Projector telescopic lens control method, system and computer equipment

Abstract

The present invention relates to a projector telescopic lens control method, system and computer equipment, including: obtaining the lens position detection data and real-time temperature monitoring data of the projector, and performing correlation analysis to obtain a corresponding real-time lens state group; obtaining the initial projection image of the projector, and performing predictive analysis on the initial projection image according to the lens position detection data to obtain a corresponding image quality trend; performing lens adjustment analysis on the real-time lens state group and the image quality trend to obtain a corresponding initial lens control scheme; constructing image relationships for the initial projection image through a preset concentric circle automatic matching algorithm to obtain a homography relationship between corresponding planes; performing parameter analysis based on the homography relationship to obtain corresponding lens fine-tuning parameters; and performing comprehensive analysis on the initial lens control scheme and the lens fine-tuning parameters to obtain a corresponding global telescopic lens adjustment strategy. The present invention can comprehensively consider a variety of influencing factors and realize precise control of the projector lens.

Description

Technical Field

[0001] The present invention relates to the technical field of projectors, and in particular to a projector telescopic lens control method, system and computer equipment. Background Art

[0002] As a display device widely used in education, business and entertainment, the image quality and projection effect of the projector directly affect the user experience. With the increasing demand for high-definition and large-size projection, precise control of the projector lens has become one of the key factors to improve projection quality. Existing projector lens control methods usually only consider a single lens position parameter or ambient temperature factor, while ignoring the mutual influence between these factors and the real-time changes of the projected image. This simplified control method may cause distortion, blurring or uneven color of the projected image, especially after long-term use or in complex environments. Therefore, how to comprehensively consider multiple influencing factors and achieve precise control of the projector lens to obtain a stable and clear projection effect has become one of the key issues in current research. Summary of the invention

[0003] The main purpose of the present invention is to provide a projector telescopic lens control method, system and computer equipment, which can comprehensively consider multiple influencing factors and realize precise control of the projector lens.

[0004] To achieve the above object, the present invention provides a projector telescopic lens control method, comprising:

[0005] Obtain the lens position detection data and real-time temperature monitoring data of the projector, and perform correlation analysis to obtain the corresponding real-time lens status group;

[0006] Acquire an initial projection image of the projector, and perform prediction analysis on the initial projection image according to the lens position detection data to obtain a corresponding image quality trend;

[0007] Performing lens adjustment analysis on the real-time lens state group and the image quality trend to obtain a corresponding initial lens control solution;

[0008] The image relationship of the initial projection image is constructed by using a preset concentric circle automatic matching algorithm to obtain a homography relationship between corresponding planes;

[0009] Performing simulated projection on the initial lens control solution based on the homography relationship to obtain a simulated projection image, and performing parameter analysis to obtain corresponding lens fine-tuning parameters;

[0010] The initial lens control scheme and the lens fine-tuning parameters are comprehensively analyzed to obtain a corresponding global telescopic lens adjustment strategy.

[0011] Furthermore, the acquisition of the lens position detection data and the real-time temperature monitoring data of the projector and the correlation analysis to obtain the corresponding real-time lens status group include:

[0012] Collecting position sensor data of a projector lens, and preprocessing the position sensor data to obtain the lens position detection data;

[0013] Acquire real-time temperature data of multiple temperature sensors inside the projector, and perform standardization processing on the real-time temperature data to obtain the real-time temperature monitoring data;

[0014] Establishing a relationship based on the lens position detection data and the real-time temperature monitoring data to obtain a corresponding relationship between the lens position and the real-time temperature;

[0015] Performing time analysis on the corresponding relationship between the lens position and the real-time temperature to obtain the change trend of the lens position and the temperature;

[0016] Analyze the lens status according to the change trend to obtain lens status data;

[0017] The lens position detection data, the real-time temperature monitoring data and the lens status data are integrated to obtain the real-time lens status group.

[0018] Furthermore, the acquiring of the initial projected image of the projector and performing a prediction analysis on the initial projected image according to the lens position detection data to obtain a corresponding image quality trend include:

[0019] Performing frequency domain transformation processing on the initial projected image to obtain corresponding frequency domain feature information;

[0020] Performing clarity evaluation on the initial projected image according to the frequency domain feature information to obtain a corresponding clarity score;

[0021] Establishing a mathematical mapping relationship based on the clarity score and the lens position detection data to obtain a relationship function between the lens position and the image quality;

[0022] Performing numerical analysis on the relationship function to obtain a sensitivity coefficient of the effect of lens position change on image quality;

[0023] Predicting and analyzing future lens positions according to the sensitivity coefficients to obtain a future lens position sequence;

[0024] An image quality simulation calculation is performed on the future lens position sequence to obtain a corresponding image quality trend.

[0025] Further, performing lens adjustment analysis on the real-time lens state group and the image quality trend to obtain a corresponding initial lens control solution includes:

[0026] Performing correlation analysis on the real-time lens state group to obtain a lens state correlation coefficient;

[0027] Compensating the image quality trend according to the lens state correlation coefficient to obtain an image quality index;

[0028] Constructing a lens adjustment objective function based on the image quality index, and performing parameter analysis and solving on the lens adjustment objective function to obtain initial lens adjustment parameters;

[0029] Performing a simulated lens position adjustment according to the initial lens adjustment parameters to obtain a simulated lens state;

[0030] Adaptively modifying the initial lens adjustment parameters according to the simulated lens state to obtain modified lens adjustment parameters;

[0031] An output of the initial lens control scheme is generated based on the modified lens adjustment parameters.

[0032] Furthermore, the image relationship construction of the initial projection image is performed by using a preset concentric circle automatic matching algorithm to obtain a homography relationship between corresponding planes, including:

[0033] Perform concentric circle projection onto a preset concentric circle array calibration plate and obtain a calibration image after projection;

[0034] Performing color channel separation on the calibration image to separate the projection concentric circle component and the calibration plate concentric circle component;

[0035] Calculating the coordinates of the projected concentric circle components according to the preset concentric circle projection geometric constraints to obtain the corresponding circle center pixel coordinates;

[0036] Performing cross-ratio invariance analysis on the center pixel coordinates to obtain a matching relationship of concentric circles;

[0037] Based on the matching relationship, a homography is calculated for the calibration plane and the projector projection plane to obtain a corresponding plane homography matrix;

[0038] Using the homography matrix to estimate the internal and external parameters of the projector to obtain a calibration result of the projector;

[0039] Performing distortion correction and geometric transformation on the initial projected image according to the calibration result to obtain a corrected image;

[0040] Extracting and matching feature points of the corrected image and establishing a corresponding relationship between the images;

[0041] Based on the corresponding relationship, homography analysis is performed on the plane homography matrix to obtain the homography relationship.

[0042] Furthermore, the homography calculation is performed on the calibration plane and the projector projection plane based on the matching relationship to obtain a corresponding plane homography matrix, including:

[0043] Performing homogeneous coordinate transformation of the corresponding points of the concentric circles on the matching relationship to obtain a homogeneous coordinate point set;

[0044] Constructing a linear equation system according to the homogeneous coordinate point set to obtain an initial homography matrix;

[0045] Performing singular value decomposition on the initial homography matrix to obtain a decomposed matrix group;

[0046] Extracting a rotation matrix and a translation vector based on the matrix group to obtain an initial posture estimate;

[0047] Optimizing the initial homography matrix according to the initial posture estimation to obtain an optimized homography matrix;

[0048] Calculate the geometric relationship between the projector projection plane and the calibration plane based on the optimized homography matrix to obtain the plane projection geometric constraint;

[0049] Accurately modeling the calibration plane and the projector projection plane according to the plane projection geometric constraints to obtain an accurate homography matrix;

[0050] The plane homography matrix is ​​corrected according to a preset error threshold to obtain the plane homography matrix.

[0051] Furthermore, the initial lens control scheme is simulated and projected based on the homography relationship to obtain a simulated projection image, and parameter analysis is performed to obtain corresponding lens fine-tuning parameters, including:

[0052] Constructing a three-dimensional projection model according to the homography relationship and the initial lens control scheme, and performing ray tracing analysis on the three-dimensional projection model to obtain a corresponding simulated projection light path;

[0053] Performing pixel mapping processing on the simulated projection light path to generate a corresponding simulated projection image matrix;

[0054] Calculating the distortion coefficient and clarity index of the simulated projection image according to the simulated projection image matrix;

[0055] Performing parameter sensitivity analysis on the initial lens control scheme based on the distortion coefficient and the clarity index to obtain a corresponding lens adjustment sensitivity curve;

[0056] The initial lens control scheme is subjected to parameter analysis according to a preset gradient descent algorithm in combination with the lens adjustment sensitivity curve to obtain corresponding lens fine-tuning parameters.

[0057] Furthermore, the initial lens control scheme and the lens fine-tuning parameters are comprehensively analyzed to obtain a corresponding global telescopic lens adjustment strategy, including:

[0058] Performing dynamic lens expansion and contraction construction on the initial lens control scheme and the lens fine-tuning parameters to obtain a lens expansion and contraction response strategy;

[0059] Adaptively performing piecewise linearization processing on the lens telescopic response strategy to obtain a piecewise linear control strategy;

[0060] The lens telescopic trajectory is planned according to the piecewise linear control strategy to obtain a lens motion trajectory curve;

[0061] Generating lens drive according to the lens motion trajectory curve to obtain a lens drive instruction set;

[0062] Dynamically compensating the lens drive instruction set to obtain a compensation drive instruction;

[0063] The compensation drive instruction is analyzed according to the lens motion trajectory curve to obtain the global telescopic lens adjustment strategy.

[0064] The present invention further provides a projector telescopic lens control system, which is applied to any one of the above projector telescopic lens control methods, comprising:

[0065] An acquisition module, the acquisition module is used to obtain the lens position detection data and real-time temperature monitoring data of the projector, and perform correlation analysis to obtain a corresponding real-time lens status group;

[0066] An analysis module, the analysis module is used to obtain an initial projection image of the projector, and perform a prediction analysis on the initial projection image according to the lens position detection data to obtain a corresponding image quality trend;

[0067] an association module, the association module being used to perform lens adjustment analysis on the real-time lens state group and the image quality trend to obtain a corresponding initial lens control solution;

[0068] A processing module, the processing module is used to construct an image relationship for the initial projection image through a preset concentric circle automatic matching algorithm to obtain a homography relationship between corresponding planes;

[0069] A control module, the control module is used to simulate the projection of the initial lens control scheme based on the homography relationship to obtain a simulated projection image, and perform parameter analysis to obtain corresponding lens fine-tuning parameters;

[0070] An execution module is used to comprehensively analyze the initial lens control scheme and the lens fine-tuning parameters to obtain a corresponding global telescopic lens adjustment strategy.

[0071] The present invention also provides a projector telescopic lens control computer device, comprising:

[0072] Memory, used to store programs;

[0073] The processor is used to execute the program to implement each step of any one of the above-mentioned methods for controlling a projector telescopic lens.

[0074] The present invention provides a projector telescopic lens control method, system and computer equipment, which have the following beneficial effects:

[0075] By correlating and analyzing the lens position detection data and real-time temperature monitoring data, the real-time status of the lens can be more accurately evaluated, providing a reliable basis for subsequent adjustments. Based on the predictive analysis of the initial projected image, possible image quality problems can be discovered and prevented in a timely manner, improving the stability of the projection effect. The homography relationship between planes is established through the concentric circle automatic matching algorithm, which realizes the accurate simulation of the initial lens control scheme, thereby obtaining more accurate lens fine-tuning parameters. This comprehensive analysis and adjustment method not only improves the clarity and uniformity of the projected image, but also can adapt to different usage environments and time lengths, effectively solving the problem of reduced projection quality under long-term use or in complex environments. In addition, by formulating a global telescopic lens adjustment strategy, this method realizes the intelligence and adaptability of the projection system, which can be flexibly adjusted according to different projection requirements and environmental changes to meet the requirements of diverse application scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0076] Figure 1 It is a flow chart of a projector telescopic lens control method provided by the present invention;

[0077] Figure 2 It is a structural diagram of a projector telescopic lens control system provided by the present invention;

[0078] Figure 3 The present invention provides a structure diagram of a projector telescopic lens control computer device.

[0079] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0080] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0081] The present invention is further described below in conjunction with the accompanying drawings and specific implementation methods.

[0082] Reference Figure 1 As shown, the present invention provides 1. a projector telescopic lens control method, comprising:

[0083] Step S1: obtaining the lens position detection data and real-time temperature monitoring data of the projector, and performing correlation analysis to obtain a corresponding real-time lens status group;

[0084] Step S2: obtaining an initial projection image of the projector, and performing prediction analysis on the initial projection image according to the lens position detection data to obtain a corresponding image quality trend;

[0085] Step S3: performing lens adjustment analysis on the real-time lens status group and image quality trend to obtain a corresponding initial lens control solution;

[0086] Step S4: constructing image relationships for the initial projection images using a preset concentric circle automatic matching algorithm to obtain homography relationships between corresponding planes;

[0087] Step S5: Simulate the projection of the initial lens control solution based on the homography relationship to obtain a simulated projection image, and perform parameter analysis to obtain corresponding lens fine-tuning parameters;

[0088] Step S6: Comprehensively analyze the initial lens control scheme and the lens fine-tuning parameters to obtain a corresponding global telescopic lens adjustment strategy.

[0089] Based on the above steps, the detailed process is as follows:

[0090] Step S1: real-time monitoring of the data of the current position of the lens, and integration of the data to obtain lens position detection data, which is usually in units of millimeters or micrometers and represents the offset of the lens relative to its initial position.

[0091] The temperature sensor monitors the projector's operating temperature in real time. Temperature changes may affect the physical properties of the lens and thus affect the projection quality.

[0092] Use data analysis algorithms (such as regression analysis or time series analysis) to determine the relationship between lens position and temperature. Increased temperature may cause expansion of the lens material, thereby changing the position and shape of the lens.

[0093] Based on the analysis results, a real-time lens status group is generated. This status group contains the current lens position and its expected change information under the current temperature conditions. The real-time lens status group can be used to further optimize the control strategy of the lens to cope with the impact of temperature changes on projection quality.

[0094] Step S2: Initialize the projector and let it project an initial image, which can be a standardized test pattern, such as a grid pattern or a specific image sample. The projected image is captured by a high-resolution camera or image sensor for subsequent image quality analysis.

[0095] The initial projected image is analyzed in combination with the lens position detection data, and the data is used to predict the impact of the lens position on the image quality. For example, a slight deviation in the lens position may cause the image to be blurred or distorted, and knowing these deviations in advance helps to conduct effective predictive analysis.

[0096] Use image processing algorithms (such as Fourier transform, edge detection, etc.) to evaluate the quality of the initial projected image, focusing on parameters such as image clarity, contrast, distortion, etc.

[0097] The image quality trend is predicted based on the lens position data and the temperature data to obtain the image quality trend, which reflects how the image quality will change under the current lens position and temperature conditions.

[0098] Step S3: Integrating the real-time lens status group and the image quality trend can fully understand the current lens status and its impact on the image quality.

[0099] The comprehensive data is analyzed using optimization algorithms (such as genetic algorithms, particle swarm optimization, etc.) to determine the best lens adjustment strategy. During the analysis process, multiple factors need to be involved, including the physical limitations of the lens, the impact of temperature on the lens, image quality requirements, etc., to obtain the analysis results.

[0100] Based on the analysis results, an initial lens control plan is generated. The plan includes specific lens adjustment steps and parameters, such as the lens movement distance, direction, speed, etc. This initial plan is the basis for subsequent lens fine-tuning and global adjustment.

[0101] Step S4: Introduce a preset concentric circle pattern into the initial projected image. These concentric circles are usually composed of multiple circles of different sizes and are used to assist image analysis. Use image processing techniques (such as Hough transform) to detect the circular contours in the projected image and match them with the preset concentric circle pattern.

[0102] Based on the correspondence between the detected circular contour and the preset pattern, a mapping between the projection plane and the image plane is established. This mapping relationship can reveal the geometric deformation in the projection process, such as perspective deformation, distortion, etc. Using the matching point pairs, the homography matrix between the projection plane and the image plane is calculated. The homography matrix describes the projective transformation relationship between two planes. The homography relationship provides an accurate mapping from one plane to another.

[0103] Step S5: Using the homography relationship to perform virtual projection simulation on the initial lens control scheme. This simulation process can predict the possible appearance and quality of the projected image after applying the initial control scheme.

[0104] Perform detailed analysis on the simulated projected image to evaluate its quality indicators, such as clarity, contrast, color reproduction, etc. Compare the differences between the simulated projected image and the ideal image to identify areas that need further improvement.

[0105] Based on the analysis results of the simulated projected image, the initial lens control scheme is fine-tuned.

[0106] Use an optimization algorithm (e.g., gradient descent) to fine-tune lens parameters such as focal length, lens position, etc. to maximize image quality. Generate a set of lens fine-tuning parameters that are designed to further optimize the initial control solution.

[0107] Step S6: Integrate the initial lens control scheme with the lens fine-tuning parameters, taking into account various factors such as lens physical limitations, temperature effects, image quality trends, etc.

[0108] Use advanced optimization algorithms (such as multi-objective optimization algorithms) to balance various requirements, such as image quality, adjustment speed, system stability, etc. Based on the changes in lens performance under long-term use, generate dynamic adjustment strategies that can adapt to different environments and usage conditions.

[0109] Based on the comprehensive analysis results, generate a comprehensive lens adjustment strategy. This strategy should include:

[0110] Precise lens movement instructions, including movement distance, speed and direction. Temperature compensation mechanism to cope with changes in lens performance under different temperature conditions. Real-time feedback and adjustment mechanism to continuously optimize image quality during projection.

[0111] The present invention provides a projector telescopic lens control method, which can more accurately evaluate the real-time status of the lens by correlating and analyzing lens position detection data and real-time temperature monitoring data, and provide a reliable basis for subsequent adjustments. Based on the predictive analysis of the initial projected image, possible image quality problems can be discovered and prevented in time, thereby improving the stability of the projection effect. The homography relationship between planes is established through the concentric circle automatic matching algorithm, and the initial lens control scheme is accurately simulated, thereby obtaining more accurate lens fine-tuning parameters. This comprehensive analysis and adjustment method not only improves the clarity and uniformity of the projected image, but also can adapt to different usage environments and time lengths, effectively solving the problem of reduced projection quality under long-term use or in complex environments. In addition, the method realizes the intelligence and adaptability of the projection system by formulating a global telescopic lens adjustment strategy, and can be flexibly adjusted according to different projection requirements and environmental changes to meet the requirements of diverse application scenarios.

[0112] In one embodiment, the lens position detection data and the real-time temperature monitoring data of the projector are obtained, and correlation analysis is performed to obtain a corresponding real-time lens status group, including:

[0113] The position sensor data of the projector lens is collected by the position sensor. The position sensor includes a linear displacement sensor and a rotary encoder. The collected raw position data is pre-processed by filtering, calibration, etc., to eliminate noise and convert it into lens position detection data in standard units. For example, the raw voltage signal is converted into displacement data in millimeters.

[0114] There are multiple temperature sensors installed inside the projector, distributed in key parts such as the light source, optical engine, and cooling system. These sensors collect temperature data in real time, and obtain real-time temperature monitoring data after standardized processing. Standardization processing includes unit conversion, outlier removal, data smoothing, etc., so that the data of different sensors are comparable.

[0115] The processed lens position detection data and real-time temperature monitoring data are time-aligned to establish a corresponding relationship between the two. For example, a set of lens position and temperature data at each point is recorded every 1 second to form a time series. Through correlation analysis, the degree of correlation between the lens position and the temperature of each temperature measurement point is determined.

[0116] Perform time series analysis on the corresponding relationship between lens position and temperature to obtain the changing trend of lens position and temperature over time. For example, calculate the rate of change of position and temperature, and determine whether there is periodic change.

[0117] Analyze the lens status based on the change trend. For example, if the lens position changes rapidly while the temperature is relatively stable, it may indicate that a zoom operation is in progress; if the temperature continues to rise while the lens position is fixed, it may indicate an overheating risk. Through the preset judgment rules, the lens status data such as the working status and thermal status of the lens are obtained.

[0118] This implementation achieves accurate monitoring of the lens position and temperature by collecting and preprocessing the position sensor data and internal temperature data of the projector lens. The two types of data are correlated and analyzed to establish a corresponding relationship between the lens position and temperature, which provides a basis for a deep understanding of the working status of the lens. Time series analysis of the changing trends of the lens position and temperature enables the system to capture the dynamic changes of the lens status in a timely manner. Analyzing the lens status based on the changing trend can accurately determine the working status and thermal status of the lens, which helps to detect potential problems early. The real-time lens status group finally integrated fully reflects the comprehensive status of the lens at a certain moment, providing a reliable basis for the intelligent control and fault prevention of the projector.

[0119] In one embodiment, an initial projected image of a projector is obtained, and a prediction analysis is performed on the initial projected image according to the lens position detection data to obtain a corresponding image quality trend, including:

[0120] The projector obtains the initial projection image through its built-in image sensor. The initial projection image is the actual image projected onto the projection screen by the projector at the current lens position. After obtaining the initial projection image, it is subjected to frequency domain transformation processing to convert the image from the spatial domain to the frequency domain. Common frequency domain transformation methods include Fourier transform and wavelet transform. Through frequency domain transformation, the frequency domain feature information corresponding to the image is obtained, such as spectrum distribution, energy concentration, etc. These frequency domain feature information can reflect the quality characteristics of the image, such as clarity and detail richness.

[0121] Based on the obtained frequency domain feature information, the clarity of the initial projected image is evaluated. The clarity evaluation uses a preset evaluation algorithm, such as edge detection, gradient analysis, etc., to calculate a clarity score. The score is a numerical value used to quantitatively characterize the clarity of the image. The higher the score, the clearer the image.

[0122] The clarity score is correlated with the current lens position detection data to establish a mathematical mapping relationship between the two. This mapping relationship can be expressed by a function equation, reflecting the corresponding relationship between the lens position and the image quality. The mapping relationship is established using statistical methods such as regression analysis and fitting based on historical data samples.

[0123] The established relationship function is numerically analyzed, and the derivative values ​​of the function at different points are calculated to obtain the sensitivity coefficient of the influence of lens position change on image quality. The sensitivity coefficient reflects the magnitude of image quality change caused by a small change in lens position and is an important prediction indicator.

[0124] According to the sensitivity coefficient, combined with the current lens position and movement trend, the lens position in the future period of time is predicted and analyzed. The prediction analysis uses time series prediction and other methods to obtain a series of predicted future lens position sequences.

[0125] The image quality is simulated and calculated for the predicted future lens position sequence. The simulation is based on the relationship function between lens position and image quality established previously, and the corresponding image quality score is calculated for each predicted position. In this way, a series of image quality prediction values ​​at future time points are obtained, forming the corresponding image quality change trend.

[0126] This embodiment obtains frequency domain feature information by performing frequency domain transformation processing on the initial projected image, which can fully reflect the clarity and detail richness of the image, and provide a reliable data basis for subsequent image quality evaluation. A mathematical mapping relationship is established between the clarity score and the lens position detection data, which realizes the quantitative correspondence between the lens position and the image quality, and provides a scientific basis for predictive analysis. By calculating the sensitivity coefficient, the degree of influence of the lens position change on the image quality can be accurately grasped, and the accuracy of the prediction is improved. Image quality simulation calculation is performed on the future lens position sequence to form the image quality change trend, which can predict possible image quality problems in advance and provide forward-looking guidance for lens control decisions.

[0127] In one embodiment, lens adjustment analysis is performed on the real-time lens state group and the image quality trend to obtain a corresponding initial lens control solution, including:

[0128] The real-time lens state group is subjected to correlation analysis to obtain the lens state correlation coefficient. The real-time lens state group includes parameters such as the focal length, aperture size, and focus distance of the current lens. By calculating the Pearson correlation coefficient between these parameters, a lens state correlation coefficient matrix reflecting the relationship between the parameters is obtained.

[0129] The image quality trend is compensated according to the lens state correlation coefficient to obtain the image quality index. The image quality trend refers to the recent changes in image clarity, contrast and other indicators. The image quality trend is weighted compensated using the lens state correlation coefficient matrix to eliminate the impact of lens parameter changes on image quality evaluation, thereby obtaining a more accurate image quality index.

[0130] Based on the image quality index, the lens adjustment objective function is constructed, and the parameters of the lens adjustment objective function are analyzed and solved to obtain the initial lens adjustment parameters. The lens adjustment objective function aims to maximize the image quality index and uses the lens parameters as independent variables. The objective function is solved by numerical optimization methods such as the gradient descent method to obtain the initial lens adjustment parameters that make the objective function achieve the optimal value.

[0131] The lens position is simulated and adjusted according to the initial lens adjustment parameters to obtain the simulated lens state. The optical imaging model is used to simulate the imaging effect after the lens adjustment according to the initial lens adjustment parameters to obtain the simulated lens state including focal length, aperture, focus distance, etc.

[0132] The initial lens adjustment parameters are adaptively corrected according to the simulated lens state to obtain the corrected lens adjustment parameters. The simulated lens state is compared with the expected target state, the deviation is calculated, and the initial lens adjustment parameters are corrected by proportional-integral-derivative (PID) control according to the deviation to obtain more accurate corrected lens adjustment parameters.

[0133] The output of the initial lens control scheme is generated based on the modified lens adjustment parameters. The modified lens adjustment parameters are converted into a specific lens control instruction sequence to form a complete initial lens control scheme, which provides a basis for subsequent lens control execution.

[0134] This embodiment obtains the lens state correlation coefficient by performing correlation analysis on the real-time lens state group, effectively capturing the intrinsic correlation between the various lens parameters and providing more comprehensive data support for subsequent lens adjustment. The image quality trend is compensated according to the lens state correlation coefficient, eliminating the interference of lens parameter changes on image quality evaluation and improving the accuracy of image quality indicators. By constructing the lens adjustment objective function and performing parameter analysis and solution, the lens adjustment is optimized and the accuracy of lens control is improved. By using the lens position simulation adjustment and adaptive correction mechanism, the lens adjustment parameters are further optimized to ensure the reliability and stability of the lens control scheme. This multi-step, closed-loop lens control method not only improves the imaging quality of the projector, but also greatly improves the user experience.

[0135] In one embodiment, the image relationship between the initial projection images is constructed by using a preset concentric circle automatic matching algorithm to obtain a homography relationship between corresponding planes, including:

[0136] The projector projects onto a preset concentric circle array calibration plate to obtain a projected calibration image. The concentric circle array calibration plate includes multiple groups of concentric circles, each group of concentric circles is composed of several circles with different radii, and the centers of these circles coincide. The image projected by the projector also includes the same concentric circle array.

[0137] The acquired calibration image is separated by color channels to separate the projection concentric circle component and the calibration plate concentric circle component. The projection concentric circle component is usually red or blue, while the calibration plate concentric circle component is black. The two components can be effectively separated by color threshold segmentation.

[0138] The coordinates of the projected concentric circle components are calculated according to the preset concentric circle projection geometric constraints to obtain the corresponding circle center pixel coordinates. The concentric circle projection geometric constraints mean that the projected concentric circles still maintain the concentricity on the image plane, so the circle center coordinates can be obtained by fitting the circle.

[0139] The cross ratio invariance analysis of the pixel coordinates of the center of the circle is performed to obtain the matching relationship of the concentric circles. The cross ratio invariance means that the cross ratio of the four collinear points remains unchanged under the projection transformation. This property can be used to establish the corresponding relationship between the projected image and the concentric circles of the calibration plate.

[0140] Based on the matching relationship, the homography of the calibration plane and the projector projection plane is calculated to obtain the corresponding plane homography matrix. The homography matrix describes the projection transformation relationship between the two planes and can be solved by the least squares method, which includes:

[0141] The least squares fitting is performed on the center coordinates of the concentric circles in the matching relationship to obtain the initial homography matrix between the calibration plane and the projection plane; the point set on the calibration plane is projected according to the initial homography matrix to obtain the corresponding point set on the projection plane; the error between the corresponding point set on the projection plane and the actual projection point set is calculated to obtain the reprojection error.

[0142] Iteratively optimize the initial homography matrix based on the reprojection error to obtain the optimized homography matrix;

[0143] The optimized homography matrix is ​​used to perform projection transformation on the feature points on the calibration plane to obtain the corresponding feature points on the projection plane; the optimized homography matrix is ​​fine-tuned according to the corresponding feature points to obtain the fine-tuned homography matrix; the fine-tuned homography matrix is ​​subjected to singular value decomposition to obtain the rotation matrix and translation vector.

[0144] The external parameter matrix of the projector is constructed based on the rotation matrix and translation vector to obtain the position information of the projector; the fine-tuned homography matrix is ​​normalized using the position information to obtain the final planar homography matrix.

[0145] The homography matrix is ​​used to estimate the internal and external parameters of the projector to obtain the calibration result of the projector. The internal parameters include focal length, principal point coordinates, etc., and the external parameters include the position and posture of the projector. These parameters can be obtained by decomposing the homography matrix.

[0146] According to the calibration results, the initial projected image is subjected to distortion correction and geometric transformation to obtain a corrected image. Distortion correction is mainly to remove lens distortion, while geometric transformation is to transform the image to the ideal projection position.

[0147] Feature points are extracted and matched on the rectified image and the corresponding relationship between images is established. SIFT or SURF algorithms are commonly used for feature point extraction, and nearest neighbor matching and other methods are used for feature point matching.

[0148] Based on the correspondence, the homography matrix of the plane is subjected to homography analysis to obtain the homography relationship. Homography analysis refers to solving the homography matrix through corresponding point pairs to establish the mapping relationship between the two images.

[0149] This embodiment achieves high-precision correction and registration of the projector image by adopting a concentric circle array calibration plate and a preset concentric circle automatic matching algorithm. This method utilizes the geometric characteristics and cross-ratio invariance of concentric circles to effectively overcome the instability problem of feature point extraction and matching in traditional methods, and improves the accuracy of calibration and correction. Through the color channel separation technology, the precise separation of the projection concentric circle component and the calibration plate concentric circle component is achieved, laying the foundation for subsequent processing. The internal and external parameter estimation method based on the homography matrix can not only accurately obtain the parameters of the projector, but also perform distortion correction and geometric transformation on the initial projected image, significantly improving the quality of the projected image. In addition, the correspondence between images is established through feature point extraction and matching, and combined with homography analysis, accurate mapping between different planes is achieved, providing a reliable basis for the precise control of the projector telescopic lens.

[0150] In one embodiment, a homography is calculated for the calibration plane and the projector projection plane based on the matching relationship to obtain a corresponding plane homography matrix, including:

[0151] The matching relationship is transformed into homogeneous coordinates of the corresponding points of the concentric circles to obtain a set of homogeneous coordinate points. The matching relationship here refers to the correspondence between the feature points on the calibration plane and the corresponding points on the projection plane of the projector. The concentric circle corresponding points refer to the corresponding feature points distributed in concentric circles on the calibration plane and the projection plane. Homogeneous coordinate transformation is the process of converting two-dimensional plane coordinates into three-dimensional homogeneous coordinates, which can simplify subsequent matrix operations.

[0152] Based on the obtained homogeneous coordinate point set, a linear equation system is constructed and solved to obtain the initial homography matrix. The linear equation system here is an overdetermined system of equations based on the coordinate relationship of the corresponding points. Solving this system of equations can obtain a preliminary homography transformation matrix. Perform singular value decomposition on the initial homography matrix to obtain the decomposed matrix group. Singular value decomposition can decompose the matrix into the product of three matrices, which is conducive to extracting rotation and translation information.

[0153] Based on the decomposed matrix group, the rotation matrix and translation vector are extracted to obtain the initial attitude estimate. The attitude here refers to the spatial position and orientation of the projector relative to the calibration plane. The initial homography matrix is ​​optimized based on the initial attitude estimate, and the matrix elements are fine-tuned using methods such as nonlinear least squares to obtain the optimized homography matrix.

[0154] The geometric relationship between the projector projection plane and the calibration plane is calculated based on the optimized homography matrix to obtain the plane projection geometric constraints, including: performing coordinate transformation on the corresponding points of the projector projection plane and the calibration plane according to the optimized homography matrix to obtain the transformed point set; performing principal component analysis on the transformed point set to obtain the normal vectors of the projection plane and the calibration plane; and calculating the angle between the projection plane and the calibration plane based on the normal vector to obtain the plane inclination angle.

[0155] The projection plane is rotated according to the plane inclination angle to obtain the rotated projection plane equation; the intersection line of the two planes is calculated based on the rotated projection plane equation and the calibration plane equation to obtain the plane projection boundary; the projection area is clipped according to the plane projection boundary to obtain the effective projection area.

[0156] The intersection of the projector optical axis and the calibration plane is calculated based on the effective projection area to obtain the projection center point; a projection cone is constructed according to the projection center point and the boundary points of the effective projection area to obtain a projection geometry model; the projector focal length and principal point coordinates are calculated based on the projection geometry model to obtain the internal parameters of the projector.

[0157] The position of the projector relative to the calibration plane is calculated based on the intrinsic parameters of the projector and the plane projection boundary to obtain the extrinsic parameter matrix; the projection transformation matrix is ​​constructed based on the intrinsic parameter and extrinsic parameter matrices to obtain the plane projection geometric constraints. The geometric relationship here includes information such as the relative position and angle between the two planes.

[0158] The plane homography matrix is ​​corrected according to the preset error threshold to obtain the final plane homography matrix. The error threshold is the allowable error range pre-set according to the actual application requirements. Through iterative optimization and other methods, the reprojection error of the homography matrix is ​​made less than the threshold. The plane homography matrix obtained in this way can accurately describe the mapping relationship between the calibration plane and the projection plane, providing a basis for subsequent lens control.

[0159] This embodiment can accurately obtain the mapping relationship between the two planes by performing precise homography calculation on the calibration plane and the projector projection plane, providing a reliable basis for lens control. The homogeneous coordinate transformation of the corresponding points of the concentric circles is adopted to simplify the subsequent matrix operations and improve the calculation efficiency. The rotation matrix and translation vector are extracted by singular value decomposition, and the preliminary estimation of the projector posture is realized, laying the foundation for subsequent optimization. The homography matrix is ​​optimized by nonlinear least squares and other methods, and the internal parameters of the projector and lens distortion are taken into account to improve the accuracy of the homography matrix. The plane projection geometric constraints are introduced for precise modeling, which further improves the accuracy of the homography relationship. Finally, correction is performed according to the preset error threshold to ensure that the final plane homography matrix can meet the requirements of practical applications, providing strong support for the precise control of the projector telescopic lens.

[0160] In one embodiment, the initial lens control solution is simulated and projected based on the homography relationship to obtain a simulated projected image, and parameter analysis is performed to obtain corresponding lens fine-tuning parameters, including:

[0161] A three-dimensional projection model is constructed based on the homography relationship and the initial lens control scheme. The homography relationship refers to the projection transformation relationship between two planes, which is used to describe the geometric relationship between the projector lens and the projection plane. The initial lens control scheme contains parameters such as the initial focal length and scaling of the lens. The three-dimensional projection model is a virtual three-dimensional space model used to simulate the propagation path of the projection light. During the construction process, information such as the projector lens position and the projection plane position is incorporated into the model. A ray tracing analysis is performed on the three-dimensional projection model to simulate the propagation path of the light from the projector lens to the projection plane to obtain the corresponding simulated projection light path. The ray tracing analysis uses a reverse ray tracing algorithm to trace the light from each pixel on the projection plane to the projector lens.

[0162] The simulated projection light path is pixel mapped to generate the corresponding simulated projection image matrix. Pixel mapping is the process of mapping the light path in three-dimensional space to a two-dimensional plane. The simulated projection image matrix is ​​a two-dimensional array, in which each element represents a pixel point on the projected image. By calculating the coordinates of the intersection of each light ray and the projection plane, it is mapped to the corresponding position in the image matrix.

[0163] The distortion coefficient and clarity index of the simulated projection image are calculated based on the simulated projection image matrix. The distortion coefficient is used to measure the degree of geometric deformation of the projected image, including radial distortion and tangential distortion. The clarity index is used to evaluate the clarity of the projected image, and indicators such as image gradient and edge sharpness can be used. During the calculation process, the simulated projection image matrix is ​​processed and analyzed, and relevant features are extracted and the index value is calculated.

[0164] Based on the distortion coefficient and clarity index, the initial lens control scheme is subjected to parameter sensitivity analysis to obtain the corresponding lens adjustment sensitivity curve. Parameter sensitivity analysis is to change the lens control parameters and observe the changes in the distortion coefficient and clarity index to determine the degree of influence of each parameter on the projection effect. The lens adjustment sensitivity curve is a functional relationship that describes the corresponding relationship between the changes in the lens control parameters and the changes in the projection effect index.

[0165] The initial lens control scheme is analyzed according to the preset gradient descent algorithm combined with the lens adjustment sensitivity curve to obtain the corresponding lens fine-tuning parameters. The gradient descent algorithm is an optimization algorithm used to find the local minimum of a function. In this embodiment, the projection effect index is used as the optimization objective function, and the lens control parameters are continuously adjusted through iterative calculation until the optimal parameter combination is found. The lens fine-tuning parameters are the adjustment amounts relative to the initial lens control scheme, which are used to optimize the projection effect.

[0166] This embodiment achieves accurate simulation of the projection process by constructing a three-dimensional projection model based on the homography relationship and performing ray tracing analysis, providing a reliable data basis for subsequent parameter optimization. The simulated projection image matrix is ​​generated by pixel mapping processing, which intuitively reflects the projection effect and facilitates quantitative analysis and evaluation. By calculating the distortion coefficient and clarity index, the quality of the projected image is comprehensively evaluated, providing a clear goal for parameter optimization. Based on parameter sensitivity analysis, the lens adjustment sensitivity curve is obtained, which reveals the degree of influence of each control parameter on the projection effect and helps with precise adjustment. Parameter analysis is performed in combination with the gradient descent algorithm to achieve automatic optimization of the lens control scheme and improve adjustment efficiency and accuracy.

[0167] In one embodiment, the initial lens control scheme and the lens fine-tuning parameters are comprehensively analyzed to obtain a corresponding global zoom lens adjustment strategy, including:

[0168] The initial lens control scheme and lens fine-tuning parameters are used to dynamically construct the lens telescopic response strategy. The initial lens control scheme includes the initial lens position, target position, and preset motion parameters. The lens fine-tuning parameters include real-time data such as environmental factors and projection image quality feedback. During the dynamic construction of lens telescopic response, the basic motion trajectory is set according to the initial control scheme, and the trajectory is adjusted in real time in combination with the fine-tuning parameters, ultimately forming a lens telescopic response strategy that can adapt to the current environment and needs.

[0169] The lens telescopic response strategy is subjected to an adaptive piecewise linearization process to obtain a piecewise linear control strategy. Adaptive piecewise linearization is a process of simplifying a complex nonlinear response strategy into several linear segments. Specifically, the following steps are included:

[0170] The lens telescopic response strategy is sampled in sections to obtain a response sampling point set.

[0171] The lens telescopic response curve is piecewise fitted according to the response sampling point set to obtain a piecewise linear function set.

[0172] Perform slope analysis on the piecewise linear function set to obtain the slope change threshold.

[0173] The piecewise linear function set is merged and optimized according to the slope change threshold to obtain an optimized piecewise linear function set.

[0174] The continuity test is performed on the optimized piecewise linear function set to obtain the continuity correction parameters.

[0175] The optimized piecewise linear function set is corrected according to the continuity correction parameter to obtain a corrected piecewise linear function set.

[0176] Parameters are extracted from the modified piecewise linear function set to obtain piecewise linear control parameters.

[0177] Generate a piecewise linear control strategy based on the piecewise linear control parameters.

[0178] This process ensures the accuracy and computational efficiency of the control strategy.

[0179] The lens telescopic trajectory is planned according to the piecewise linear control strategy to obtain the lens motion trajectory curve. During the trajectory planning process, the physical constraints of the lens motion, such as maximum speed and acceleration limit, are considered to generate a smooth and continuous motion curve in each linear interval. These curves together constitute a complete lens motion trajectory to ensure the stability and accuracy of the lens during motion.

[0180] The lens drive is generated according to the lens motion trajectory curve to obtain the lens drive instruction set. The drive generation process discretizes the continuous motion trajectory into a series of position, velocity and acceleration data at time points. Based on these data and the characteristics of the lens driver, the corresponding motor control instructions are generated to form a complete lens drive instruction set.

[0181] The lens drive instruction set is dynamically compensated to obtain compensated drive instructions. The dynamic compensation process takes into account possible errors and interference factors in practice, such as mechanical friction, temperature changes, etc. The original drive instructions are corrected through pre-established error models or real-time feedback data to generate compensated drive instructions to improve control accuracy.

[0182] The compensation drive command is analyzed according to the lens motion trajectory curve to obtain the global telescopic lens adjustment strategy. During the command analysis process, the compensated drive command is compared with the ideal motion trajectory to evaluate the control effect and make necessary optimization adjustments. The final global telescopic lens adjustment strategy comprehensively considers multiple factors such as the initial control scheme, real-time fine-tuning requirements, characteristics and error compensation, and can achieve high-precision and high-reliability lens telescopic control.

[0183] This embodiment realizes dynamic optimization of the lens telescopic process by comprehensively analyzing the initial lens control scheme and lens fine-tuning parameters, so that the control strategy can adapt to different environmental factors and projection requirements, and improves the flexibility and adaptability of the system. Adaptive piecewise linearization processing is used to simplify complex nonlinear responses into easy-to-implement piecewise linear control, which not only ensures control accuracy but also improves computational efficiency. The smoothness and stability of the lens movement are ensured through lens telescopic trajectory planning and drive instruction generation. The introduction of a dynamic compensation mechanism effectively overcomes errors caused by factors such as mechanical friction and temperature changes, and improves control accuracy. The final global telescopic lens adjustment strategy takes into account many factors, realizes high-precision and high-reliability lens telescopic control, and significantly improves the image quality and user experience of the projector.

[0184] Reference Figure 2 As shown, the present invention further provides a projector telescopic lens control system, which is applied to any one of the above projector telescopic lens control methods, comprising:

[0185] The acquisition module is used to obtain the lens position detection data and real-time temperature monitoring data of the projector, and perform correlation analysis to obtain the corresponding real-time lens status group;

[0186] An analysis module is used to obtain an initial projection image of the projector, and to perform a prediction analysis on the initial projection image according to the lens position detection data to obtain a corresponding image quality trend;

[0187] An association module, which is used to perform lens adjustment analysis on the real-time lens status group and image quality trend to obtain a corresponding initial lens control solution;

[0188] A processing module, the processing module is used to construct an image relationship for the initial projection image through a preset concentric circle automatic matching algorithm to obtain a homography relationship between corresponding planes;

[0189] A control module, which is used to simulate the projection of the initial lens control scheme based on the homography relationship to obtain a simulated projection image, and perform parameter analysis to obtain corresponding lens fine-tuning parameters;

[0190] The execution module is used to comprehensively analyze the initial lens control scheme and the lens fine-tuning parameters to obtain the corresponding global telescopic lens adjustment strategy.

[0191] The present invention provides a projector telescopic lens control system, which can more accurately evaluate the real-time status of the lens by correlating and analyzing lens position detection data and real-time temperature monitoring data, and provide a reliable basis for subsequent adjustments. Based on the predictive analysis of the initial projected image, possible image quality problems can be discovered and prevented in time, thereby improving the stability of the projection effect. The homography relationship between planes is established through the concentric circle automatic matching algorithm, and the initial lens control scheme is accurately simulated, thereby obtaining more accurate lens fine-tuning parameters. This comprehensive analysis and adjustment method not only improves the clarity and uniformity of the projected image, but also can adapt to different usage environments and time lengths, effectively solving the problem of reduced projection quality under long-term use or in complex environments. In addition, the method realizes the intelligence and adaptability of the projection system by formulating a global telescopic lens adjustment strategy, and can be flexibly adjusted according to different projection requirements and environmental changes to meet the requirements of diverse application scenarios.

[0192] Reference Figure 3 As shown, the present invention also provides a projector telescopic lens control computer device, comprising:

[0193] Memory, used to store programs;

[0194] The processor is used to execute the program to implement each step of any one of the above-mentioned projector telescopic lens control methods.

[0195] In this embodiment, the processor and the memory may be connected via a bus or other means. The memory may include a volatile memory, such as a random access memory; the memory may also include a non-volatile memory, such as a read-only memory, a flash memory, a hard disk, or a solid-state drive. The processor may be a general-purpose processor, such as a central processing unit, a digital signal processor, an application-specific integrated circuit, or one or more integrated circuits configured to implement the embodiments of the present invention.

[0196] It should be noted that technicians in the relevant technical field can clearly understand that for the convenience and conciseness of description, the specific working process of the system and each module described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0197] The above description is only a preferred embodiment of the present invention, and does not limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made by using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A projector telescopic lens control method, characterized in that: include: Obtain the lens position detection data and real-time temperature monitoring data of the projector, and perform correlation analysis to obtain the corresponding real-time lens status group; Acquire an initial projection image of the projector, and perform prediction analysis on the initial projection image according to the lens position detection data to obtain a corresponding image quality trend; Performing lens adjustment analysis on the real-time lens state group and the image quality trend to obtain a corresponding initial lens control solution; The image relationship of the initial projection image is constructed by using a preset concentric circle automatic matching algorithm to obtain a homography relationship between corresponding planes; Performing simulated projection on the initial lens control solution based on the homography relationship to obtain a simulated projection image, and performing parameter analysis to obtain corresponding lens fine-tuning parameters; Comprehensively analyzing the initial lens control scheme and the lens fine-tuning parameters to obtain a corresponding global telescopic lens adjustment strategy; The obtaining of the initial projection image of the projector and performing prediction analysis on the initial projection image according to the lens position detection data to obtain a corresponding image quality trend includes: Performing frequency domain transformation processing on the initial projected image to obtain corresponding frequency domain feature information; Performing clarity evaluation on the initial projected image according to the frequency domain feature information to obtain a corresponding clarity score; Establishing a mathematical mapping relationship based on the clarity score and the lens position detection data to obtain a relationship function between the lens position and the image quality; Performing numerical analysis on the relationship function to obtain a sensitivity coefficient of the effect of lens position change on image quality; Predicting and analyzing future lens positions according to the sensitivity coefficients to obtain a future lens position sequence; Performing image quality simulation calculation on the future lens position sequence to obtain a corresponding image quality trend; The image relationship construction of the initial projection image by using a preset concentric circle automatic matching algorithm to obtain a homography relationship between corresponding planes includes: Perform concentric circle projection onto a preset concentric circle array calibration plate and obtain a calibration image after projection; Performing color channel separation on the calibration image to separate the projection concentric circle component and the calibration plate concentric circle component; Calculating the coordinates of the projected concentric circle components according to the preset concentric circle projection geometric constraints to obtain the corresponding circle center pixel coordinates; Performing cross-ratio invariance analysis on the center pixel coordinates to obtain a matching relationship of concentric circles; Based on the matching relationship, a homography is calculated for the calibration plane and the projector projection plane to obtain a corresponding plane homography matrix; Using the homography matrix to estimate the internal and external parameters of the projector to obtain a calibration result of the projector; Performing distortion correction and geometric transformation on the initial projected image according to the calibration result to obtain a corrected image; Extracting and matching feature points of the corrected image and establishing a matching relationship between the images; Based on the matching relationship, homography analysis is performed on the plane homography matrix to obtain the homography relationship.

2. The projector telescopic lens control method according to claim 1, characterized in that: The obtaining of the lens position detection data and the real-time temperature monitoring data of the projector and performing correlation analysis to obtain a corresponding real-time lens status group includes: Collecting position sensor data of a projector lens, and preprocessing the position sensor data to obtain the lens position detection data; Acquire real-time temperature data of multiple temperature sensors inside the projector, and perform standardization processing on the real-time temperature data to obtain the real-time temperature monitoring data; Establishing a relationship based on the lens position detection data and the real-time temperature monitoring data to obtain a corresponding relationship between the lens position and the real-time temperature; Performing time analysis on the corresponding relationship between the lens position and the real-time temperature to obtain the change trend of the lens position and the temperature; Analyze the lens status according to the change trend to obtain lens status data; The lens position detection data, the real-time temperature monitoring data and the lens status data are integrated to obtain the real-time lens status group.

3. The projector telescopic lens control method according to claim 1, characterized in that: The performing lens adjustment analysis on the real-time lens state group and the image quality trend to obtain a corresponding initial lens control solution includes: Performing correlation analysis on the real-time lens state group to obtain a lens state correlation coefficient; Compensating the image quality trend according to the lens state correlation coefficient to obtain an image quality index; Constructing a lens adjustment objective function based on the image quality index, and performing parameter analysis and solving on the lens adjustment objective function to obtain initial lens adjustment parameters; Performing a simulated lens position adjustment according to the initial lens adjustment parameters to obtain a simulated lens state; Adaptively modifying the initial lens adjustment parameters according to the simulated lens state to obtain modified lens adjustment parameters; An output of the initial lens control scheme is generated based on the modified lens adjustment parameters.

4. The projector telescopic lens control method according to claim 1, characterized in that: The step of performing homography calculation on the calibration plane and the projector projection plane based on the matching relationship to obtain a corresponding plane homography matrix includes: Performing homogeneous coordinate transformation of the corresponding points of the concentric circles on the matching relationship to obtain a homogeneous coordinate point set; Constructing a linear equation system according to the homogeneous coordinate point set to obtain an initial homography matrix; Performing singular value decomposition on the initial homography matrix to obtain a decomposed matrix group; Extracting a rotation matrix and a translation vector based on the matrix group to obtain an initial posture estimate; Optimizing the initial homography matrix according to the initial posture estimation to obtain an optimized homography matrix; Calculate the geometric relationship between the projector projection plane and the calibration plane based on the optimized homography matrix to obtain the plane projection geometric constraint; Accurately modeling the calibration plane and the projector projection plane according to the plane projection geometric constraints to obtain an accurate homography matrix; The precise homography matrix is ​​corrected according to a preset error threshold to obtain the plane homography matrix.

5. The projector telescopic lens control method according to claim 1, characterized in that: The initial lens control scheme is simulated and projected based on the homography relationship to obtain a simulated projection image, and parameter analysis is performed to obtain corresponding lens fine-tuning parameters, including: Constructing a three-dimensional projection model according to the homography relationship and the initial lens control scheme, and performing ray tracing analysis on the three-dimensional projection model to obtain a corresponding simulated projection light path; Performing pixel mapping processing on the simulated projection light path to generate a corresponding simulated projection image matrix; Calculating the distortion coefficient and clarity index of the simulated projection image according to the simulated projection image matrix; Performing parameter sensitivity analysis on the initial lens control scheme based on the distortion coefficient and the clarity index to obtain a corresponding lens adjustment sensitivity curve; The initial lens control scheme is subjected to parameter analysis according to a preset gradient descent algorithm in combination with the lens adjustment sensitivity curve to obtain corresponding lens fine-tuning parameters.

6. The projector telescopic lens control method according to claim 1, characterized in that: The comprehensive analysis of the initial lens control scheme and the lens fine-tuning parameters to obtain a corresponding global telescopic lens adjustment strategy includes: Performing dynamic lens expansion and contraction construction on the initial lens control scheme and the lens fine-tuning parameters to obtain a lens expansion and contraction response strategy; Adaptively performing piecewise linearization processing on the lens telescopic response strategy to obtain a piecewise linear control strategy; The lens telescopic trajectory is planned according to the piecewise linear control strategy to obtain a lens motion trajectory curve; Generating lens drive according to the lens motion trajectory curve to obtain a lens drive instruction set; Performing dynamic compensation on the lens driving instruction set to obtain a compensation driving instruction; The compensation drive instruction is analyzed according to the lens motion trajectory curve to obtain the global telescopic lens adjustment strategy.

7. A projector telescopic lens control system, characterized in that: The projector telescopic lens control method applied to any one of claims 1 to 6 above comprises: An acquisition module, the acquisition module is used to obtain the lens position detection data and real-time temperature monitoring data of the projector, and perform correlation analysis to obtain a corresponding real-time lens status group; An analysis module, the analysis module is used to obtain an initial projection image of the projector, and perform a prediction analysis on the initial projection image according to the lens position detection data to obtain a corresponding image quality trend; an association module, the association module being used to perform lens adjustment analysis on the real-time lens state group and the image quality trend to obtain a corresponding initial lens control solution; A processing module, the processing module is used to construct an image relationship for the initial projection image through a preset concentric circle automatic matching algorithm to obtain a homography relationship between corresponding planes; A control module, the control module is used to simulate the projection of the initial lens control scheme based on the homography relationship to obtain a simulated projection image, and perform parameter analysis to obtain corresponding lens fine-tuning parameters; An execution module, the execution module is used to comprehensively analyze the initial lens control scheme and the lens fine-tuning parameters to obtain a corresponding global telescopic lens adjustment strategy; The obtaining of the initial projection image of the projector and performing prediction analysis on the initial projection image according to the lens position detection data to obtain a corresponding image quality trend includes: Performing frequency domain transformation processing on the initial projected image to obtain corresponding frequency domain feature information; Performing clarity evaluation on the initial projected image according to the frequency domain feature information to obtain a corresponding clarity score; Establishing a mathematical mapping relationship based on the clarity score and the lens position detection data to obtain a relationship function between the lens position and the image quality; Performing numerical analysis on the relationship function to obtain a sensitivity coefficient of the effect of lens position change on image quality; Predicting and analyzing future lens positions according to the sensitivity coefficients to obtain a future lens position sequence; Performing image quality simulation calculation on the future lens position sequence to obtain a corresponding image quality trend; The image relationship construction of the initial projection image by using a preset concentric circle automatic matching algorithm to obtain a homography relationship between corresponding planes includes: Perform concentric circle projection onto a preset concentric circle array calibration plate and obtain a calibration image after projection; Performing color channel separation on the calibration image to separate the projection concentric circle component and the calibration plate concentric circle component; Calculating the coordinates of the projected concentric circle components according to the preset concentric circle projection geometric constraints to obtain the corresponding circle center pixel coordinates; Performing cross-ratio invariance analysis on the center pixel coordinates to obtain a matching relationship of concentric circles; Based on the matching relationship, a homography is calculated for the calibration plane and the projector projection plane to obtain a corresponding plane homography matrix; Using the homography matrix to estimate the internal and external parameters of the projector to obtain a calibration result of the projector; Performing distortion correction and geometric transformation on the initial projected image according to the calibration result to obtain a corrected image; Extracting and matching feature points of the corrected image and establishing a matching relationship between the images; Based on the matching relationship, homography analysis is performed on the plane homography matrix to obtain the homography relationship.

8. A computer device for controlling a projector telescopic lens, characterized in that: include: Memory, used to store programs; A processor is used to execute the program to implement each step of a projector telescopic lens control method as described in any one of claims 1 to 6.

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