Zoom lens based on wireless remote adjustment and control method thereof

Abstract

The invention discloses a zoom lens based on wireless remote adjustment and a control method thereof. The zoom lens comprises a data acquisition and transmission module, a control mechanism and a remote adjustment execution module. Comprehensive environment information is obtained based on the surrounding environment parameters and the external environment parameters; the control mechanism comprises an environment prediction model and a lens performance prediction model; the environment prediction model predicts an environment parameter change trend to obtain environment prediction information of a specified time period; the lens performance prediction model predicts the adaptability of the zoom lens to the environment and the imaging effect, and lens performance prediction information is obtained; judging whether the current lens parameter setting meets a preset imaging effect index in a specified time period or not; generating lens parameter adjustment information and triggering a lens adjustment instruction to a remote adjustment execution module; the remote adjustment execution module executes a corresponding lens parameter adjustment operation; according to the invention, wireless remote adjustment of the zoom lens can be realized conveniently, and the stability and accuracy of the lens adjustment state are improved.

Description

Technical Field

[0001] The present application relates to the technical field of zoom lenses, and in particular to a zoom lens based on wireless remote adjustment and a control method thereof. Background Art

[0002] In modern security monitoring, remote observation and scientific research, cameras are key devices for obtaining image information. The accuracy and flexibility of their focus and zoom functions directly determine the imaging quality and application effect. With the continuous advancement of technology, the requirements for cameras are no longer limited to basic image capture, but also require them to be able to quickly and accurately adjust the focal length, focus and aperture under complex and changing environmental conditions to adapt to shooting needs at different distances and lighting conditions.

[0003] Camera focus and zoom adjustment are important means to ensure image clarity and capture target details. Focus adjustment can ensure that the camera accurately focuses on the target object to achieve the clearest image; while zoom adjustment allows the camera to change the shooting angle and range within a certain range, thereby achieving flexible monitoring and observation of targets at different distances; traditional zoom lenses mostly use manual adjustment, that is, adjusting the focal length and focus by rotating the focus ring or zoom ring on the lens; however, this method has many inconveniences, such as difficult to control adjustment accuracy, cumbersome operation, and long time consumption. Especially in application scenarios where frequent adjustment of focal length and focus is required, manual adjustment is particularly inefficient and inconvenient.

[0004] The adjustment state of the zoom lens is not only affected by the operator's technical level, but also by a variety of environmental factors such as ambient temperature, humidity, vibration, etc. These factors may cause slight changes in the internal mechanical structure of the lens, thereby affecting the accuracy of focal length and focus.

[0005] In summary, the zoom lens in the prior art has many deficiencies in the lens adjustment state, especially the adjustment effect of the infrared zoom lens under complex environmental conditions is even more difficult to guarantee; these problems seriously restrict the application effect of the camera in the fields of security monitoring, remote observation, etc.; therefore, how to realize the wireless remote adjustment of the zoom lens and improve the stability and accuracy of the lens adjustment state has become a technical problem that needs to be solved urgently. Summary of the invention

[0006] In order to facilitate wireless remote adjustment of a zoom lens and improve the stability and accuracy of the lens adjustment state, the present application provides a zoom lens based on wireless remote adjustment and a control method thereof.

[0007] In the first aspect, the invention objective of the present application is achieved by adopting the following technical solutions: A zoom lens based on wireless remote adjustment, comprising a data acquisition and transmission module, a control mechanism and a remote adjustment execution module; The data acquisition and transmission module has a built-in sensor for collecting ambient environment parameters, receives external environment parameters through a wireless communication interface, and obtains comprehensive environmental information based on the ambient environment parameters and external environment parameters; The control mechanism includes an environment prediction model and a lens performance prediction model; in the environment prediction model, a prediction of a change trend of environmental parameters is performed based on the comprehensive environment information to obtain environment prediction information for a specified time period; in the lens performance prediction model, based on the comprehensive environment information, the environment prediction information and the current lens ecological health, the adaptability of the zoom lens to the environment and the imaging effect under different zoom settings are predicted respectively to obtain lens performance prediction information for a specified time period; The control mechanism analyzes the environment prediction information and the lens performance prediction information to determine whether the current lens parameter setting meets the preset imaging effect index in the specified time period; generates lens parameter adjustment information according to the judgment result; and triggers the lens adjustment instruction to the remote adjustment execution module based on the lens parameter adjustment information; The remote adjustment execution module executes a corresponding lens parameter adjustment operation based on the lens parameter adjustment information.

[0008] By adopting the above technical solution, the zoom lens of the present application is provided with a remote adjustment execution module for performing wireless remote adjustment operations and a data communication interface capable of data transmission interaction. In actual application, the remote adjustment execution module is configured as a control circuit board for Bluetooth wireless communication, which is arranged in the dimming circle of the zoom lens; the wireless remote adjustment of the zoom lens is facilitated by the control mechanism and the remote adjustment execution module, and the automated and intelligent adjustment method is conducive to improving the adjustment efficiency of the zoom lens.

[0009] Specifically, in order to improve the stability and accuracy of the lens adjustment state, the present application considers that the zoom lens is easily affected by environmental changes (especially the interference of various environmental factors such as temperature, humidity, vibration, etc. of the infrared zoom lens environment). The environmental changes are fully captured through the data acquisition sensor module (the data acquisition sensor module has a built-in temperature and humidity sensor, a light intensity sensor, and an air pressure sensor, etc.), and the data from different sensors are integrated and analyzed to improve the accuracy and reliability of the comprehensive environmental information. Then the environmental prediction model predicts future environmental changes, so that the lens performance prediction model can predict the lens performance of the specified time period in real time according to the environmental prediction information and the current actual lens ecological health (wherein the lens ecological health is used to indicate the health status of the parts of each adjustment component of the lens), and obtain the lens performance prediction information. By analyzing the environmental impact and the lens ecological health, the control effect of the zoom lens is explored from multiple angles, effectively reducing the occurrence of slight changes in the internal mechanical structure of the lens, thereby affecting the accuracy of the focal length and focus, and the lens parameters of the zoom lens are targetedly controlled, which is conducive to improving the stability and accuracy of the lens adjustment state.

[0010] In addition, in order to carry out fine-grained monitoring of the lens adjustment status and each lens parameter, the control mechanism of the present application will also analyze the environmental prediction information and the lens performance prediction information to determine whether the current lens parameter settings meet the preset imaging effect indicators in the specified time period. The imaging effect indicators are set based on the preset imaging quality indicators, light utilization efficiency and energy consumption balance indicators. When the lens status data of the zoom lens does not meet the expected effect, the lens parameter adjustment information will also be obtained, and the lens parameter adjustment operation will be executed in time through the remote adjustment execution module. That is, when there is a deviation in the lens adjustment state, the lens parameters will be fine-tuned immediately to ensure that the lens state is always maintained in the best state, thereby improving the stability and accuracy of the lens adjustment state.

[0011] In a preferred example of the present application: the environmental prediction model is obtained by: Collecting historical environmental data of the area where the zoom lens is located, the historical environmental data including time series data of temperature, humidity, light intensity, air pressure and wind speed; Based on the historical environmental data, combined with meteorological principles and statistical methods, model training is performed to predict the changing trend of environmental parameters within a specified time period in the future and generate an environmental prediction model; The lens performance prediction model is obtained by: Collect historical performance data of zoom lenses, the historical performance data including imaging quality parameters of lenses with different zoom settings, lens ecological health indicators, and corresponding environmental condition data; Based on the historical performance data and environmental condition data, combined with optical imaging principles and machine learning algorithms, model training is performed to predict the environmental conditions and lens imaging effects of the zoom lens under different zoom settings in a specified future time period, and generate a lens performance prediction model.

[0012] By adopting the above technical solution, the environmental prediction model established based on historical data can more accurately predict the changing trend of future environmental parameters and the imaging effect of the lens under different conditions, providing a reliable basis for the adjustment of lens parameters; the lens performance prediction model based on the specified time period is conducive to tracking the state of the zoom lens as the environment changes within the specified time period, and predicting the lens performance, which is conducive to intelligent control of the zoom lens.

[0013] In a preferred example of the present application: before triggering the lens adjustment instruction to the remote adjustment execution module based on the lens parameter adjustment information, the control mechanism further includes: Acquire physical characteristic parameters of the zoom lens, wherein the physical characteristic parameters include the focal length range, zoom speed, and lens structure parameters of the lens, and establish a physical model of the lens; Obtain historical lens adjustment records and imaging effect feedback information, analyze the differences in imaging effects corresponding to different zoom settings, and establish a lens image conversion model based on the physical model of the lens; The environmental prediction information, the lens performance prediction information and the current lens ecological health are used as inputs of the lens image conversion model, and lens parameter adjustment information is generated according to the judgment result.

[0014] By adopting the above technical solution, the lens portrait conversion model combines the physical characteristic parameters, historical adjustment records and imaging effect feedback of the lens, so as to more comprehensively reflect the actual state of the lens, thereby generating more accurate lens parameter adjustment information. The lens portrait conversion model can be customized and adjusted according to different types of lenses, different external environments and different user needs, thereby improving the applicability and flexibility of the zoom lens control system.

[0015] In the second aspect, the invention objective of the present application is achieved by adopting the following technical solutions: A zoom lens control method based on wireless remote adjustment, The data acquisition and transmission module collects ambient environment parameters and receives external environment parameters, and obtains comprehensive environmental information based on the ambient environment parameters and external environment parameters; In the environmental prediction model, the change trend of environmental parameters is predicted based on the comprehensive environmental information to obtain environmental prediction information for a specified time period; in the lens performance prediction model, the adaptability of the zoom lens to the environment and the imaging effect under different zoom settings are predicted based on the comprehensive environmental information, the environmental prediction information and the current lens ecological health, to obtain lens performance prediction information for a specified time period; Analyze the environment prediction information and the lens performance prediction information to determine whether the current lens parameter settings meet the preset imaging effect indicators in the specified time period; generate lens parameter adjustment information according to the determination result; and trigger a lens adjustment instruction based on the lens parameter adjustment information; A corresponding lens parameter adjustment operation is performed based on the lens parameter adjustment information.

[0016] By adopting the above technical solutions, combined with data collection, environmental prediction, lens performance prediction and parameter adjustment steps, intelligent control of zoom lenses can be achieved; through wireless remote adjustment, manual intervention is reduced and adjustment efficiency is improved, and combined with environmental prediction information, environmental changes can be predicted in advance and lens parameters can be adjusted, which is conducive to ensuring that the lens can maintain the best imaging effect under different environmental conditions or in complex and changeable environments. The lens performance prediction model predicts the imaging effects under different zoom settings based on comprehensive environmental information and the ecological health of the lens, effectively improving the imaging quality of the lens.

[0017] In a preferred example of the present application: before performing the corresponding lens parameter adjustment operation based on the lens parameter adjustment information, the method includes: In the preset lens image conversion model, the current lens parameter settings and historical adjustment records of the zoom lens are obtained; Formulate a lens parameter adjustment strategy based on the lens parameter adjustment information and in combination with the physical characteristics and operation limitations of the lens, wherein the lens parameter adjustment strategy includes a zoom speed, an adjustment sequence, an adjustment step length, and a sensitivity adjustment interval; In the lens performance prediction model, simulated adjustment is performed based on the lens parameter adjustment strategy to obtain a simulated adjustment result; Based on the simulation adjustment result, optimizing the lens parameter adjustment strategy until the preset imaging effect index is met; The lens parameter adjustment information corresponding to the final lens parameter adjustment strategy is sent to the corresponding remote adjustment execution module.

[0018] By adopting the above technical solution, the present application adds the specification and optimization process of the lens parameter adjustment strategy to ensure that the lens parameter adjustment strategy meets the preset imaging effect indicators, thereby improving the stability and reliability of the lens imaging state; by simulating the adjustment and optimization process, the number of unnecessary adjustments is reduced, which is beneficial to reducing unnecessary losses to the zoom lens and related equipment, and facilitating the use and maintenance of the zoom lens.

[0019] In a preferred example of the present application, the combined analysis of the environmental prediction information and the lens performance prediction information to determine whether the current lens parameter setting meets the preset imaging effect index in the specified time period includes: Matching the key environmental parameters in the environmental prediction information with the environmental adaptability index in the lens performance prediction model to evaluate the possible impact of the environment on the lens performance effect; the key environmental parameters include temperature, humidity and light intensity; In the lens performance prediction model, the imaging effect of the lens under different zoom settings under predicted environmental conditions is simulated, and the imaging effect includes imaging indicators of clarity, contrast and color reproduction; Compare the simulated imaging effect with the preset imaging effect index one by one; When any simulated imaging effect does not meet the preset imaging effect index, lens parameter adjustment suggestion information is generated and output.

[0020] By adopting the above technical solution, the present application analyzes the combined environmental prediction information and lens performance information to determine whether the current lens parameters meet the preset imaging effect indicators, and generates lens parameter adjustment suggestion information; by matching key environmental parameters with environmental adaptability indicators, the judgment accuracy and efficiency of whether the current lens parameter settings are sufficient to meet the imaging effect indicators are determined, and when any simulated imaging effect does not meet the preset imaging effect indicators, lens parameter adjustment suggestion information is generated, which is conducive to timely discovery of problems and timely adjustments, thereby improving the stability of the high imaging quality of the zoom lens.

[0021] In a preferred example of the present application: the method further comprises: fusing the physical model and the lens performance prediction model to generate a lens image conversion model; The fusion physical model and the lens performance prediction model are used to generate a lens image conversion model, and the lens image conversion model is generated, including: Based on the physical model and the lens performance prediction model, key parameters and adjustable parameters are selected as fusion points, and based on a preset model fusion algorithm, the physical model and the lens performance prediction model are fused to obtain an initial lens image conversion model; The current state parameters and external environment parameters of the zoom lens are obtained as inputs of an initial lens portrait conversion model, and the initial lens portrait conversion model is trained and optimized based on a preset lens portrait training data set to obtain a lens portrait conversion model; wherein the lens portrait training data includes lens portraits of different types of zoom lenses in different environments, and the lens portraits include imaging effect predictions, environmental adaptability assessments, and lens health status evaluations of the zoom lens under different zoom settings.

[0022] By adopting the above technical solution, the lens portrait conversion model generated by integrating the physical model and the lens performance prediction model can more comprehensively reflect the physical characteristics and performance of the lens. By training and optimizing the model, the prediction accuracy of the lens portrait conversion model for the lens imaging effect under future environmental conditions is improved.

[0023] In the third aspect, the invention objective of the present application is achieved by adopting the following technical solutions: A computer device comprises a memory, a processor and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the zoom lens control method based on wireless remote adjustment are implemented.

[0024] In a fourth aspect, the invention objective of the present application is achieved by adopting the following technical solutions: A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the zoom lens control method based on wireless remote adjustment are implemented.

[0025] In summary, the present application includes at least one of the following beneficial technical effects: 1. The zoom lens of the present application is provided with a remote adjustment execution module for performing wireless remote adjustment operations and a data communication interface capable of data transmission interaction. In actual application, the remote adjustment execution module is configured as a control circuit board for Bluetooth wireless communication, which is arranged in the dimming circle of the zoom lens; the wireless remote adjustment of the zoom lens is facilitated by the control mechanism and the remote adjustment execution module, and the automated and intelligent adjustment method is conducive to improving the adjustment efficiency of the zoom lens; specifically, in order to improve the stability and accuracy of the lens adjustment state, the present application considers that the zoom lens is easily affected by environmental changes (especially the interference of various environmental factors such as the ambient temperature, humidity, and vibration of the infrared zoom lens), and comprehensively captures the data through a data acquisition sensor module (the data acquisition sensor module has a built-in temperature and humidity sensor, a light intensity sensor, and an air pressure sensor, etc.) It can grasp environmental changes and integrate and analyze data from different sensors to improve the accuracy and reliability of comprehensive environmental information. Then, the environmental prediction model predicts future environmental changes, so that the lens performance prediction model can predict the lens performance of a specified time period in real time based on the environmental prediction information and the current actual lens ecological health (where the lens ecological health is used to indicate the health status of each lens adjustment component). The lens performance prediction information is obtained. By analyzing the environmental impact and lens ecological health, the control effect of the zoom lens is explored from multiple angles, effectively reducing the occurrence of minor changes in the internal mechanical structure of the lens, which in turn affects the accuracy of the focal length and focus. The lens parameters of the zoom lens are targeted for control, which is conducive to improving the stability and accuracy of the lens adjustment state. 2. This application adds the designation and optimization process of the lens parameter adjustment strategy to ensure that the lens parameter adjustment strategy meets the preset imaging effect index, thereby improving the stability and reliability of the lens imaging state; through the simulation adjustment and optimization process, the number of unnecessary adjustments is reduced, which is conducive to reducing unnecessary losses to the zoom lens and related equipment, and facilitating the use and maintenance of the zoom lens; 3. The lens portrait conversion model generated by integrating the physical model and the lens performance prediction model can more comprehensively reflect the physical characteristics and performance of the lens. By training and optimizing the model, the prediction accuracy of the lens portrait conversion model for the lens imaging effect under future environmental conditions is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 It is a principle block diagram of a zoom lens based on wireless remote adjustment in one embodiment of the present application; Figure 2 is a flow chart of a zoom lens control method based on wireless remote adjustment in one embodiment of the present application; Figure 3This is a flow chart before step S4 in a zoom lens control method based on wireless remote adjustment in an embodiment of the present application; Figure 4 is a flow chart of step S3 in a zoom lens control method based on wireless remote adjustment in one embodiment of the present application; Figure 5 It is a schematic diagram of a device in an embodiment of the present application. DETAILED DESCRIPTION

[0027] The present application is further described in detail below in conjunction with the accompanying drawings.

[0028] In one embodiment, if Figure 1 As shown, the present application discloses a zoom lens based on wireless remote adjustment, which includes a data acquisition and transmission module, a control mechanism and a remote adjustment execution module; the data acquisition and transmission module has a built-in sensor for collecting surrounding environment parameters, and receives external environment parameters through a wireless communication interface, and obtains comprehensive environmental information based on the surrounding environment parameters and external environment parameters.

[0029] The control mechanism includes an environment prediction model and a lens performance prediction model; the environment prediction model is obtained by: Collect historical environmental data of the area where the zoom lens is located, including time series data of temperature, humidity, light intensity, air pressure and wind speed; conduct model training based on historical environmental data, combined with meteorological principles and statistical methods, predict the changing trend of environmental parameters in a specified time period in the future, and generate an environmental prediction model.

[0030] The lens performance prediction model is obtained in the following way: Collect historical performance data of zoom lenses, including imaging quality parameters of lenses with different zoom settings, lens ecological health indicators, and corresponding environmental condition data; conduct model training based on historical performance data and environmental condition data, combined with optical imaging principles and machine learning algorithms (such as neural networks and random forests), to predict the predicted environmental conditions and lens imaging effects of zoom lenses under different zoom settings in a specified time period in the future, and generate a lens performance prediction model.

[0031] In the environmental prediction model, the trend of environmental parameter changes is predicted based on the comprehensive environmental information to obtain the environmental prediction information for a specified time period; in the lens performance prediction model, the adaptability of the zoom lens to the environment and the imaging effect under different zoom settings are predicted based on the comprehensive environmental information, the environmental prediction information and the current lens ecological health, to obtain the lens performance prediction information for a specified time period; the control mechanism analyzes the environmental prediction information and the lens performance prediction information to determine whether the current lens parameter settings meet the preset imaging effect indicators in the specified time period; generates lens parameter adjustment information based on the judgment result; based on the lens parameter adjustment information, triggers the lens adjustment instruction to the remote adjustment execution module; the remote adjustment execution module executes the corresponding lens parameter adjustment operation based on the lens parameter adjustment information.

[0032] In this embodiment, based on the lens parameter adjustment information, before triggering the lens adjustment instruction to the remote adjustment execution module, the control mechanism further includes: The physical characteristic parameters of the zoom lens, including the focal length range, zoom speed, and lens structure parameters of the lens, are obtained to establish a physical model of the lens; historical lens adjustment records and imaging effect feedback information are obtained, and the differences in imaging effects corresponding to different zoom settings are analyzed, and a lens portrait conversion model is established in combination with the physical model of the lens; environmental prediction information, lens performance prediction information, and the current lens ecological health are used as inputs to the lens portrait conversion model, and lens parameter adjustment information is generated based on the judgment results.

[0033] The implementation principle of a zoom lens based on wireless remote adjustment in an embodiment of the present application is as follows: the zoom lens of the present application is provided with a remote adjustment execution module for executing wireless remote adjustment operations and a data communication interface capable of data transmission interaction. In actual application, the remote adjustment execution module is configured as a control circuit board for Bluetooth wireless communication, which is arranged in the dimming circle of the zoom lens; the wireless remote adjustment of the zoom lens is facilitated by the control mechanism and the remote adjustment execution module, and the automated and intelligent adjustment method is conducive to improving the adjustment efficiency of the zoom lens; specifically, in order to improve the stability and accuracy of the lens adjustment state, the present application considers that the zoom lens is easily affected by environmental changes (especially the interference of various environmental factors such as ambient temperature, humidity, vibration, etc. of the infrared zoom lens), and uses a data acquisition sensor module (the data acquisition sensor module has built-in temperature and humidity sensors, light intensity sensors, etc.) The lens performance prediction model can predict the lens performance of a specified time period in real time based on the environmental prediction information and the current actual lens ecological health (where the lens health ecological health is used to indicate the health status of each adjustment component of the lens). The lens performance prediction information is obtained. By analyzing the environmental impact and lens health ecological health, the control effect of the zoom lens is explored from multiple angles, effectively reducing the occurrence of slight changes in the internal mechanical structure of the lens, which in turn affects the accuracy of the focal length and focus. The lens parameters of the zoom lens are controlled in a targeted manner, which is beneficial to improving the stability and accuracy of the lens adjustment state.

[0034] In one embodiment, a zoom lens control method based on wireless remote adjustment is provided. The zoom lens control method based on wireless remote adjustment is applied to the zoom lens based on wireless remote adjustment as described above.

[0035] like Figure 2 As shown, a zoom lens control method based on wireless remote adjustment specifically includes the following steps: S1: Collect surrounding environment parameters through the data acquisition and transmission module, and receive external environment parameters, and obtain comprehensive environmental information based on the surrounding environment parameters and external environment parameters.

[0036] In this embodiment, the surrounding environment parameters include temperature, humidity, light intensity, wind speed, etc. A sensor network is deployed around the zoom lens to collect the surrounding environment parameters. External environment parameters such as weather forecast data are received from an external system through a wireless communication interface (such as Wi-Fi, Bluetooth, LoRa). Comprehensive environmental information is obtained by integrating data based on the surrounding environment parameters and external environment parameters.

[0037] S2: In the environmental prediction model, the changing trend of environmental parameters is predicted based on the comprehensive environmental information to obtain the environmental prediction information for a specified time period; in the lens performance prediction model, the adaptability of the zoom lens to the environment and the imaging effect under different zoom settings are predicted based on the comprehensive environmental information, the environmental prediction information and the current ecological health of the lens to obtain the lens performance prediction information for a specified time period.

[0038] In this embodiment, the ecological health of the lens refers to the hardware health of each component of the lens, and the health is assessed based on the functions and applicability of different components. The ecological health of the lens includes the durability of the mechanical structure, the service life of the lens, the focusing speed, the zooming speed, the stability of the lens performance, etc. In the environmental prediction model, a machine learning algorithm (such as LSTM, ARIMA) is used to perform a time series analysis on the comprehensive environmental information to predict the changing trend of environmental parameters within a specified time period in the future; in the lens performance prediction model, the comprehensive environmental information, the environmental prediction information and the current ecological health of the lens are combined to simulate the imaging process under different zoom settings to predict the imaging effect (clarity, contrast, color reproduction, etc.) of the lens in different environments.

[0039] Specifically, based on the environmental prediction information and the historical performance data of the lens under different zoom settings, the adaptability of the zoom lens to the environment under different zoom settings, including focusing speed and stability, is predicted; by combining the lens performance parameters (such as resolution, distortion rate), environmental prediction information and the current ecological health of the lens, image processing algorithms are used to predict imaging effects, such as clarity and color reproduction.

[0040] S3: Analyze the combined environment prediction information and lens performance prediction information to determine whether the current lens parameter settings meet the preset imaging effect indicators in the specified time period; generate lens parameter adjustment information based on the judgment result; and trigger a lens adjustment instruction based on the lens parameter adjustment information.

[0041] In this embodiment, the imaging effect index includes a clarity threshold, color reproduction requirements, and contrast requirements, etc. The lens parameter adjustment information includes zoom settings, exposure compensation, white balance adjustment, etc. Through wireless communication technology, the lens adjustment instruction is sent to the zoom lens control system to trigger the corresponding adjustment operation.

[0042] S4: Execute a corresponding lens parameter adjustment operation based on the lens parameter adjustment information.

[0043] In this embodiment, after receiving the adjustment instruction, the zoom lens control system drives the lens to perform corresponding adjustment operations such as zoom, focus, exposure, etc.; during the adjustment process, the lens status and imaging effect are continuously monitored to ensure that the adjustment process is smooth and effective.

[0044] In one embodiment, if Figure 3 As shown, before step S4, a zoom lens control method based on wireless remote adjustment includes: S41: In a preset lens image conversion model, current lens parameter settings and historical adjustment records of the zoom lens are obtained.

[0045] In this embodiment, the current lens parameter settings include focal length, aperture, ISO and other parameter values. In the lens image conversion model, the past adjustment records of the zoom lens are retrieved, including the adjustment time, parameter settings before and after the adjustment, and feedback on the imaging effect after the adjustment. To ensure the accuracy and timeliness of the lens image conversion model, the model is regularly updated to reflect the latest performance and status of the lens.

[0046] S42: formulating a lens parameter adjustment strategy according to the lens parameter adjustment information and in combination with physical characteristics and operation restrictions of the lens. The lens parameter adjustment strategy includes a zoom speed, an adjustment sequence, an adjustment step length, and a sensitivity adjustment interval.

[0047] In this embodiment, the received lens parameter adjustment information is parsed to identify the parameters and target values ​​that need to be adjusted; a lens parameter adjustment strategy is preliminarily formulated based on the physical characteristics of the lens (such as zoom range, maximum aperture, and minimum focus distance) and operation restrictions (such as adjustment speed restrictions and avoiding frequent adjustments to protect the lens); and the adjustment strategy is then further refined, including determining the zoom speed, adjustment sequence (which parameter to adjust first), adjustment step size (the magnitude of each adjustment), and sensitivity adjustment interval, etc.

[0048] S43: In the lens performance prediction model, simulated adjustment is performed based on the lens parameter adjustment strategy to obtain a simulated adjustment result.

[0049] In this embodiment, the formulated lens parameter adjustment strategy is input into the lens performance prediction model to simulate the lens parameter adjustment process, including zoom, aperture adjustment, ISO change, etc., and calculate the imaging effect under different environmental conditions; the model outputs the prediction of the imaging effect after simulation adjustment, including key indicators such as clarity, contrast, color reproduction, etc., to obtain the simulation adjustment result.

[0050] S44: Optimizing the lens parameter adjustment strategy based on the simulation adjustment result until a preset imaging effect index is met.

[0051] Specifically, if the simulation result does not meet the index requirements, the lens parameter adjustment strategy is adjusted according to the evaluation result, and the simulation adjustment is performed again.

[0052] S45: Sending the lens parameter adjustment information corresponding to the final lens parameter adjustment strategy to the corresponding remote adjustment execution module.

[0053] Specifically, the adjustment instruction is sent to the remote adjustment execution module (such as the lens controller) through the wireless communication interface.

[0054] In one embodiment, if Figure 4 As shown, in step S3, the environment prediction information and the lens performance prediction information are analyzed to determine whether the current lens parameter settings meet the preset imaging effect indicators in the specified time period, including: S31: Match the key environmental parameters in the environmental prediction information with the environmental adaptability indicators in the lens performance prediction model to evaluate the possible impact of the environment on the lens performance effect; the key environmental parameters include temperature, humidity and light intensity.

[0055] Specifically, the extracted key environmental parameters are matched with the environmental adaptability indicators in the model to evaluate the possible impact of the environment in the current and predicted time periods on the lens imaging effect; the environmental adaptability indicators need to be set based on the actual performance and empirical data of the lens, and updated regularly to reflect changes in lens performance.

[0056] S32: In the lens performance prediction model, the imaging effect of the lens under different zoom settings under predicted environmental conditions is simulated, and the imaging effect includes imaging indicators of clarity, contrast, and color reproduction.

[0057] Specifically, in the lens performance prediction model, for each zoom setting, the imaging process of the lens is simulated under set environmental conditions; when recording the imaging effect, imaging indicators such as clarity, contrast, and color reproduction obtained during the simulation process can be recorded.

[0058] S33: Compare the simulated imaging effect with the preset imaging effect index one by one.

[0059] In this embodiment, preset imaging effect indicators are loaded from the system or user configuration, including thresholds or ranges of clarity, contrast and color reproduction, and the simulated imaging effect is compared with the preset imaging effect indicators one by one to determine whether the simulated imaging effect meets the preset indicators.

[0060] S34: When any simulated imaging effect does not meet a preset imaging effect index, lens parameter adjustment suggestion information is generated and output.

[0061] In this embodiment, for the unsatisfied items, corresponding lens parameter adjustment suggestion information is generated in combination with the physical characteristics and operation limitations of the lens. These suggestions may include adjusting the zoom range, aperture size, ISO sensitivity and other parameters.

[0062] In one embodiment, a zoom lens control method based on wireless remote adjustment further includes: fusing a physical model and a lens performance prediction model to generate a lens image conversion model.

[0063] The physical model and the lens performance prediction model are integrated to generate a lens image conversion model, which includes: S10: Based on the physical model and the lens performance prediction model, key parameters and adjustable parameters are selected as fusion points, and based on a preset model fusion algorithm, the physical model and the lens performance prediction model are fused to obtain an initial lens image conversion model.

[0064] Specifically, the physical model and the lens performance prediction model are deeply analyzed to identify the key parameters and adjustable parameters between the two, and the appropriate model fusion algorithm is selected according to the characteristics of the fusion point; the model fusion algorithms include weighted fusion, Bayesian fusion, and neural network fusion; then the selected model fusion algorithm is used to fuse the physical model and the lens performance prediction model at the fusion point, and then the initial lens portrait conversion model obtained after the fusion is preliminarily verified to ensure that it can correctly reflect the physical characteristics and performance of the lens.

[0065] S20: Obtain current state parameters and external environment parameters of the zoom lens as input of an initial lens portrait conversion model, and train and optimize the initial lens portrait conversion model based on a preset lens portrait training data set to obtain a lens portrait conversion model; wherein the lens portrait training data includes lens portraits of different types of zoom lenses in different environments, and the lens portraits include imaging effect predictions, environmental adaptability assessments, and lens health status evaluations of the zoom lens under different zoom settings.

[0066] In this embodiment, lens portrait data of different types of zoom lenses in different environments are collected from multiple channels; the lens portrait data includes information such as imaging effect prediction, environmental adaptability evaluation and lens health status evaluation of the zoom lens under different zoom settings; then, according to the characteristics of the lens portrait conversion model and the scale of the training data, appropriate training parameters such as learning rate, number of iterations, batch size, etc. are set; the pre-processed training data is input into the initial lens portrait conversion model to execute the model training process. During the training process, the loss function is calculated based on the output of the model and the label of the training data, and the parameters of the model are updated through the back propagation algorithm; the performance of the model is regularly evaluated during the training process, such as using a validation set or a test set for performance evaluation, and the training parameters are adjusted or the model structure is optimized according to the evaluation results to improve the generalization ability and accuracy of the model; finally, when the model performance reaches the preset standard, the training process is stopped and the final lens portrait conversion model is output.

[0067] Furthermore, the collection of lens portrait training data should be as comprehensive and diverse as possible to cover zoom lenses of different types, brands and ages; through accurate imaging effect prediction and environmental adaptability evaluation, users can adjust lens parameters according to actual needs and environmental conditions to obtain the best imaging effect.

[0068] It should be understood that the serial numbers of the steps in the above embodiments do not imply a sequence of execution. The execution sequence of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0069] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 5 As shown. The computer device includes a processor, a memory, a network interface and a database connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store a lens performance prediction model, a lens image conversion model and a lens image training data set. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a zoom lens control method based on wireless remote adjustment is implemented.

[0070] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, steps of a zoom lens control method based on wireless remote adjustment are implemented.

[0071] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps of a zoom lens control method based on wireless remote adjustment are implemented.

[0072] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0073] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0074] The embodiments described above are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, it should be understood by those skilled in the art that the technical solutions described in the aforementioned embodiments may still be modified, or some of the features thereof may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A zoom lens based on wireless remote adjustment, characterized in that: It includes a data acquisition and transmission module, a control mechanism and a remote adjustment execution module; The data acquisition and transmission module has a built-in sensor for collecting ambient environment parameters, receives external environment parameters through a wireless communication interface, and obtains comprehensive environmental information based on the ambient environment parameters and external environment parameters; The control mechanism includes an environment prediction model and a lens performance prediction model; in the environment prediction model, a prediction of a change trend of environmental parameters is performed based on the comprehensive environment information to obtain environment prediction information for a specified time period; in the lens performance prediction model, based on the comprehensive environment information, the environment prediction information and the current lens ecological health, the adaptability of the zoom lens to the environment and the imaging effect under different zoom settings are predicted respectively to obtain lens performance prediction information for a specified time period; The control mechanism analyzes the environment prediction information and the lens performance prediction information to determine whether the current lens parameter setting meets the preset imaging effect index in the specified time period; generates lens parameter adjustment information according to the judgment result; and triggers the lens adjustment instruction to the remote adjustment execution module based on the lens parameter adjustment information; The remote adjustment execution module executes a corresponding lens parameter adjustment operation based on the lens parameter adjustment information.

2. The zoom lens based on wireless remote adjustment according to claim 1, characterized in that: The environmental prediction model is obtained by: Collecting historical environmental data of the area where the zoom lens is located, the historical environmental data including time series data of temperature, humidity, light intensity, air pressure and wind speed; Based on the historical environmental data, combined with meteorological principles and statistical methods, model training is performed to predict the changing trend of environmental parameters within a specified time period in the future and generate an environmental prediction model; The lens performance prediction model is obtained by: Collect historical performance data of zoom lenses, the historical performance data including imaging quality parameters of lenses with different zoom settings, lens ecological health indicators, and corresponding environmental condition data; Based on the historical performance data and environmental condition data, combined with optical imaging principles and machine learning algorithms, model training is performed to predict the environmental conditions and lens imaging effects of the zoom lens under different zoom settings in a specified future time period, and generate a lens performance prediction model.

3. The zoom lens based on wireless remote adjustment according to claim 1, characterized in that: Before triggering the lens adjustment instruction to the remote adjustment execution module based on the lens parameter adjustment information, the control mechanism further includes: Acquire physical characteristic parameters of the zoom lens, wherein the physical characteristic parameters include the focal length range, zoom speed, and lens structure parameters of the lens, and establish a physical model of the lens; Obtain historical lens adjustment records and imaging effect feedback information, analyze the differences in imaging effects corresponding to different zoom settings, and establish a lens image conversion model based on the physical model of the lens; The environmental prediction information, the lens performance prediction information and the current lens ecological health are used as inputs of the lens image conversion model, and lens parameter adjustment information is generated according to the judgment result.

4. A zoom lens control method based on wireless remote adjustment, characterized in that: The data acquisition and transmission module collects ambient environment parameters and receives external environment parameters, and obtains comprehensive environmental information based on the ambient environment parameters and external environment parameters; In the environmental prediction model, the change trend of environmental parameters is predicted based on the comprehensive environmental information to obtain environmental prediction information for a specified time period; in the lens performance prediction model, the adaptability of the zoom lens to the environment and the imaging effect under different zoom settings are predicted based on the comprehensive environmental information, the environmental prediction information and the current lens ecological health, to obtain lens performance prediction information for a specified time period; Analyze the environment prediction information and the lens performance prediction information to determine whether the current lens parameter settings meet the preset imaging effect indicators in the specified time period; generate lens parameter adjustment information according to the determination result; and trigger a lens adjustment instruction based on the lens parameter adjustment information; A corresponding lens parameter adjustment operation is performed based on the lens parameter adjustment information.

5. The zoom lens control method based on wireless remote adjustment according to claim 4, characterized in that: Before performing the corresponding lens parameter adjustment operation based on the lens parameter adjustment information, the method includes: In the preset lens image conversion model, the current lens parameter settings and historical adjustment records of the zoom lens are obtained; Formulate a lens parameter adjustment strategy based on the lens parameter adjustment information and in combination with the physical characteristics and operation limitations of the lens, wherein the lens parameter adjustment strategy includes a zoom speed, an adjustment sequence, an adjustment step length, and a sensitivity adjustment interval; In the lens performance prediction model, simulated adjustment is performed based on the lens parameter adjustment strategy to obtain a simulated adjustment result; Based on the simulation adjustment result, optimizing the lens parameter adjustment strategy until the preset imaging effect index is met; The lens parameter adjustment information corresponding to the final lens parameter adjustment strategy is sent to the corresponding remote adjustment execution module.

6. The zoom lens control method based on wireless remote adjustment according to claim 4, characterized in that: The combining of the environment prediction information and the lens performance prediction information for analysis to determine whether the current lens parameter settings meet the preset imaging effect index in the specified time period includes: Matching the key environmental parameters in the environmental prediction information with the environmental adaptability index in the lens performance prediction model to evaluate the possible impact of the environment on the lens performance effect; the key environmental parameters include temperature, humidity and light intensity; In the lens performance prediction model, the imaging effect of the lens under different zoom settings under predicted environmental conditions is simulated, and the imaging effect includes imaging indicators of clarity, contrast and color reproduction; Compare the simulated imaging effect with the preset imaging effect index one by one; When any simulated imaging effect does not meet the preset imaging effect index, lens parameter adjustment suggestion information is generated and output.

7. The zoom lens control method based on wireless remote adjustment according to claim 6, characterized in that: The method further includes: fusing the physical model and the lens performance prediction model to generate a lens image conversion model; The fusion physical model and the lens performance prediction model are used to generate a lens image conversion model, and the lens image conversion model is generated, including: Based on the physical model and the lens performance prediction model, key parameters and adjustable parameters are selected as fusion points, and based on a preset model fusion algorithm, the physical model and the lens performance prediction model are fused to obtain an initial lens image conversion model; The current state parameters and external environment parameters of the zoom lens are obtained as inputs of an initial lens portrait conversion model, and the initial lens portrait conversion model is trained and optimized based on a preset lens portrait training data set to obtain a lens portrait conversion model; wherein the lens portrait training data includes lens portraits of different types of zoom lenses in different environments, and the lens portraits include imaging effect predictions, environmental adaptability assessments, and lens health status evaluations of the zoom lens under different zoom settings.

8. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the zoom lens control method based on wireless remote adjustment as described in any one of claims 4 to 7 are implemented.

9. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of a zoom lens control method based on wireless remote adjustment as claimed in any one of claims 4 to 7 are implemented.

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