4044 results about "Ambilight" patented technology

The invention discloses a high-precision image processing method and system based on illumination adaptive compensation, and relates to the technical field of computer vision and image processing, and the method comprises the steps: inputting an original image, and dividing the image into a high-frequency edge layer, an intermediate-frequency texture layer and a low-frequency illumination layer through a multi-scale residual network; acquiring illumination intensity, color temperature and scene categories in real time by using an ambient light sensor and a scene semantic segmentation model, and generating dynamic compensation parameters; carrying out dynamic range expansion on a low-frequency illumination layer based on a physical illumination model, and adjusting the weight of highlight suppression and dark area enhancement through a self-adaptive S-shaped exposure curve; a double-branch generative adversarial network is adopted, noise suppression and super-resolution reconstruction are carried out on the high-frequency layer, and texture detail enhancement is carried out on the intermediate-frequency layer; aligning the data of the depth camera and the infrared sensor with the visible light image through a cross-modal fusion module; and performing tone mapping on the fused image based on human visual characteristics, and outputting an enhanced image with a high dynamic range and reserved details.

The invention provides a scene reconstruction method based on delayed rendering and three-dimensional Gaussian. The method comprises the following steps: S1, generating initial three-dimensional point cloud data based on a multi-view image; s2, constructing a trainable structural body for three-dimensional Gaussian modeling; s3, normal initialization and residual optimization are carried out on the Gaussian ellipsoid primitives, depth consistency constraint is combined, and a differentiable and learnable normal reconstruction mechanism is realized, so that the geometric expression ability of illumination modeling is enhanced; s4, introducing a reflection training mechanism based on ambient light and a reflection direction, and generating a Gaussian attribute based on a visual angle; and S5, a final image is generated through a differentiable Gaussian sputtering rendering algorithm, and optimization is carried out through pixel loss of the final image and a real image. According to the method, the reality sense and geometric consistency of the Gaussian sputtering model under the complex illumination condition are remarkably improved, and the technical problems of unreal rendering effect, inaccurate surface normal estimation, weak propagation capability and the like of the existing three-dimensional Gaussian sputtering model under the complex illumination condition are solved.

The invention relates to the technical field of display control, in particular to a display self-monitoring method and system and a display, and the method comprises the following steps: collecting light intensity data, comparing and classifying ambient light as low light, strong light or reflected light with a preset standard, judging whether a real-time color temperature and a standard color temperature difference value exceed a threshold value, if yes, adjusting the color temperature and the brightness, and if not, adjusting the brightness; pixel RGB channel proportions are extracted frame by frame, a color gamut distribution diagram is generated, restoration instruction time features are recorded, the color temperature adjustment trend is counted, and a backlight gradient compensation mode is generated. In the invention, the light intensity around the display is monitored in real time, the light intensity is compared with the preset illumination condition, and the ambient light condition is automatically classified, so that the display can adjust the color temperature and the brightness according to different illumination environments, and the backlight drive of the display is adjusted in time by analyzing the coverage areas of the red, green and blue channels in the display frame frame by frame; the adaptive capacity and the long-term stability of the display under variable illumination conditions are improved, and more optimized visual experience is provided for users.

The invention belongs to the technical field of intelligent lighting, and discloses an intelligent adjustment method and system for the spectrum of a quantum dot light-emitting lamp. The objective of the invention is to solve the problem that an existing lighting system cannot meet personalized healthy lighting requirements. The method comprises the following steps: firstly, acquiring user biological rhythm, environment spectrum, use scene, user preference and physiological health data through multi-dimensional data acquisition, and constructing a feature data set; then human factor optical feature extraction and cross-situation demand analysis are carried out, and a spectral response model is established; carrying out quantum dot material photoelectric characteristic mapping and spectrum synthesis modeling based on the model, and determining a luminescence parameter space; constructing a spectrum optimization model, performing multi-objective optimization by comprehensively considering visual comfort, energy efficiency and health influence, and generating a dynamic spectrum regulation and control strategy; closed-loop verification and adaptive optimization are carried out based on real-time physiological feedback, and an intelligent spectrum adjustment scheme is formed. According to the invention, the advantage of spectrum adjustability of the quantum dot material is fully exerted, and real personalized intelligent illumination is realized.

The invention provides an intelligent event identification method and system based on a high-speed camera, and the method comprises the steps: setting the collection parameters of the high-speed camera, and triggering the camera to collect a target scene video stream. And hardware acceleration decoding processing is carried out on the collected original video data stream, real-time environment illumination information of the environment illumination sensor is obtained, and dynamic brightness equalization processing is executed. And performing motion adaptive denoising processing on the video sequence. Geometric distortion correction is carried out on the image sequence through camera calibration parameters, sub-pixel-level displacement vectors and dense optical flow field data of a moving object are extracted, and multi-scale morphological features are extracted. And the features are fused to generate motion feature data, the data are processed through a spatio-temporal joint event classification model, an event identification result is output, the result is bound with a high-precision timestamp, and event identification information is output to an industrial control system display device in real time. According to the invention, the accuracy and real-time performance of event identification can be improved.

The invention relates to the field of liquid crystal display, and discloses a liquid crystal display screen dynamic contrast optimization method and system, and the method comprises the following steps: collecting ambient light intensity and backlight module temperature parameters in real time, and combining with image content entropy analysis to dynamically generate a non-uniform backlight partition grid; a brightness diffusion physical model is constructed based on hardware parameters such as the refractive index of the light guide plate and the LED spacing, and the optimal brightness of each partition is solved by adopting a temperature self-adaptive improved particle swarm algorithm; driving voltage is generated through piecewise nonlinear gamma mapping and inverse function iterative calculation, and the driving voltage is adapted to the nonlinear response characteristics of the backlight module; a hardware accelerator is used for executing a diffusion equation and optimization calculation in parallel, and model parameters are dynamically adjusted in combination with feedback of an optical sensor, so that a closed-loop control link is formed. According to the method, the contrast performance and the dynamic scene adaptability of the display screen are comprehensively improved through dynamic partition adaptive to the environment, an optimization algorithm driven by a physical model and real-time processing accelerated by hardware.

The invention relates to a light control method and system based on AI model analysis, and the method comprises the steps: obtaining environment illumination data of a target scene and user interaction input, and carrying out the semantic demand analysis, and obtaining semantic description information; performing illumination demand analysis on the semantic description information through a pre-trained light driving model to obtain illumination demand parameters; performing light field demand analysis on the illumination demand parameters according to the environment illumination data and the user interaction input, and generating light field control information; and acquiring power load data, performing instruction construction on the light field control information, and generating a light control instruction. According to the invention, dynamic self-adaptive regulation and control of the light environment can be realized, and the limitation that the existing method only depends on static compensation and cannot adapt to complex scene changes is overcome.

The invention relates to the technical field of smart lighting, in particular to a smart lighting decision optimization method based on big data, which comprises the following steps of: firstly, acquiring data of a lighting area in real time, performing spatial-temporal feature extraction on the data, the method comprises the steps of generating a region illumination demand feature vector based on a real-time feature vector, then generating a dynamic illumination optimization strategy based on a reinforcement learning model in combination with a historical illumination strategy library and the real-time feature vector, and finally adjusting brightness parameters and spectral distribution of each intelligent lamp in a region according to the dynamic illumination optimization strategy. According to the method, the data of the illumination area is collected in real time, the optimization strategy is dynamically generated in combination with the reinforcement learning model, illumination requirements of different time periods and different areas can be accurately matched, and therefore the problem that in the prior art, real-time optimization of the illumination strategy in the dynamic environment is insufficient is effectively solved.

The invention relates to the technical field of light attenuation compensation control, in particular to an automatic light source control method and system. The method comprises the following steps: acquiring historical light source operation state parameters, performing long-time-sequence operation state change evolution, and constructing a long-time-sequence light source state change curve; performing nonlinear light source attenuation analysis and multi-period light source attenuation evolution on the long-time sequence light source state change curve to construct a light source attenuation evolution model; acquiring real-time light source operation state monitoring parameters and environment illumination signals; inputting into a light source attenuation evolution model, and carrying out light source attenuation evolution simulation to obtain a light source attenuation gradient situation; and acquiring real-time working current and voltage parameters of the automatic light source, and performing adaptive light attenuation compensation optimization based on the attenuation gradient situation of the light source so as to generate an adaptive light attenuation compensation optimization engine. According to the invention, the accuracy and effect of overall compensation control of light attenuation of the light source are improved.

The invention discloses an end-to-end automatic driving method based on dynamic multi-modal fusion in a complex scene, and belongs to the technical field of automatic driving. In order to solve the problems of sensor perception deficiency, cross-modal feature mismatching, unstable trajectory planning and the like easily occurring in night, low-illumination and complex dynamic environments in the existing end-to-end automatic driving method, texture details of a camera mode and geometric structure features of a laser radar mode are respectively enhanced through a double-flow feature refining mechanism; the characteristic difference between different modes is relieved; an information-driven dynamic fusion strategy is designed, the fusion weight is adaptively adjusted according to scene factors such as environment illumination and obstacle density, and the scene sensitivity and discrimination ability of the model are improved; asymmetric convolution and a low-rank-sparse decoupling technology are introduced, multi-order reconstruction of key channels is carried out on the multi-modal features, and the path change modeling capability is enhanced; and in combination with time sequence dependence of waypoints, outputting a future trajectory through an autoregression decoder to realize high-precision trajectory prediction and stable decision control.

The invention discloses a reflecting object inverse rendering method, system and device based on two-dimensional Gaussian sputtering and multi-mode diffusion prior and a medium. The method comprises the steps that images and camera parameters of a reflecting object under multiple visual angles are acquired; calculating an observation angle according to the camera parameters; performing rasterization rendering on the images of the reflecting object under the multiple visual angles by using the trained two-dimensional Gaussian primitives under the observation visual angle to obtain a rendered image under the new visual angle; according to the method, two-dimensional Gaussian is adopted as a scene representation element, surface characteristics are better fitted, and geometric reconstruction precision can be remarkably improved; the trained two-dimensional Gaussian primitive is closer to a real three-dimensional scene, and experimental tests of multiple data sets show that the method not only can accurately reconstruct geometric and material distribution of a high-reflection area, but also can recover clear environment illumination with high-frequency details, realizes efficient and real reflection inverse rendering, and has a good application prospect. The method can be widely applied to downstream tasks such as three-dimensional reconstruction, material editing and relighting.

The invention relates to the technical field of display, and particularly discloses a dynamic ambient light adaptive OLED display optimization method and system, and the method comprises the steps: obtaining an ambient light time sequence data set of an environment where an OLED display screen is located, and synchronously obtaining real-time display parameters and historical brightness adjustment data of the display screen; acquiring ambient light sensing features according to the ambient light time sequence data set; obtaining photo-thermal structure coverage area data of the OLED display screen according to the real-time display parameters; and acquiring preliminary optimization parameters according to the ambient light sensing characteristics and the photo-thermal structure coverage area data. According to the invention, illumination intensity, spectrum drift and contrast change are captured in real time in combination with ambient light perception characteristics, the one-sidedness of adjustment only according to brightness traditionally is solved, reflection can be reduced through photothermal structure deformation under strong light, brightness can be improved to offset interference, and human visual characteristics can be matched under weak light. And the display definition and the visual comfort in different environments are effectively improved.

The invention relates to the technical field of intelligent control, and discloses a light control method and system, a controller and a storage medium, and the method comprises the steps: collecting ambient light, human traffic and user preference data through multi-sensor fusion; after normalization processing, inputting a reinforcement learning model to dynamically calculate target brightness and color temperature, and generating a control instruction to adjust a lamp; and optimizing model parameters in combination with user feedback. The system integrates a data acquisition module, an intelligent processing module, a regulation and control execution module and a feedback optimization module to form a closed-loop control chain. The controller supports PWM dimming and a DMX512 protocol, an emergency module is arranged in the controller, and illumination is maintained according to a historical mean value when communication is interrupted. Through high-precision environment perception calibration, a multi-target dynamic dimming strategy, an intelligent closed-loop learning mechanism and a distributed fault-tolerant control system, the long-standing core problems of light sensation drift, strategy adaptation stiffness, strong cold start dependence, poor cluster stability and the like in the field of intelligent illumination are systematically solved.

The invention relates to the field of commodity visualization, in particular to a commodity display interaction visualization method and device. The method comprises the following steps: collecting a multi-azimuth image of a commodity, carrying out three-dimensional texture modeling, and constructing a three-dimensional texture mapping model; performing material light rendering on the three-dimensional texture mapping model to generate a material rendering result; collecting an environment detection image of a commodity display environment, and performing environment illumination adaptation compensation on a material rendering result to obtain an illumination compensation rendering commodity; carrying out attribute information visual layout on the illumination compensation rendering commodity to obtain a commodity visual space; and carrying out interaction response animation analysis according to the commodity visualization space, carrying out multi-target parallel rendering, and executing commodity interaction visualization operation. The form and surface details of the commodity in the real world are accurately restored, the visual reality sense is improved, and the interactive experience feeling of browsing the commodity by a user is enhanced.

The invention discloses a hidden camera detection method and system based on a cat eye effect, computer equipment and a storage medium, and relates to the technical field of laser imaging, and the method comprises the steps: sensing ambient light, carrying out the initialization, and carrying out the parameter adjustment in real time; transmitting a signal through a multispectral light source, and receiving a reflected signal for multiband imaging; carrying out adaptive binarization processing on the image, and calculating a local gray scale probability distribution matrix of the image; and calculating a suspected degree for target detection, and giving an alarm when a camera is recognized. According to the hidden camera detection method based on the cat eye effect, through automatic switching of multi-band light sources, the types of the light sources are optimized, detection light of different wavelengths is emitted, the broad spectrum range is covered, the reflection characteristics of various hidden imaging devices are dealt with, detection is carried out according to imaging of different light sources, and the detection accuracy is improved. The method can be used for detecting the anti-reconnaissance hidden imaging equipment.

The invention relates to the technical field of optical lens defect detection, and particularly discloses an optical lens laser-induced damage on-line detection method and system, a linear polarizer and a narrow-band filter are connected in series in a detection laser light path, non-target polarized light is filtered through polarization direction matching, meanwhile, interference of the environment and scattered light is inhibited through the narrow-band filter, and the laser-induced damage on-line detection system is obtained. According to the method, external source noise such as ambient light and non-target polarized light is reduced through polarization matching and narrow-band filtering, randomness of speckle noise is offset through multi-angle collection and signal fusion in a visual detection mode, exposure is dynamically adjusted, an image is fused to improve the signal-to-noise ratio, noise and real signals are decoupled through self-supervised learning, and the real-time performance of the system is improved. Dust interference is removed in combination with morphological operation; a deep learning reasoning model enhances the damage identification capability in a noise environment, defocusing blur caused by mechanical vibration is eliminated through phase conjugate correction, and the influence of photoelectric conversion noise, dust interference and the like on the detection efficiency and accuracy is remarkably reduced through multi-link linkage.

The invention discloses a virtual-real fusion exhibition display interaction system and a multi-mode perception method, and belongs to the technical field of exhibition display interaction. The system collects audience eyeball fixation points, gesture actions and ambient light data through AR / VR equipment, analyzes coordinates of a region of interest through an eyeball fixation point attention mechanism, a gesture space-time encoder and a multi-modal fusion unit, triggers holographic projection explanation and virtual exhibition stand light and shadow dynamic adjustment (including illumination intensity, color, Gaussian blur and the like) based on a threshold value, and performs real-time display on the virtual exhibition stand. And multi-user collaborative interaction is realized through federal learning. According to the method, reinforcement learning is adopted to optimize an event-driven threshold value, and virtual and real visual splitting is eliminated in combination with ambient light adaptive mapping. The problems of low participation degree, insufficient single-mode interaction information and multi-user cooperation of traditional exhibition are solved, interest analysis accuracy is improved through multi-mode fusion, personalized experience is enhanced through dynamic interaction, the method is suitable for multiple scenes such as museums and science and technology museums, and exhibition intellectualization, immersion and group interaction efficiency are effectively improved.

The invention relates to the technical field of organic light-emitting display data processing, in particular to an adaptive adjustment method for active matrix organic light-emitting display. In combination with current stress parameter fluctuation captured by the programmable current sampling module and heat distribution data of the temperature sensor network, the dynamic aging model micro-service cluster is input for parameter coupling calculation, and time-varying degradation characteristic parameters are output; the containerized simulation micro-service constructs a virtual aging scene based on the parameters and generates a compensation coefficient matrix; according to the method, the problem of compensation deviation caused by the fact that a traditional static model cannot adapt to current stress, temperature bias and a material relaxation coupling effect is solved, dynamic balance of display brightness, color gamut and power consumption is achieved, and the service life of a display panel is prolonged.

The invention relates to the technical field of augmented reality and industrial safety monitoring, in particular to an AR glasses dangerous state dynamic labeling method and system based on multi-source perception, and the method comprises the steps: synchronously collecting data such as a depth image and gas concentration through multi-source equipment such as a depth camera and a gas sensor; extracting rotation invariant point cloud features through an improved dangerous target detection model, and fusing multi-modal data to generate a dynamic danger level; based on VIO, realizing accurate spatial registration of annotation and a real scene, and generating a self-adaptive annotation style according to a danger level; and multi-device labeling pose synchronization is realized through an entropy weighting ICP algorithm, and labeling transparency and size are dynamically optimized in combination with a user fatigue value and environment illumination. According to the method, the comprehensiveness of danger identification and the accuracy of marking are improved, team collaborative operation is supported, the method is suitable for scenes such as electric power inspection and dangerous chemical transportation, and the operation safety and efficiency are guaranteed.

The invention provides a roof leakage point intelligent positioning method and system based on machine vision, and relates to the technical field of constructional engineering detection.The method comprises the steps that 1, roof image data and surface texture, temperature field and environment illumination parameters are collected through a visible light and infrared thermal imaging two-channel sensing device, a multi-dimensional data set is constructed, and a multi-dimensional data set is established; generating visual data through dynamic range correction based on the multi-dimensional data set; step 2, based on visual data, performing detection area division on the acquired image, extracting a local temperature difference gradient, a surface texture abrupt change rate and a liquid flow track parameter, and establishing a multi-index characteristic matrix; according to the method, the features of the roof image are extracted through machine vision, intelligent positioning, risk grade division and dynamic evolution tracking of roof leakage points are realized, and the leakage positioning accuracy is improved.

The invention relates to the technical field of automatic induction, and discloses an automatic induction lamplight angle adjustment control method and device and lighting equipment. The method comprises the following steps: acquiring ambient light parameters in real time to obtain ambient light sensing data; performing multi-scale space division and feature fusion on the ambient light sensing data to obtain a three-dimensional ambient light distribution diagram; inputting the three-dimensional ambient light distribution diagram into a light angle calculation network for light change characteristic analysis to obtain a light optimal angle parameter group; performing smooth transition light sequence calculation according to the light optimal angle parameter group and the current light configuration state to obtain a sectional light adjustment control instruction; and performing motion path planning on the end effector of the lamp based on the sectional light adjustment control instruction to obtain an effector motion instruction set. According to the invention, light change characteristics of different spatial scales can be captured at the same time, and the adjustment accuracy and adaptability of the actuator are improved.

The invention discloses a BIM-based process simulation and consultation service support system and method, and relates to the technical field of three-dimensional modeling and visualization. The system comprises a BIM holographic data acquisition module, a process logic intelligent deconstruction module, a dynamic process simulation engine module, a physical field real-time monitoring module, an expert knowledge decision module and a visual scheme generation module. And multi-dimensional deviation early warning thresholds are set for different construction stages, the accuracy of conflict detection of various processes is ensured, meanwhile, environment illumination parameters collected by a sensor are linked with a BIM rendering engine in real time, the problem of light and shadow distortion in a digital twinning scene can be dynamically corrected, material texture misjudgment caused by illumination color temperature deviation is avoided, and the working efficiency of the digital twinning scene is improved. The accuracy of process conflict early warning is improved, and the construction safety risk and the resource scheduling error are reduced.

The invention relates to the technical field of light source adjustment, in particular to an automatic light source adjustment method and system based on real-time environment change. The method comprises the following steps: collecting environment illumination monitoring parameters of an automatic light source, and carrying out real-time light path tracking and dynamic light environment perception modeling to construct a real-time light environment perception map; obtaining an automatic light source historical operation report, carrying out light source parameter preference mining, and carrying out adaptive light source adjustment according to a real-time light environment perception map so as to construct an initial light source regulation and control strategy; performing light source control execution according to the initial light source regulation and control strategy, performing space light source disturbance detection, and generating disturbance light source multi-dimensional features; and performing light source change situation evolution analysis on the multi-dimensional characteristics of the disturbed light source, performing intelligent light disturbance reverse compensation, and constructing an intelligent anti-interference light source regulation and control strategy. According to the invention, real-time light source compensation adjustment is carried out according to environment light source changes, and accurate and rapid user light source demand response is realized.

The invention relates to the technical field of image processing, in particular to an image imaging method based on an anti-ambient light interference technology and image acquisition equipment thereof. According to the method, a photoelectric sensor is used for receiving a mixed optical signal reflected by a target, a tunable optical filter is used for extracting a reflected light component containing pulse coding characteristics, and an anti-interference characteristic pattern with a time dimension identifier is generated; based on the time dimension identifier of the anti-interference feature map, identifying an effective reflection region meeting a preset reflection characteristic threshold in the target scene, and marking a transient interference region generated by direct illumination of ambient light; and performing differential operation on the light intensity data of the effective reflection area and the spectral characteristics of the transient interference area, and reconstructing a target intrinsic image shielded by light. According to the invention, the imaging definition and the target identification reliability under severe illumination conditions such as backlight and strong light can be improved.

The invention relates to the technical field of projection display, and discloses a projection curtain light field display gain method and system used under ambient light. According to the method, environment light data, projection curtain data and original output signals of projection equipment are collected in real time, and a dynamic light field distribution model is established after fusion processing. And based on the dynamic light field distribution model, adopting an adaptive genetic algorithm to optimize a compensation weight, generating a light field compensation parameter set, performing reverse compensation processing of brightness gain, contrast and chromaticity offset on an original output signal, and generating an enhanced projection signal. The system comprises a multi-source data acquisition module, a light field feature extraction module, a dynamic compensation calculation module, a signal enhancement processing module and a closed-loop feedback control module, ensures that the projection image keeps an optimal display effect under different ambient light conditions, and remarkably improves the watching experience of audiences.

The invention provides an LED lamp intelligent energy-saving control method and system, and the method comprises the steps: obtaining environment illumination intensity data, personnel flow density data and current working state parameters of an LED lamp, which are collected by a plurality of sensors, carrying out the preprocessing of the original data of the sensors, and obtaining a standardized environment perception data set; calculating power resources required by the intelligent control system are evaluated according to the LED lamp control parameter optimization scheme, the brightness output of the LED lamp is controlled according to the calculating power resources, and the current proportion of red, green and blue LED chips is adjusted according to the color temperature; whether the light beam angle needs to be adjusted or not is judged through matching analysis of the light beam angle and environmental perception data, if yes, the lens position of the LED lamp is changed, and the output spectral characteristics of the LED lamp are measured and determined through a spectrum analyzer; after sensor calibration parameters are updated, LED lamp power consumption data are collected, and if the deviation between actual power consumption and a theoretical calculation value is smaller than a preset percentage, it is determined that the energy-saving control effect reaches an expected target.

The invention relates to the technical field of LED dimming control, in particular to an LED ceiling lamp control system based on dynamic light source adjustment, which comprises a brightness sensing module, a dimming decision module, a light source regulation and control module, an anomaly detection module and a brightness optimization module. According to the invention, the operation load of the lamp is dynamically measured and calculated by combining ambient light and thermal radiation data, the collaborative perception of illumination intensity and thermal energy distribution is realized, the response sensitivity to weak brightness change is improved by comparing the brightness demand with the real-time output deviation and accurately identifying the dimming trigger condition, and the response sensitivity to weak brightness change is improved by comparing the initial brightness with the feedback difference value. The brightness of a plurality of lamps can be adjusted coordinately, the spatial light environment is kept stable and consistent, overload and temperature rise abnormity can be checked and abnormal lamps can be identified by combining current fluctuation and temperature abrupt change analysis, an intervention record and reaction duration comparison mechanism is introduced into a regulation and control instruction, the response efficiency is improved, and the efficiency is improved. And brightness priority adjustment and overall illumination balance control of the key area are realized.

The invention discloses a monitoring image processing method and system for high-precision target tracking, and belongs to the technical field of monitoring processing, and the method specifically comprises the steps: collecting polarization data of incident light in a monitoring scene, and generating a physical attribute signature of a light source; carrying out space-time clustering analysis on pixel points of which the variable quantity exceeds an environment illumination baseline in the monitoring scene to form a physical boundary of an illumination mutation region; obtaining motion trail data of the target vehicle, and generating a motion trail space area of the target vehicle; marking an overlapping region of the physical boundary of the illumination abrupt change region and the motion trail space region as a dynamic interference source influence region; if the predicted position of the target vehicle is located in the dynamic interference source influence area, calling an exposure control parameter and a gain control parameter corresponding to the physical attribute signature, calculating a focusing control parameter according to the scene depth of the predicted position, and loading the focusing control parameter to a sensor control unit; according to the method, the problem of target key frame loss caused by AE / AF delay under dynamic illumination is effectively solved.

The invention provides a self-adaptive color depth optimization method for a liquid crystal display screen, which comprises the following steps of: acquiring manual adjustment operations of a user on brightness, contrast and color parameters of the liquid crystal display screen in different use scenes to form a user preference data set; according to the user preference data set, a data classification method is adopted to classify manual adjustment operations in different use scenes, and features of ambient light and content types are extracted to determine preference feature distribution of a user in a specific scene, and a personalized color preference model is constructed; preliminary calibration is carried out in combination with a dynamic balance algorithm, and display parameters are optimized through a continuous learning mechanism and secondary calibration. The problem that in the prior art, color adjustment of a liquid crystal display screen lacks individuation and scene self-adaption capacity is solved, continuous self-adaption of the display effect is achieved, manual intervention of a user is reduced, and the individuation degree and comfort degree of visual experience are improved.

The invention provides an AR-based bridge crack detection analysis method and system, and relates to the technical field of bridge detection analysis, and the technical scheme is characterized in that the method comprises the steps: monitoring the ambient light parameters of a bridge detection region; adjusting illumination output to stabilize imaging illumination conditions of the crack region; acquiring a crack image, and acquiring polarization information of the crack; stokes parameters are calculated, and a polarization degree image and a polarization angle image are generated; extracting a crack two-dimensional contour based on the polarization degree image and the polarization angle image; fusing the two-dimensional contour of the crack with the depth data to generate a three-dimensional model of the crack; and based on the crack three-dimensional model, crack geometric parameter quantitative analysis and multi-stage evolution state evaluation are carried out. The AR-based bridge crack detection and analysis method and system provided by the invention have the advantages of overcoming the influence of outdoor complex illumination conditions on image acquisition quality, improving the accuracy of crack recognition and three-dimensional modeling, and supporting reliable multi-stage evolution state evaluation.