Intelligent terminal control method and intelligent terminal

Abstract

The invention discloses a control method of an intelligent terminal and the intelligent terminal, and relates to the technical field of intelligent terminals, and the control method comprises the following steps: S1, obtaining the eye gazing position of a user based on a camera, and converting the gazing direction into a specific position coordinate on a screen; s2, detecting a position where a user touches a screen based on a touch screen sensor, and obtaining coordinates of the touch position; s3, comparing the obtained coordinates of the watching position with the coordinates of the touch position, judging whether the watching position is within a range limited by the touch position, establishing a judgment range threshold value, and comparing; and S4, when judging that the watching position is consistent with the touch position, responding to the touch of the user, and executing operation control. In the aspect of interaction accuracy, the watching position coordinates acquired by the camera and the touch position coordinates of the touch screen are fused, so that the problem of inaccurate positioning of the target operation object caused by large partition of the touch screen is solved, the accuracy of touch response of the touch screen is improved, and misoperation is prevented.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent terminals, and in particular to a control method of an intelligent terminal and an intelligent terminal. Background Art

[0002] With the rapid development of information technology, smart terminal devices have been deeply integrated into people's daily lives and work scenes, becoming indispensable tools. Human-computer interaction is the core link for smart terminals to realize functions and services. The convenience, accuracy and intelligence of its interaction methods directly affect the user experience and the application efficiency of the device. At present, the touch operation method commonly used in smart terminals relies on direct contact between the user's fingers and the screen to trigger instructions. However, this interaction method has many limitations. In some special scenarios, such as when the user's hands are occupied and the flexibility of the fingers is limited, it is difficult to complete the touch operation smoothly; at the same time, for devices with larger screen sizes, one-handed operation often cannot reach the entire area of ​​the screen, and the hand posture needs to be adjusted frequently, which increases the user's operation burden and reduces efficiency. In addition, traditional touch interaction lacks the ability to predict the user's operation intentions. It only executes instructions based on the touch position, which is difficult to meet the user's demand for efficient and natural interaction. It is easy to make errors in the calculation of the operation object, which leads to misoperation. In this regard, we propose a control method and a smart terminal for smart terminals. Summary of the Invention

[0003] In order to solve the above technical problems, a control method of an intelligent terminal and an intelligent terminal are provided. This technical solution solves the above problems.

[0004] In order to achieve the above objects, the technical solution adopted by the present invention is: The control method of the intelligent terminal includes the following steps: S1. Obtain the user's eye gaze position based on the camera and convert the gaze direction into specific position coordinates on the screen; S2. Detecting the position where the user touches the screen based on the touch screen sensor, and obtaining the coordinates of the touched position; S3. Compare the acquired gaze position coordinates with the touch position coordinates to determine whether the gaze position is within the range defined by the touch position, establish a judgment range threshold, and perform a comparison; S4. When it is determined that the gaze position is consistent with the touch position, responding to the user's touch and performing operation control; S5. When it is determined that the gaze position is inconsistent with the touch position, the touch operation is not responded to, and the screen vibrates to remind the user. The user performs the touch operation again, and the control operation data is stored; S6. When determining whether the gaze position is consistent with the touch position, adaptively adjust the range threshold of the determination based on the user's usage habits and operation scenario factors.

[0005] Preferably, the position coordinate determination step in step S1 is: Acquire a facial image of a human face based on a camera, and extract eye features from the acquired facial image based on an eye detection algorithm; An eye model is built to describe the geometric structure and movement of the eye. Based on the position of the eye feature points and the eye model, the vector from the center of the eye to the gaze point is calculated, i.e., the gaze vector, which is the user's gaze direction. By displaying calibration points on the screen, letting the user look at the points, recording the eye features captured by the camera and the corresponding screen coordinates, establishing a mapping relationship between the gaze direction and the screen coordinates, and based on the mapping relationship, converting the calculated gaze direction into specific position coordinates on the screen.

[0006] Preferably, the eye feature extraction step is: After preprocessing the image captured by the camera, the face area is found in the preprocessed image, the face bounding box is determined, and the face is separated from the entire image; Within the located face region, the deep learning-based eye detection model determines the specific location of the eyes within the face region, obtains the eye bounding box, and narrows the processing scope. The eye area image is binarized to divide the image into foreground and background, and the eyeball is highlighted from the eye area. An edge detection algorithm is used to find the edge contour of the eyeball, obtain edge information, and analyze the edge information to determine the key feature points of the eyeball.

[0007] Preferably, the gaze direction determining step is: Use the combined model to simulate the structure of the real eye, define the model parameters, and determine the initial position and posture of the model in three-dimensional space; Based on the coordinates of the extracted eye feature points in the two-dimensional image, the eye feature points on the two-dimensional image are mapped to three-dimensional space through the inverse transformation of the perspective projection to obtain the three-dimensional coordinates of the feature points in the world coordinate system; Based on the established eye geometry model and the determined three-dimensional coordinates of the eye feature points, the center position of the eye in three-dimensional space is determined through geometric calculation; Set a target point on the screen as the gaze point, determine the actual gaze target position, and obtain the coordinates of the gaze point in three-dimensional space; Based on vector operations, the three-dimensional gaze vector is calculated with the center of the eye as the starting point and the gaze point as the end point. The user's gaze direction is determined by analyzing the direction of the gaze vector.

[0008] Preferably, the step of acquiring the coordinates of the touch position in step S2 is: When the user touches the touch screen, the signal acquisition circuit inside the touch screen collects the electrical signal generated by the sensor and converts it into a digital signal. The upper left corner of the screen is the origin (0, 0), the horizontal axis is the X axis, and the vertical axis is the Y axis. Process and calibrate the digital signal when the user touches, calculate the coordinates of the touch position, determine the touch point based on the position and intensity of the capacitance change, obtain the X and Y coordinates of the touch point in the touch screen coordinate system, and obtain the coordinate information of the touch position.

[0009] Preferably, the comparison step in step S3 is: Get the gaze position coordinates and touch position coordinates; The judgment range threshold is set based on experimental analysis. The range threshold is centered on the touch position and the maximum distance the gaze position is allowed to deviate from. Calculate the Euclidean distance between the gaze position and the touch position; The calculated Euclidean distance is compared with the set range threshold. If the distance is less than or equal to the threshold, the gaze position is determined to be within the range defined by the touch position; otherwise, it is determined to be out of the range.

[0010] Preferably, in step S4, when the judgment is consistent, the corresponding control logic is executed based on the operation corresponding to the touch position.

[0011] Preferably, the step of adaptively adjusting the judgment range threshold in step S6 is: Continuously collect data on the user's gaze position, touch position, and corresponding operation results; Record the current operation scenario and the operation status under different task types; When the system is initialized, a default judgment range threshold is set for each scene category; After each operation, evaluate the success rate of the operation. If the operation is successful, it means that the current threshold is appropriate. If the operation fails, the threshold needs to be adjusted. Dynamically adjust the threshold based on the operation success rate and user feedback. If the operation success rate is low, increase the threshold. A smooth adjustment strategy is adopted, and each adjustment is based on the proportional adjustment threshold; Regularly mine and analyze the collected user operation data.

[0012] Preferably, a certain number of recent operations are selected to calculate the success rate, and the calculation formula for the success rate is: number of successful operations / total number of operations.

[0013] A smart terminal, a control method applied to any of the above-mentioned smart terminals, includes: a camera, a touch screen, a vibration module, a storage unit and a sensor, wherein the camera is located directly above the touch screen, and the vibration module, storage unit and sensor are all located inside the smart terminal.

[0014] Compared with the prior art, the present invention has the following beneficial effects: In terms of interaction accuracy, the present invention integrates the gaze position coordinates obtained by the camera and the touch position coordinates of the touch screen to avoid misoperation; in terms of convenience, the system automatically responds to operations when the two are consistent, simplifying the process. The system can also adaptively adjust the judgment threshold based on user habits and scenarios to meet personalized needs. When the gaze and touch positions are inconsistent, the user is guided to make corrections through vibration prompts, and the operation data is stored for analysis and optimization, solving the problem of inaccurate positioning of the target operation object due to large touch screen partitions, improving the accuracy of touch response of the touch screen, and preventing misoperation. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 This is a control step flow chart of the present invention; Figure 2 Schematic diagram of the intelligent terminal of the present invention. DETAILED DESCRIPTION

[0016] The following description is intended to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments described below are merely examples, and those skilled in the art may conceive of other obvious variations.

[0017] Reference Figure 1 As shown, the control method of the intelligent terminal includes the following control steps: S1. Obtain the user's eye gaze position based on the camera and convert the gaze direction into specific position coordinates on the screen; S2. Detecting the position where the user touches the screen based on the touch screen sensor, and obtaining the coordinates of the touched position; S3. Compare the acquired gaze position coordinates with the touch position coordinates to determine whether the gaze position is within the range defined by the touch position, establish a judgment range threshold, and perform a comparison; S4. When it is determined that the gaze position is consistent with the touch position, responding to the user's touch and performing operation control; S5. When it is determined that the gaze position is inconsistent with the touch position, the touch operation is not responded to, and the screen vibrates to remind the user. The user performs the touch operation again, and the control operation data is stored; S6. When determining whether the gaze position is consistent with the touch position, adaptively adjust the range threshold of the determination based on the user's usage habits and operation scenario factors.

[0018] This application achieves a comprehensive improvement in interactive performance. In terms of interactive accuracy, the gaze position coordinates obtained by the camera and the touch position coordinates of the touch screen are integrated to avoid misoperation. In terms of convenience, the system automatically responds to operations when the two are consistent, simplifying the process. The system can also adaptively adjust the judgment threshold based on user habits and scenarios to meet personalized needs, such as providing interactive experiences of different accuracies in gaming and browsing scenarios. When the gaze and touch positions are inconsistent, the user is guided to make corrections through vibration prompts, and the operation data is stored for analysis and optimization. In addition, this method breaks the limitations of traditional interaction and helps expand the application of smart terminals in emerging fields of VR and AR. At the same time, it enhances the system's adaptive capabilities, dynamically optimizes interaction parameters according to user behavior and scene changes, and ensures stable and efficient interactive services under various usage conditions.

[0019] The steps for determining the position coordinates in step S1 are: Acquire a facial image of a human face based on a camera, and extract eye features from the acquired facial image based on an eye detection algorithm; An eye model is built to describe the geometric structure and movement of the eye. Based on the position of the eye feature points and the eye model, the vector from the center of the eye to the gaze point is calculated, i.e., the gaze vector, which is the user's gaze direction. By displaying calibration points on the screen, letting the user look at the points, recording the eye features captured by the camera and the corresponding screen coordinates, establishing a mapping relationship between the gaze direction and the screen coordinates, and based on the mapping relationship, converting the calculated gaze direction into specific position coordinates on the screen.

[0020] This application uses an eye detection algorithm to extract eye features from facial images, which can accurately capture subtle changes in the eyes. Combined with the established eye model, it calculates the gaze vector and quantifies eye movements into analyzable gaze direction data from a physiological structure level. On this basis, a mapping relationship between gaze direction and screen coordinates is established through calibration, which can accurately convert the user's gaze direction into screen position coordinates, effectively avoiding the problem of false touch caused by operational errors in traditional interaction methods, greatly improving the accuracy of interaction, and meeting the needs of scenes with extremely high positioning accuracy requirements for drawing design and precision operations.

[0021] The steps for eye feature extraction are: After preprocessing the image captured by the camera, the face area is found in the preprocessed image, the face bounding box is determined, and the face is separated from the entire image; Within the located face region, the deep learning-based eye detection model determines the specific location of the eyes within the face region, obtains the eye bounding box, and narrows the processing scope. The eye area image is binarized to divide the image into foreground and background, and the eyeball is highlighted from the eye area. An edge detection algorithm is used to find the edge contour of the eyeball, obtain edge information, and analyze the edge information to determine the key feature points of the eyeball.

[0022] The eye detection model based on deep learning determines the eye position: the input face area image is , a deep learning eye detection model After processing, output the bounding box coordinates of the eyes in the face area , expressed as: in are the coordinates of the upper left corner of the bounding box, It is the coordinate of the lower right corner of the bounding box, through which the eye area image can be extracted : Eye area image binarization processing: For the eye area image , set the binarization threshold to , using the binarization function Process the image and divide it into foreground (value ) and background (values ​​of ), and get the binary image : in Represents pixel coordinates in an image.

[0023] Edge detection algorithm finds the edge contour of the eyeball: Use the Canny edge detection algorithm to find the edge contour of the eyeball. , for the binary image Processing to obtain edge image : At the edge of the image The value is Pixels with a value of 0 represent edge points, and pixels with a value of 0 represent non-edge points. Analyze edge information to determine key feature points of the eye: Edge image For analysis, let the feature point detection function be By analyzing edge information (such as edge curvature and direction), we can determine the key feature points of the eyeball. , expressed as: in Indicates the The coordinates of the key feature points.

[0024] The steps to determine the gaze direction are: Use the combined model to simulate the structure of the real eye, define the model parameters, and determine the initial position and posture of the model in three-dimensional space; Based on the coordinates of the extracted eye feature points in the two-dimensional image, the eye feature points on the two-dimensional image are mapped to three-dimensional space through the inverse transformation of the perspective projection to obtain the three-dimensional coordinates of the feature points in the world coordinate system; Based on the established eye geometry model and the determined three-dimensional coordinates of the eye feature points, the center position of the eye in three-dimensional space is determined through geometric calculation; Set a target point on the screen as the gaze point, determine the actual gaze target position, and obtain the coordinates of the gaze point in three-dimensional space; Based on vector operations, the three-dimensional gaze vector is calculated with the center of the eye as the starting point and the gaze point as the end point. The user's gaze direction is determined by analyzing the direction of the gaze vector.

[0025] Use the combined model to simulate the structure of the real eye and determine the initial position and posture: Let the combined eye model be , the model parameters are , the initial position of the model in three-dimensional space is , the initial posture is the rotation matrix Indicates that: in It is an initialization function, which is used to determine the model and its initial state in three-dimensional space according to the model parameters; Map the eye feature points on the two-dimensional image to the three-dimensional space: Let the coordinate set of the extracted two-dimensional eye feature points be ,in Indicates the The coordinates of the feature points in the two-dimensional image, the intrinsic parameter matrix of the camera is , the external parameter matrix is and (Transformation from world coordinate system to camera coordinate system), through the inverse transformation of perspective projection, the two-dimensional feature points are mapped to three-dimensional space to obtain the three-dimensional coordinate set of the feature points in the world coordinate system ,in ; The inverse transformation formula is as follows: By solving the above equation (usually multiple characteristic points need to be solved simultaneously), we can get : in is the inverse projection function; Determine the center position of the eye in three-dimensional space: set the eye geometry model The geometric relationship function is , based on the determined three-dimensional coordinates of the eye feature points , determine the center position of the eye in three-dimensional space through geometric calculations : Get the coordinates of the gaze point in three-dimensional space: The coordinates of the target point (gaze point) set on the screen in the screen coordinate system are , also through the camera intrinsic parameter matrix , external parameter matrix and And the related spatial transformation, convert it to three-dimensional space, and get the coordinates of the gaze point in three-dimensional space: : in: Is a function that converts screen coordinates into three-dimensional space; Calculate the 3D gaze vector and determine the user's gaze direction: based on the eye center position As the starting point, the gaze point position As the end point, calculate the three-dimensional gaze vector : By looking at the vector Direction analysis to determine the user's gaze direction.

[0026] The steps for obtaining the coordinates of the touch position in step S2 are: When the user touches the touch screen, the signal acquisition circuit inside the touch screen collects the electrical signal generated by the sensor and converts it into a digital signal. The upper left corner of the screen is the origin (0, 0), the horizontal axis is the X axis, and the vertical axis is the Y axis. Process and calibrate the digital signal when the user touches, calculate the coordinates of the touch position, determine the touch point based on the position and intensity of the capacitance change, obtain the X and Y coordinates of the touch point in the touch screen coordinate system, and obtain the coordinate information of the touch position.

[0027] This application uses the touch screen's internal signal acquisition circuit to accurately collect sensor electrical signals, convert them into digital signals, and determine the touch point coordinates based on the position and intensity of the capacitance change, achieving sub-millimeter positioning accuracy. This high-precision positioning allows the system to accurately respond to commands when users perform delicate operations such as handwriting input, drawing design, and clicking small icons, effectively reducing false touches and significantly improving operational accuracy and interactive experience. The universal method of establishing a coordinate system with the upper left corner of the screen as the origin, and the touch detection principle based on capacitance changes, make this coordinate acquisition method applicable to various types of touch screen devices, including smartphones, tablets, smart car central control screens, and touch all-in-one computers.

[0028] The comparison steps in step S3 are: Get the gaze position coordinates and touch position coordinates; The judgment range threshold is set based on experimental analysis. The range threshold is centered on the touch position and the maximum distance the gaze position is allowed to deviate from. Calculate the Euclidean distance between the gaze position and the touch position; The calculated Euclidean distance is compared with the set range threshold. If the distance is less than or equal to the threshold, the gaze position is determined to be within the range defined by the touch position; otherwise, it is determined to be out of the range.

[0029] This application can accurately judge the user's true operation intention by accurately calculating the Euclidean distance between the gaze position and the touch position and comparing it with the set range threshold. The reasonably set range threshold provides a certain fault tolerance for user operations. When the user has a slight gaze or touch deviation during the operation, as long as the distance is within the threshold range, the system can still determine that the operation is valid, avoiding operation failure due to minor errors and reducing user frustration.

[0030] When the gaze position and touch position are determined to be consistent through step S3, the system enters the critical control logic execution stage. The system will quickly retrieve the pre-established "touch position-operation mapping table". This mapping table divides the screen into different areas according to the functional layout of the smart terminal and the user's operating habits, and associates specific operations with each area. In the main interface, the upper left corner area of ​​the screen corresponds to the "return to the previous menu" operation, and the bottom middle area corresponds to the "open the commonly used application list" operation. After retrieving the operation instructions corresponding to the touch position, the system parses and verifies the instructions. The parsing process converts the abstract operation instructions into specific codes or command parameters that can be executed by the computer; the verification process checks the legality and validity of the instructions to ensure that the operation can be executed under the current system state. For example, when playing a video, if the touch position corresponds to the "pause video" operation, but the video is currently in the paused state, the system will ignore the repeated instructions to avoid invalid operations.

[0031] The steps for adaptively adjusting the judgment range threshold in step S6 are: Continuously collect data on the user's gaze position, touch position, and corresponding operation results; Record the current operation scenario and the operation status under different task types; When the system is initialized, a default judgment range threshold is set for each scene category; After each operation, evaluate the success rate of the operation. If the operation is successful, it means that the current threshold is appropriate. If the operation fails, the threshold needs to be adjusted. Dynamically adjust the threshold based on the operation success rate and user feedback. If the operation success rate is low, increase the threshold. A smooth adjustment strategy is adopted, and each adjustment is based on the proportional adjustment threshold; Regularly mine and analyze the collected user operation data.

[0032] This application continuously collects user gaze position, touch position and operation result data, and combines it with operation scenario analysis to accurately locate the adaptation relationship between user operation habits and thresholds in different scenarios. By recording user feedback and analyzing operation success rates, the system can perceive each user's unique operation habits and preferences, set default thresholds for different scenario categories, and dynamically adjust based on real-time data, making the system highly adaptable.

[0033] Select a certain number of recent operations to calculate the success rate. The success rate calculation formula is: number of successful operations / total number of operations.

[0034] A smart terminal, a control method applied to any of the above-mentioned smart terminals, includes: a camera, a touch screen, a vibration module, a storage unit and a sensor, wherein the camera is located directly above the touch screen, and the vibration module, storage unit and sensor are all located inside the smart terminal.

[0035] The camera of this application is located directly above the touch screen, which can accurately capture the user's eye information and provide clear image data for determining the coordinates of the gaze position. Combined with the touch screen, it realizes dual interactive verification based on gaze and touch, reduces misoperation, and integrates a vibration module. When the gaze position is inconsistent with the touch position, it can promptly give the user intuitive feedback through vibration to guide the user to re-operate.

[0036] The basic principles, main features, and advantages of the present invention are shown and described above. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions only describe the principles of the present invention. Various changes and improvements are possible without departing from the spirit and scope of the present invention, and such changes and improvements fall within the scope of the invention as claimed.

Claims

1. A control method for an intelligent terminal, characterized in that: The control steps are: S1. Obtain the user's eye gaze position based on the camera and convert the gaze direction into specific position coordinates on the screen; S2. Detecting the position where the user touches the screen based on the touch screen sensor, and obtaining the coordinates of the touched position; S3. Compare the acquired gaze position coordinates with the touch position coordinates to determine whether the gaze position is within the range defined by the touch position, establish a judgment range threshold, and perform a comparison; S4. When it is determined that the gaze position is consistent with the touch position, responding to the user's touch and performing operation control; S5. When it is determined that the gaze position is inconsistent with the touch position, the touch operation is not responded to, and the screen vibrates to remind the user. The user performs the touch operation again, and the control operation data is stored; S6. When determining whether the gaze position is consistent with the touch position, adaptively adjust the range threshold of the determination based on the user's usage habits and operation scenario factors.

2. The control method of the intelligent terminal according to claim 1, characterized in that: The steps for determining the position coordinates in step S1 are: Acquire a facial image of a human face based on a camera, and extract eye features from the acquired facial image based on an eye detection algorithm; An eye model is built to describe the geometric structure and movement of the eye. Based on the position of the eye feature points and the eye model, the vector from the center of the eye to the gaze point is calculated, i.e., the gaze vector, which is the user's gaze direction. By displaying calibration points on the screen, letting the user look at the points, recording the eye features captured by the camera and the corresponding screen coordinates, establishing a mapping relationship between the gaze direction and the screen coordinates, and based on the mapping relationship, converting the calculated gaze direction into specific position coordinates on the screen.

3. The control method of the intelligent terminal according to claim 2, characterized in that: The steps for eye feature extraction are: After preprocessing the image captured by the camera, the face area is found in the preprocessed image, the face bounding box is determined, and the face is separated from the entire image; Within the located face region, the deep learning-based eye detection model determines the specific location of the eyes within the face region, obtains the eye bounding box, and narrows the processing scope. The eye area image is binarized to divide the image into foreground and background, and the eyeball is highlighted from the eye area. An edge detection algorithm is used to find the edge contour of the eyeball, obtain edge information, and analyze the edge information to determine the key feature points of the eyeball.

4. The control method of the intelligent terminal according to claim 2, characterized in that: The steps to determine the gaze direction are: Use the combined model to simulate the structure of the real eye, define the model parameters, and determine the initial position and posture of the model in three-dimensional space; Based on the coordinates of the extracted eye feature points in the two-dimensional image, the eye feature points on the two-dimensional image are mapped to three-dimensional space through the inverse transformation of the perspective projection to obtain the three-dimensional coordinates of the feature points in the world coordinate system; Based on the established eye geometry model and the determined three-dimensional coordinates of the eye feature points, the center position of the eye in three-dimensional space is determined through geometric calculation; Set a target point on the screen as the gaze point, determine the actual gaze target position, and obtain the coordinates of the gaze point in three-dimensional space; Based on vector operations, the three-dimensional gaze vector is calculated with the center of the eye as the starting point and the gaze point as the end point. The user's gaze direction is determined by analyzing the direction of the gaze vector.

5. The control method of the intelligent terminal according to claim 1, characterized in that: The steps for obtaining the coordinates of the touch position in step S2 are: When the user touches the touch screen, the signal acquisition circuit inside the touch screen collects the electrical signal generated by the sensor and converts it into a digital signal. The upper left corner of the screen is the origin (0, 0), the horizontal axis is the X axis, and the vertical axis is the Y axis. Process and calibrate the digital signal when the user touches, calculate the coordinates of the touch position, determine the touch point based on the position and intensity of the capacitance change, obtain the X and Y coordinates of the touch point in the touch screen coordinate system, and obtain the coordinate information of the touch position.

6. The control method of the intelligent terminal according to claim 1, characterized in that: The comparison steps in step S3 are: Get the gaze position coordinates and touch position coordinates; The judgment range threshold is set based on experimental analysis. The range threshold is centered on the touch position and the maximum distance the gaze position is allowed to deviate from. Calculate the Euclidean distance between the gaze position and the touch position; Compare the calculated Euclidean distance with the set range threshold. If the distance is less than or equal to the threshold, the gaze position is determined to be within the range defined by the touch position. Otherwise, it is judged to be out of range.

7. The control method of the intelligent terminal according to claim 1, characterized in that: In step S4, when the judgment is consistent, the corresponding control logic is executed based on the operation corresponding to the touch position.

8. The control method of the intelligent terminal according to claim 1, characterized in that: The steps for adaptively adjusting the judgment range threshold in step S6 are: Continuously collect data on the user's gaze position, touch position, and corresponding operation results; Record the current operation scenario and the operation status under different task types; When the system is initialized, a default judgment range threshold is set for each scene category; After each operation, evaluate the success rate of the operation. If the operation is successful, it means that the current threshold is appropriate. If the operation fails, the threshold needs to be adjusted. Dynamically adjust the threshold based on the operation success rate and user feedback. If the operation success rate is low, increase the threshold. A smooth adjustment strategy is adopted, and each adjustment is based on the proportional adjustment threshold; Regularly mine and analyze the collected user operation data.

9. The control method of the intelligent terminal according to claim 8, characterized in that: Select a certain number of recent operations to calculate the success rate. The success rate calculation formula is: number of successful operations / total number of operations.

10. A smart terminal, applied to the control method of any one of claims 1 to 9, characterized in that: include: The camera, touch screen, vibration module, storage unit and sensor are located inside the smart terminal.

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