined based on the pupil image captured by the front-facing camera, the amount of light detected by the front-facing camera, and the spatial position status of the mobile terminal.

[0011] Optionally, the spatial position state of the mobile terminal includes: the angular velocity and angular displacement of the mobile terminal.

[0012] Optionally, in the triggering step, if multiple QR codes are captured, the following further step is included between the payment intention determination step and the payment execution step: The QR code identification step involves determining the target QR code selected by the user from among the multiple QR codes based on the user's pupil gaze direction captured by the front-facing camera. In the payment execution step, the payment operation is performed based on the target QR code determined in the QR code determination step.

[0013] Optionally, the QR code determination step includes: Based on the event of capturing multiple QR codes, the front-facing camera of the mobile terminal emits infrared light; Obtain infrared reflection information of the infrared light from the user's pupils; Based on the infrared reflection information, the user's gaze position on the mobile terminal screen is determined, and the QR code at the gaze position is identified as the target QR code.

[0014] Optionally, the QR code determination step includes: Based on the event of capturing multiple QR codes, the front-facing camera of the mobile terminal emits infrared light; Obtain the first infrared reflection information of the infrared light from the user's pupil; Based on the first infrared reflection information, the user's first gaze position on the mobile terminal screen is determined to select the first candidate QR code; After detecting that the user's gaze has left the mobile terminal screen and is looking at the target QR code in the real scene for a specified time based on the first infrared reflection information, the user's pupil reflects the infrared light in a second infrared reflection information. Based on the second infrared reflection information and the QR code orientation position obtained by the rear camera, the user's second gaze direction in the real scene is determined to select the second candidate QR code; and When it is determined that the relative positional relationship between the first candidate QR code and the second candidate QR code is consistent, the QR code is determined as the target QR code.

[0015] Optionally, determining that the relative positional relationship between the first candidate QR code and the second candidate QR code is consistent includes: Determine whether the position of the first candidate QR code on the screen of the mobile terminal relative to other QR codes is the same as the position of the second candidate QR code relative to the other QR codes in the real-world scenario.

[0016] Optionally, the infrared reflection information includes the infrared reflection angle information of the user's pupil and the center position information of the user's pupil.

[0017] Optionally, the QR code determination step includes: The user's pupil image captured by the front-facing camera is input into a pre-trained deep learning model, wherein the pre-trained deep learning model pre-trains the correspondence between the pupil image and the gaze orientation. The deep learning model outputs the user's gaze orientation corresponding to the pupil image; and The target QR code is determined from the plurality of QR codes based on the gaze orientation.

[0018] Optionally, the low-light environment includes an environment where the flash of the mobile terminal is turned on.

[0019] A QR code payment system for low-light environments according to one aspect of the present invention includes: The rear camera is used to capture QR codes; The front-facing camera is used to capture images of the user's pupils and to detect the amount of light entering the camera. The activation trigger module is used to activate the front camera when the rear camera captures a QR code in a low-light environment. The payment intention determination module determines whether the user has the intention to pay based on changes in the user's pupil image captured by the front-facing camera and the amount of light detected by the front-facing camera; and The payment execution module, in response to the judgment result that the user has the intention to pay, completes the payment operation based on the QR code.

[0020] Optionally, in the payment intention determination module, if the pupil of the user captured by the front-facing camera continuously shrinks for a specified time and the amount of light detected by the front-facing camera is greater than a preset first predetermined threshold, it is determined that the user has the intention to pay.

[0021] Optionally, in the payment intention determination module, if the pupil of the user captured by the front-facing camera becomes smaller and then larger, and the amount of light detected by the front-facing camera is less than a pre-set second predetermined threshold, it is determined that the user has the intention to pay.

[0022] Optionally, in the payment intention determination module, the user's willingness to pay is determined based on the pupil image captured by the front-facing camera, the amount of light detected by the front-facing camera, and the spatial position status of the mobile terminal.

[0023] Optionally, the angular velocity and angular displacement of the mobile terminal are obtained by the gyroscope of the mobile terminal as the spatial position state of the mobile terminal.

[0024] Optionally, it further includes: The QR code identification module determines the target QR code selected by the user from multiple QR codes based on the user's pupil gaze direction captured by the front-facing camera. The payment execution module performs a payment operation based on the target QR code determined in the QR code determination module.

[0025] Optionally, the front-facing camera further includes: an infrared module for emitting infrared light and receiving infrared reflection information. The QR code determination module, based on the event of capturing multiple QR codes, causes the infrared module of the mobile terminal to emit infrared light. The infrared module of the front-facing camera acquires infrared reflection information of the infrared light from the user's pupils. The QR code determination module determines the user's gaze position on the mobile terminal screen based on the infrared reflection information and identifies the QR code at the gaze position as the target QR code.

[0026] Optionally, the front-facing camera further includes: an infrared module for emitting infrared light and receiving infrared reflection information. The QR code determination module, based on the event of capturing multiple QR codes, causes the infrared module of the mobile terminal to emit infrared light. The infrared module of the front-facing camera acquires the first infrared reflection information of the infrared light from the user's pupil. The QR code determination module determines the user's first gaze position on the mobile terminal screen based on the first infrared reflection information to select the first candidate QR code. When the QR code determination module detects that the user's gaze has left the mobile terminal screen and is looking at the target QR code in the real scene for a specified time based on the first infrared reflection information, the infrared module of the front-facing camera acquires the second infrared reflection information of the user's pupils on the infrared light. Based on the second infrared reflection information and the QR code orientation position obtained by the rear camera, the QR code determination module determines the user's second gaze direction in the real scene to select the second candidate QR code. When it is determined that the relative positional relationship between the first candidate QR code and the second candidate QR code is consistent, the QR code is determined as the target QR code.

[0027] Optionally, determining that the relative positional relationship between the first candidate QR code and the second candidate QR code is consistent includes: Determine whether the position of the first candidate QR code on the screen of the mobile terminal relative to other QR codes is the same as the position of the second candidate QR code relative to the other QR codes in the real-world scenario.

[0028] Optionally, the infrared reflection information includes the infrared reflection angle information of the user's pupil and the center position information of the user's pupil.

[0029] Optionally, the QR code determination module further includes a deep learning model. The user's pupil image captured by the front-facing camera is input into the deep learning model, wherein the deep learning model is pre-trained to have a correspondence between the pupil image and the gaze orientation. Based on the user's gaze orientation corresponding to the pupil image output by the deep learning model, the target QR code is determined from the plurality of QR codes.

[0030] The present invention provides a computer-readable medium having a computer program stored thereon, which, when executed by a processor, implements the QR code payment method in a low-light environment.

[0031] A computer device according to one aspect of the present invention includes a storage module, a processor, and a computer program stored on the storage module and executable on the processor, wherein the processor executes the computer program to implement the QR code payment method in a low-light environment.

[0032] A computer program product according to one aspect of the present invention includes a computer program that, when executed by a processor, implements the QR code payment method in a low-light environment. Attached Figure Description

[0033] The described and other objects and advantages of the invention will become more fully clear from the following detailed description taken in conjunction with the accompanying drawings, wherein like or similar elements are denoted by the same reference numerals.

[0034] Figure 1 This is a flowchart illustrating the QR code payment method in a low-light environment according to the first embodiment of the present invention.

[0035] Figure 2 This is a structural block diagram of a QR code payment system in a low-light environment according to the first embodiment of the present invention.

[0036] Figure 3 This is a flowchart illustrating the QR code payment method in a low-light environment according to the second embodiment of the present invention.

[0037] Figure 4 This is a structural block diagram of a QR code payment system in a low-light environment according to the second embodiment of the present invention. Detailed Implementation

[0038] The following are some embodiments of the present invention, intended to provide a basic understanding of the invention. They are not intended to identify key or decisive elements of the invention or to limit the scope of protection sought.

[0039] For the purposes of brevity and illustrativeness, the principles of the invention are described herein primarily with reference to exemplary embodiments. However, those skilled in the art will readily recognize that the same principles are equivalently applicable to all types of QR code payment methods and systems in low-light environments according to the present invention, and that these same principles can be implemented therein, with any such variations not departing from the true spirit and scope of the invention.

[0040] Furthermore, reference is made in the following description to the accompanying drawings, which illustrate specific exemplary embodiments. Electrical, mechanical, logical, and structural modifications may be made to these embodiments without departing from the spirit and scope of the invention. Moreover, while features of the invention are disclosed in conjunction with only one of several embodiments, this feature may be combined with one or more other features of other embodiments if desired and / or advantageous for any given or identifiable function. Therefore, the following description should not be considered limiting in any sense, and the scope of the invention is defined by the appended claims and their equivalents.

[0041] Terms such as “possessing” and “comprising” indicate that, in addition to having units (modules) and steps that are directly and explicitly stated in the specification and claims, the technical solution of the present invention does not exclude the presence of other units (modules) and steps that are not directly or explicitly stated.

[0042] The QR code payment method in low-light environments according to one aspect of the present invention is applied to a mobile terminal equipped with a front-facing camera and a rear-facing camera. The QR code payment method includes the following steps: The triggering step is initiated when the rear camera captures the QR code in a low-light environment, and then the front camera of the mobile terminal is activated. The payment intention determination step determines whether the user has the intention to pay based on changes in the user's pupil image captured by the front-facing camera and the amount of light detected by the front-facing camera; and The payment execution step, in response to the judgment result that the user has the intention to pay, completes the payment operation based on the QR code.

[0043] In this way, by capturing changes in pupil size (such as the duration of continuous pupil shrinkage) with the front-facing camera and combining this with the amount of light entering the eye to determine payment intention, the problem of difficulty in recognizing payment intention in low-light environments can be solved, enabling contactless automatic payment processes.

[0044] In the payment intention determination step, as a determination method, if the pupil in the pupil image continuously shrinks for a specified time and the amount of light entering the eye is greater than a pre-set first specified threshold, it is determined that the user has the intention to pay.

[0045] In this way, the continuous constriction of the pupil can be obtained by recording pupil images with the front-facing camera. For example, the recorded pupil images can be stored in the mobile terminal and the changes in pupil images before and after a specified time (e.g., a few seconds) can be compared. The amount of light entering the eye can be obtained by the sensor of the front-facing camera of the mobile terminal. By setting the dual conditions of continuous pupil constriction and light entering the eye exceeding a first threshold in the pupil image, the accuracy of payment intention judgment can be improved, and erroneous payment operations can be avoided.

[0046] In the payment intention determination step, as another determination method, if the pupil in the pupil image becomes smaller and then larger and the amount of light entering is less than a pre-set second predetermined threshold, it is determined that the user has the intention to pay.

[0047] In this way, the dynamic judgment logic of first making the pupil smaller and then larger and the amount of light entering is less than the second threshold can be adapted to scenarios where users dynamically adjust the position of their mobile terminals to block the reflected light of the QR code, thereby enhancing the flexibility of the judgment mechanism.

[0048] In the payment intention determination step, the user's willingness to pay is determined based on the pupil image captured by the front-facing camera, the amount of light detected by the front-facing camera, and the spatial position of the mobile terminal. The spatial position of the mobile terminal includes its angular velocity and angular displacement.

[0049] In this way, by further combining the spatial position status (angular velocity / angular displacement) of the mobile terminal for multi-dimensional judgment, the problem of misjudgment that may occur due to single parameter judgment can be solved.

[0050] In the triggering step, if multiple QR codes are captured, the following further step is included between the payment intention determination step and the payment execution step: The QR code identification step involves determining the target QR code selected by the user from among the multiple QR codes based on the user's pupil gaze direction captured by the front-facing camera. In the payment execution step, the payment operation is performed based on the target QR code determined in the QR code determination step.

[0051] In this way, when the rear camera captures multiple QR codes, the target QR code can be automatically determined by the direction of pupil gaze, solving the problem of having to manually select one in multi-code scenarios.

[0052] The QR code determination step includes: Based on the event of capturing multiple QR codes, the front-facing camera of the mobile terminal emits infrared light; Obtain infrared reflection information of the infrared light from the user's pupils; Based on the infrared reflection information, the user's gaze position on the mobile terminal screen is determined, and the QR code at the gaze position is identified as the target QR code.

[0053] By using infrared reflection information to locate the screen's viewing position and automatically selecting the QR code, payment efficiency can be improved.

[0054] The QR code determination step includes: Based on the event of capturing multiple QR codes, the front-facing camera of the mobile terminal emits infrared light; Obtain the first infrared reflection information of the infrared light from the user's pupil; Based on the first infrared reflection information, the user's first gaze position on the mobile terminal screen is determined to select the first candidate QR code; After detecting that the user's gaze has left the mobile terminal screen and is looking at the target QR code in the real scene for a specified time based on the first infrared reflection information, the user's pupil reflects the infrared light in a second infrared reflection information. Based on the second infrared reflection information and the QR code orientation position obtained by the rear camera, the user's second gaze direction in the real scene is determined to select the second candidate QR code; and When the relative positions of the first candidate QR code and the second candidate QR code are determined to be consistent, the QR code is identified as the target QR code. The step of determining that the relative positional relationship between the first candidate QR code and the second candidate QR code is consistent includes: Determine whether the position of the first candidate QR code on the screen of the mobile terminal relative to other QR codes is the same as the position of the second candidate QR code relative to the other QR codes in the real-world scenario.

[0055] In this way, by verifying the gaze position in two stages (screen + real scene), the accuracy of QR code selection can be ensured and selection errors can be prevented.

[0056] As an alternative method, the QR code determination step includes: The user's pupil image captured by the front-facing camera is input into a pre-trained deep learning model, wherein the pre-trained deep learning model pre-trains the correspondence between the pupil image and the gaze orientation. The deep learning model outputs the user's gaze orientation corresponding to the pupil image; and The target QR code is determined from the plurality of QR codes based on the gaze orientation.

[0057] In this way, by using a deep learning model to replace the infrared module, the compatibility problem of devices without infrared functionality is solved.

[0058] The low-light environment includes an environment where the flash of the mobile terminal is turned on.

[0059] This section includes the flash-on environment in the low-light definition, so that the mobile terminal can be detected to be in a low-light environment by detecting the flash being turned on.

[0060] First Implementation Method Figure 1 This is a flowchart illustrating the QR code payment method in a low-light environment according to the first embodiment of the present invention.

[0061] The QR code payment method in low-light environment according to the first embodiment of the present invention is applied to a mobile terminal with a front camera and a rear camera. The QR code payment method of this embodiment corresponds to a scenario where only one QR code is captured by the rear camera.

[0062] like Figure 1 As shown, the QR code payment method in a low-light environment according to the first embodiment of the present invention includes the following steps: Initiate triggering step S101: when the rear camera captures the QR code in a low-light environment, activate the front camera of the mobile terminal. The payment intention determination step S102 determines whether the user has the intention to pay based on changes in the user's pupil image captured by the front-facing camera and the amount of light detected by the front-facing camera; and In payment execution step S103, in response to the judgment result that the user has the intention to pay, the payment operation is completed based on the QR code.

[0063] Specifically, in the activation triggering step S101, in order to obtain the QR code in a low-light environment, the user turns on the flashlight and opens the rear camera of the mobile terminal. After confirming that the flashlight is on and the rear camera has captured the QR code, the user triggers the activation of the front camera of the mobile terminal.

[0064] In the payment intention judgment step S102, the changes in the user's pupil image captured by the front camera can be realized by recording the pupil state map by the front camera and comparing the changes in the state map. The amount of light detected by the front camera refers to the amount of light entering the user's eyes after the flash light is reflected by the QR code.

[0065] Here, in the payment willingness determination step S102, the following two methods can be used to determine whether a user has the willingness to pay: (1) If the front-facing camera detects that the user's pupils are continuously shrinking and remain in a small pupil state for a certain period of time (e.g., a few seconds), and the amount of light detected by the front-facing camera is greater than a specified threshold, then it is determined that the user has the intention to pay; or (2) If the front camera detects that the user's pupils have become smaller and then larger, and the amount of light detected by the front camera is less than the specified threshold (in this case, the QR code is reflected into the user's eyes, and the user adjusts the position of the mobile terminal to block the reflected light, and the amount of light will become smaller), then it is determined that the user has the intention to pay.

[0066] Furthermore, based on changes in the user's pupil image and the amount of light detected by the front-facing camera, the user's willingness to pay can also be determined by combining the spatial position of the mobile terminal. For example, when the rear-facing camera captures the payment QR code, it calls the mobile terminal's gyroscope to obtain the angular velocity and angular displacement of the mobile terminal. If the angular velocity and angular displacement are within a specified threshold, it indicates that the spatial state during movement is stable, which suggests that the user has the willingness to pay.

[0067] In payment execution step S103, in response to the judgment result that the user has the intention to pay, the browser of the mobile terminal is invoked to access the URL address of the QR code. Based on the URL information, the browser requests to open the corresponding payment application, and the corresponding payment application completes the payment.

[0068] Figure 2 This is a structural block diagram of a QR code payment system in a low-light environment according to the first embodiment of the present invention.

[0069] like Figure 2As shown, the QR code payment system 100 in a low-light environment according to the first embodiment of the present invention includes: The rear camera captures QR codes. The front-facing camera 120 captures images of the user's pupils and is used to detect the amount of light entering the camera; The activation trigger module 130 is used to activate the front camera when the rear camera captures a QR code in a low-light environment. The payment willingness determination module 140 uses the user's pupil image captured by the front-facing camera and the amount of light detected by the front-facing camera to determine whether the user has the willingness to pay; and The payment execution module 150 completes the payment operation based on the QR code, according to the judgment result that the user has the intention to pay.

[0070] Specifically, if the user's pupils continuously shrink and remain so for a specified time in the pupil image captured by the front-facing camera, and the amount of light detected by the front-facing camera is greater than a pre-set first specified threshold, the payment willingness judgment module 140 determines that the user has the willingness to pay.

[0071] Alternatively, if the user's pupils in the pupil image captured by the front-facing camera of the payment willingness determination module 140 become smaller and then larger, and the amount of light detected by the front-facing camera is less than a pre-set second predetermined threshold, the user is determined to have the willingness to pay.

[0072] Furthermore, in the payment intention judgment module 140, the user's willingness to pay can be determined based on the pupil image captured by the front-facing camera and the amount of light detected by the front-facing camera, combined with the spatial position status of the mobile terminal. The spatial position status of the mobile terminal is obtained by using the mobile terminal's gyroscope to measure the angular velocity and angular displacement.

[0073] Second Implementation Method Figure 3 This is a flowchart illustrating the QR code payment method in a low-light environment according to the second embodiment of the present invention.

[0074] The QR code payment method in low-light environment according to the second embodiment of the present invention is applied to a mobile terminal with a front camera and a rear camera. Unlike the first embodiment, the QR code payment method in the second embodiment corresponds to a scenario where multiple QR codes are captured by the rear camera.

[0075] like Figure 2 As shown, the QR code payment method in a low-light environment according to the first embodiment of the present invention includes the following steps: In the triggering step S201, when the rear camera captures the QR code in a low-light environment, the front camera of the mobile terminal is activated. The payment intention judgment step S202 determines whether the user has the intention to pay based on the changes in the user's pupil image captured by the front camera and the amount of light detected by the front camera. In the QR code determination step S203, the target QR code selected by the user is determined from the plurality of QR codes based on the user's pupil gaze direction captured by the front-facing camera. In payment execution step S204, in response to the judgment result that the user has the intention to pay, the payment operation is completed based on the target QR code.

[0076] The QR code identification step S203 specifically includes the following sub-steps (not shown): Based on the event of capturing multiple QR codes, the front-facing camera of the mobile terminal emits infrared light; Acquire infrared reflection information of the infrared light from the user's pupil, wherein the infrared reflection information includes the infrared reflection angle information of the user's pupil and the center position information of the user's pupil; Based on the infrared reflection information (including the infrared reflection angle information of the user's pupil and the center position information of the user's pupil), the user's gaze position on the mobile terminal screen is determined and the QR code at the gaze position is identified as the target QR code.

[0077] Figure 4 This is a structural block diagram of a QR code payment system in a low-light environment according to the second embodiment of the present invention.

[0078] like Figure 4 As shown, the QR code payment system 200 in a low-light environment according to the second embodiment of the present invention includes: The rear camera 210 captures QR codes; The front-facing camera 220 captures images of the user's pupils and is used to detect the amount of light entering the camera. The activation trigger module 230 is used to activate the front camera when the rear camera captures a QR code in a low-light environment; The payment willingness judgment module 240 uses the user's pupil image captured by the front-facing camera and the amount of light detected by the front-facing camera to determine whether the user has the willingness to pay; The QR code determination module 250 determines the target QR code selected by the user from multiple QR codes based on the user's pupil gaze direction captured by the front-facing camera; and The payment execution module 260 completes the payment operation based on the target QR code, based on the judgment result indicating the willingness to pay.

[0079] The front-facing camera 220 further includes an infrared module (not shown), which is used to emit infrared rays and receive infrared reflection information (including infrared reflection angle information of the user's pupil and center position information of the user's pupil).

[0080] Third Implementation Method The third embodiment of the present invention also involves a scenario where multiple QR codes are captured by the rear camera. Unlike the second embodiment, it determines the target QR code by combining the gaze position obtained by the front camera with the QR code selected by the user in the real-world scene (or observed by the user in the real-world scene). Therefore, except for the QR code determination step, the remaining steps are the same as in the second embodiment.

[0081] In the third embodiment, the QR code determination step includes the following sub-steps: Based on the event of capturing multiple QR codes, the front-facing camera of the mobile terminal emits infrared light; Obtain the first infrared reflection information of the infrared light from the user's pupil; Based on the first infrared reflection information, the user's first gaze position on the mobile terminal screen is determined to select the first candidate QR code; After detecting that the user's gaze has left the mobile terminal screen and is looking at the target QR code in the real scene for a specified time based on the first infrared reflection information, the user's pupil reflects the infrared light in a second infrared reflection information. Based on the second infrared reflection information and the QR code orientation position obtained by the rear camera, the user's second gaze direction in the real scene is determined to select the second candidate QR code; and When it is determined that the relative positional relationship between the first candidate QR code and the second candidate QR code is consistent, the QR code is determined as the target QR code.

[0082] The determination that the relative positional relationship between the first candidate QR code and the second candidate QR code is consistent includes: Determine whether the position of the first candidate QR code on the screen of the mobile terminal relative to other QR codes is the same as the position of the second candidate QR code relative to the other QR codes in the real-world scenario.

[0083] As a specific example, the QR code identification process includes the following sub-steps: When the rear camera captures multiple QR codes, the front camera of the mobile terminal will emit infrared light. Based on the infrared reflection angle information of the user's pupil and the center position information of the user's pupil, determine the position of the user's gaze on the mobile terminal screen and determine the payment QR code A that the user is looking at on the mobile terminal screen (determine the screen gaze point: QR code A); The front-facing camera determines the user's gaze orientation in real time. When the user's gaze moves away from the mobile terminal screen and remains stable for a period of time, it uses the pupil's infrared reflection angle and pupil center position information to obtain the user's viewing direction of the QR code (that is, to determine that the user's eyes have left the QR code on the screen and are observing the QR code in the real scene). Based on the QR code's viewing direction in the real scene, combined with the viewing direction of the payment QR code captured by the rear camera, it determines that the payment QR code B selected by the user in the real scene is the QR code observed by the user's eyes in the real scene (determining the real-scene gaze point: QR code B); and To determine whether payment QR code A and payment QR code B are the same QR code, one method is to use relative position information. For example, if payment QR code A is the leftmost QR code among two QR codes, and payment QR code B is also the leftmost QR code among two QR codes, then payment QR code A and payment QR code B are considered to be the same QR code. If they match, then that QR code is used as the target QR code (QR code A / B cross-validation and final confirmation).

[0084] Fourth Implementation Method The fourth embodiment of the present invention also involves a scenario where multiple QR codes are captured by the rear camera. Unlike the second embodiment, the front camera does not need an infrared module; instead, it has a deep learning model. Therefore, except for the QR code determination step, the remaining steps are the same as in the second embodiment.

[0085] Therefore, in the fourth embodiment, the QR code determination step includes the following sub-steps: The user's pupil image captured by the front-facing camera is input into a pre-trained deep learning model (e.g., a convolutional neural network), in which the correspondence between the pupil image and the gaze orientation is pre-trained. The deep learning model outputs the user's gaze orientation corresponding to the pupil image; and The target QR code is determined from the plurality of QR codes based on the gaze orientation.

[0086] As described above, the QR code payment method and system for low-light environments of the present invention can determine the user's payment intention by capturing changes in the user's pupils using the front-facing camera of the mobile terminal and combining this with the amount of light entering the front-facing camera and the spatial position of the mobile terminal. Based on this, the system uses the pupil's infrared reflection angle and pupil center position information to determine the user's gaze position on the mobile phone screen, simultaneously combining this with the direction and position of the QR code in the user's observed scene, thereby determining the target QR code selected by the user.

[0087] The QR code payment method and system for low-light environments of the present invention no longer rely on explicit user commands. Instead, by comprehensively analyzing the user's physiological signals (pupil changes), environmental information (light intake), and behavioral characteristics (phone stability), it can intelligently distinguish whether the user wants to pay or simply view information. This fundamentally solves the problem of misoperation caused by the inability to understand the user's true intention in the prior art, making human-computer interaction more intelligent and humanized.

[0088] The QR code payment method and system in low-light environments of the present invention realize automatic selection in multi-code scenarios, improving payment efficiency. Specifically, by using high-precision gaze tracking technology, especially the screen and real scene (QR code A / QR code B) cross-verification mechanism, the target QR code that the user wants to pay can be automatically, quickly and accurately determined. The user no longer needs to manually click to select, and the entire operation process is greatly simplified, significantly improving the payment efficiency and smoothness in multi-code coexistence scenarios.

[0089] The QR code payment method and QR code payment system in low-light environments of the present invention can be applied to mobile terminals. Its application scenarios include, but are not limited to, the following: QR code payment for parking fees in low-light environments, QR code payment for shared bicycles in low-light environments, QR code payment for vending machines, QR code payment for street vendors, etc.

[0090] The above are merely specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Those skilled in the art can conceive of other feasible variations or substitutions based on the technical scope disclosed in the present invention, and such variations or substitutions are all covered within the scope of protection of the present invention. Where there is no conflict, the embodiments of the present invention and the features thereof can also be combined with each other. The scope of protection of the present invention is determined by the claims.

Claims

1. A QR code payment method for low-light environments, wherein the QR code payment method is applied to a mobile terminal equipped with a front-facing camera and a rear-facing camera, characterized in that, The QR code payment method includes the following steps: The triggering step is initiated when the rear camera captures the QR code in a low-light environment, and then the front camera of the mobile terminal is activated. The payment intention determination step determines whether the user has the intention to pay based on changes in the user's pupil image captured by the front-facing camera and the amount of light detected by the front-facing camera; and The payment execution step, in response to the judgment result that the user has the intention to pay, completes the payment operation based on the QR code.

2. The QR code payment method in low-light environments as described in claim 1, characterized in that, In the payment intention determination step, if the pupil in the pupil image continuously shrinks for a specified time and the amount of light entering the eye is greater than a pre-set first specified threshold, it is determined that the user has the intention to pay.

3. The QR code payment method in low-light environments as described in claim 1, characterized in that, In the payment intention determination step, if the pupil in the pupil image shrinks and then enlarges again and the amount of light entering the eye is less than a pre-set second predetermined threshold, it is determined that the user has the intention to pay.

4. The QR code payment method in low-light environments as described in claim 1, characterized in that, In the payment intention determination step, the user's willingness to pay is determined based on the pupil image captured by the front-facing camera, the amount of light detected by the front-facing camera, and the spatial position status of the mobile terminal.

5. The QR code payment method in low-light environments as described in claim 4, characterized in that, The spatial position state of the mobile terminal includes: the angular velocity and angular displacement of the mobile terminal.

6. The QR code payment method in low-light environments as described in claim 5, characterized in that, In the triggering step, if multiple QR codes are captured, the following further step is included between the payment intention determination step and the payment execution step: The QR code identification step involves determining the target QR code selected by the user from among the multiple QR codes based on the user's pupil gaze direction captured by the front-facing camera. In the payment execution step, the payment operation is performed based on the target QR code determined in the QR code determination step.

7. The QR code payment method in low-light environments as described in claim 6, characterized in that, The QR code determination steps include: Based on the event of capturing multiple QR codes, the front-facing camera of the mobile terminal emits infrared light; Obtain infrared reflection information of the infrared light from the user's pupils; Based on the infrared reflection information, the user's gaze position on the mobile terminal screen is determined, and the QR code at the gaze position is identified as the target QR code.

8. The QR code payment method in low-light environments as described in claim 6, characterized in that, The QR code determination steps include: Based on the event of capturing multiple QR codes, the front-facing camera of the mobile terminal emits infrared light; Obtain the first infrared reflection information of the infrared light from the user's pupil; Based on the first infrared reflection information, the user's first gaze position on the mobile terminal screen is determined to select the first candidate QR code; After detecting that the user's gaze has left the mobile terminal screen and is looking at the target QR code in the real scene for a specified time based on the first infrared reflection information, the user's pupil reflects the infrared light in a second infrared reflection information. Based on the second infrared reflection information and the QR code orientation position obtained by the rear camera, the user's second gaze direction in the real scene is determined to select the second candidate QR code; and When it is determined that the relative positional relationship between the first candidate QR code and the second candidate QR code is consistent, the QR code is determined as the target QR code.

9. The QR code payment method in low-light environments as described in claim 8, characterized in that, The determination that the relative positional relationship between the first candidate QR code and the second candidate QR code is consistent includes: Determine whether the position of the first candidate QR code on the screen of the mobile terminal relative to other QR codes is the same as the position of the second candidate QR code relative to the other QR codes in the real-world scenario.

10. The QR code payment method in low-light environments as described in claim 7, characterized in that, The infrared reflection information includes the infrared reflection angle information of the user's pupil and the center position information of the user's pupil.

11. The QR code payment method in low-light environments as described in claim 6, characterized in that, The QR code determination steps include: The user's pupil image captured by the front-facing camera is input into a pre-trained deep learning model, wherein the pre-trained deep learning model pre-trains the correspondence between the pupil image and the gaze orientation. The deep learning model outputs the user's gaze orientation corresponding to the pupil image; and The target QR code is determined from the plurality of QR codes based on the gaze orientation.

12. The QR code payment method in low-light environments as described in claim 1, characterized in that, The low-light environment includes an environment where the flash of the mobile terminal is turned on.

13. A QR code payment system for low-light environments, characterized in that, include: The rear camera is used to capture QR codes; The front-facing camera is used to capture images of the user's pupils and to detect the amount of light entering the camera. The activation trigger module is used to activate the front camera when the rear camera captures a QR code in a low-light environment. The payment willingness determination module determines whether the user has the willingness to pay based on the changes in the user's pupil image captured by the front-facing camera and the amount of light detected by the front-facing camera. as well as The payment execution module, in response to the judgment result that the user has the intention to pay, completes the payment operation based on the QR code.

14. The QR code payment system in low-light environments as described in claim 13, characterized in that, In the payment intention determination module, if the pupil of the user captured by the front-facing camera continuously decreases in size for a specified time and the amount of light detected by the front-facing camera is greater than a preset first specified threshold, it is determined that the user has the intention to pay.

15. The QR code payment system in low-light environments as described in claim 13, characterized in that, In the payment intention determination module, when the pupil of the user captured by the front-facing camera becomes smaller and then larger, and the amount of light detected by the front-facing camera is less than a pre-set second predetermined threshold, it is determined that the user has the intention to pay.

16. The QR code payment system in low-light environments as described in claim 13, characterized in that, In the payment intention determination module, the user's willingness to pay is determined based on the pupil image captured by the front-facing camera, the amount of light detected by the front-facing camera, and the spatial position status of the mobile terminal.

17. The QR code payment system in low-light environments as described in claim 15, characterized in that, As the spatial position state of the mobile terminal, the angular velocity and angular displacement of the mobile terminal are obtained through the gyroscope of the mobile terminal.

18. The QR code payment system in low-light environments as described in claim 13, characterized in that, Further includes: The QR code identification module determines the target QR code selected by the user from multiple QR codes based on the user's pupil gaze direction captured by the front-facing camera. The payment execution module performs a payment operation based on the target QR code determined in the QR code determination module.

19. The QR code payment system in low-light environments as described in claim 18, characterized in that, The front-facing camera further includes: an infrared module for emitting infrared light and receiving reflected infrared light information. The QR code determination module, based on the event of capturing multiple QR codes, causes the infrared module of the mobile terminal to emit infrared light. The infrared module of the front-facing camera acquires infrared reflection information of the infrared light from the user's pupils. The QR code determination module determines the user's gaze position on the mobile terminal screen based on the infrared reflection information and identifies the QR code at the gaze position as the target QR code.

20. The QR code payment system in low-light environments as described in claim 18, characterized in that, The front-facing camera further includes: an infrared module for emitting infrared light and receiving reflected infrared light information. The QR code determination module, based on the event of capturing multiple QR codes, causes the infrared module of the mobile terminal to emit infrared light. The infrared module of the front-facing camera acquires the first infrared reflection information of the infrared light from the user's pupil. The QR code determination module determines the user's first gaze position on the mobile terminal screen based on the first infrared reflection information to select the first candidate QR code. When the QR code determination module detects that the user's gaze has left the mobile terminal screen and is looking at the target QR code in the real scene for a specified time based on the first infrared reflection information, the infrared module of the front-facing camera acquires the second infrared reflection information of the user's pupils on the infrared light. Based on the second infrared reflection information and the QR code orientation position obtained by the rear camera, the QR code determination module determines the user's second gaze direction in the real scene to select the second candidate QR code. When it is determined that the relative positional relationship between the first candidate QR code and the second candidate QR code is consistent, the QR code is determined as the target QR code.

21. The QR code payment system in low-light environments as described in claim 20, characterized in that, The determination that the relative positional relationship between the first candidate QR code and the second candidate QR code is consistent includes: Determine whether the position of the first candidate QR code on the screen of the mobile terminal relative to other QR codes is the same as the position of the second candidate QR code relative to the other QR codes in the real-world scenario.

22. The QR code payment system in low-light environments as described in claim 20, characterized in that, The infrared reflection information includes the infrared reflection angle information of the user's pupil and the center position information of the user's pupil.

23. The QR code payment system in low-light environments as described in claim 18, characterized in that, The QR code determination module further includes a deep learning model. The user's pupil image captured by the front-facing camera is input into the deep learning model, wherein the deep learning model is pre-trained to have a correspondence between the pupil image and the gaze orientation. Based on the user's gaze orientation corresponding to the pupil image output by the deep learning model, the target QR code is determined from the plurality of QR codes.

24. A computer-readable medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the QR code payment method in low-light environments as described in any one of claims 1 to 12.

25. A computer device, comprising a storage module, a processor, and a computer program stored on the storage module and executable on the processor, characterized in that, When the processor executes the computer program, it implements the QR code payment method in low-light environment as described in any one of claims 1 to 12.

26. A computer program product, comprising a computer program, characterized in that, When executed by a processor, the computer program implements the QR code payment method in low-light environments as described in any one of claims 1 to 12.

Images