4873 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 relates to the field of inductive control of illuminating lamps, in particular to an inductive control system of an inductive LED illuminating lamp. The method comprises the following steps: the lighting scene module is used for identifying all LED lighting lamps in an area; calculating node positions of all the LED lighting lamps in the area one by one, and identifying use scenes in the area to construct a plurality of LED lighting scene sub-areas; the ambient light feature module is used for acquiring ambient light parameters of a scene sub-region; performing light spatial distribution tracking on the ambient light parameters of the scene sub-regions, and performing ambient light state feature mining to generate ambient light comprehensive state features; and the multi-area lighting cooperation module is used for carrying out dynamic light source output parameter adjustment and multi-area lighting cooperation smoothing on the plurality of LED lighting scene sub-areas based on the environment light comprehensive state characteristics so as to generate multi-area lighting cooperation control parameters. According to the invention, rapid and accurate induction control of the LED illuminating lamp is realized.

The invention relates to the technical field of image processing, and discloses a display method and system for a vehicle-mounted LED display screen. The method comprises the following steps: acquiring ambient light intensity data, performing fusion processing to obtain a characteristic value, and predicting ambient light change; identifying a driving scene according to the road condition data, and analyzing the priority by combining the ambient light change data; arranging a display area in combination with the eye movement data, and determining display parameters; analyzing the multi-modal interaction data, determining an interaction strategy, and verifying to generate response data; adjusting display content according to the ambient light features, and outputting a display effect in combination with response data; and energy consumption is estimated by integrating various data, and control parameters are generated to adjust an LED driving circuit. Through intelligent analysis and processing of multi-dimensional data such as ambient light intensity, driving scene and eye movement tracking, dynamic optimization and energy-saving control of display content are realized, and the problem that display effect and energy efficiency are difficult to consider in the prior art is overcome.

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 embodiment of the invention provides an intelligent illumination automatic adjustment method and device based on illumination intensity and personnel detection, and reliability evaluation and abnormity correction are carried out on data by synchronously collecting environment illumination intensity and personnel activity data. An illumination activity association model is innovatively constructed, and feature fusion is realized by using a fuzzy logic algorithm. The system establishes a complete evaluation index system including illumination uniformity, a color rendering index and a glare value, and performs constraint optimization based on an illumination scene adaptation model. Through introducing a dynamic compensation mechanism of a personnel detection probability value and a time period priority factor, accurate illumination adjustment control is realized. The method breaks through the limitation of dimming in a traditional fixed mode, and provides a comprehensive technical solution for an intelligent lighting system.

The invention discloses a product detection method and system based on machine vision, and relates to the technical field of machine vision, and the method comprises the steps: initializing an ambient light sensor, evaluating an initial illumination condition, and dynamically adjusting a light source parameter to verify and lock an optimal setting; selecting a preset wavelength range to configure a spectral imaging system to collect image data according to the characteristics of the building material, performing primary processing and image synthesis to obtain a comprehensive spectral image, and performing feature extraction to obtain a high-quality image data set; preprocessing an image data set on edge equipment, deploying a deep learning model to carry out preliminary defect detection, identifying and marking defect types, and extracting local and frequency domain features; and refining defect types by using a classification algorithm according to the preliminary detection result, integrating a final classification result and image data, and transmitting to a cloud to complete detection. According to the invention, high-precision and high-efficiency product defect detection is realized.

The invention relates to the technical field of building energy saving, in particular to a building energy-saving management system and method based on the Internet of Things. The method comprises the following steps: acquiring a target architectural design drawing; building structure feature point recognition is carried out on the target building design drawing, three-dimensional space point cloud modeling is carried out, and a building three-dimensional structure model is constructed; building environment illumination parameters and personnel flow monitoring parameters are collected based on multiple sensor nodes; environment light intensity space distribution analysis is carried out on the building environment illumination parameters, then dynamic light intensity distribution rendering is carried out, and an environment light intensity distribution rendering model is constructed; and according to the building three-dimensional structure model, carrying out regional use scene analysis on the environment light intensity distribution rendering model, and carrying out optimal time sequence illumination demand fitting so as to construct an optimal illumination demand time sequence curve of each region. The energy consumption utilization rate of the building is increased, and accurate equipment regulation and control are achieved.

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 relates to the technical field of spherical display screens, and discloses a visual enhancement method and system for an LED creative spherical display screen, and the method comprises the steps: inputting an original display image of the LED spherical display screen into a multi-scale Transform layered CNN network for feature extraction, and obtaining a multi-dimensional feature image set; feature mapping is carried out, pixel points are projected into a spherical coordinate system, display deviation is calculated, and a comprehensive evaluation matrix is generated; calculating a space compensation coefficient through an N-order polynomial function to obtain a space-time compensation matrix; performing gradient calculation on the space-time compensation matrix to obtain a target vector field; inputting the target vector field into a U-Net structure generator for adversarial training to obtain compensation optimization parameters; according to the method, the real-time dynamic optimization of the display image of the spherical display screen is realized, and the display quality under different environment illumination conditions is ensured.

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 the technical field of intelligent lighting, and discloses a light emitting diode intelligent dimming system based on multispectral control, which comprises a multi-sensor data acquisition module, a data fusion processing unit, a user behavior prediction module, a dynamic spectrum adjustment module and the like. Environmental data are collected in real time through multiple sensors, user behaviors are predicted in combination with a machine learning algorithm, and personalized adjustment and dynamic response of illumination are achieved. The system can accurately adjust the color temperature, brightness and spectral distribution of the light source according to the changes of ambient light, temperature and humidity, human body activities and the like, and provides a more efficient and energy-saving illumination scheme. Meanwhile, through cooperative work of the Internet of Things technology and intelligent equipment, the comfort level of the whole environment is optimized. Particularly, the intelligent feedback and learning module of the system continuously optimizes the control strategy according to the use feedback of the user, the user experience and the adaptability of the system are further improved, and a comfortable and intelligent lighting environment is provided for the user.

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 three-dimensional modeling, and provides a satellite three-dimensional reconstruction method in a complex illumination environment, which comprises the following steps: acquiring images under different illumination conditions, and extracting image features by combining multi-view collaborative observation; performing feature point and multi-view data registration, generating a three-dimensional model and analyzing illumination change; performing system initialization by using the initially matched feature points, and establishing an initial three-dimensional point cloud model; sparse point cloud is recovered through multi-view stereoscopic vision, and motion recovery is carried out; a 2D diffusion model is used to complement the shielded area, and laser radar data is combined to carry out densification processing on the sparse point cloud; a three-dimensional grid model is generated, and texture mapping is carried out by a multi-view image; light compensation is adopted, a polarized light separation technology is used, and ambient light and specular reflection light are separated; according to the method, through multi-view-angle collaborative observation, the shielding problem under a single view angle is reduced, the 2D diffusion model is used for complementing the shielded area, and the completeness and precision of three-dimensional reconstruction are ensured.

The invention relates to the technical field of display screen color adjustment, and discloses a display screen color adjustment method and system based on environment information, and the method comprises the steps: obtaining display content data, environment color data, environment light data and a display screen type of a display screen; calculating color perception data according to the environment color data and the display screen type, and performing data processing on the color perception data to obtain chromaticity feedback data; establishing a relationship between the ambient light data and user preferences through a support vector machine method to obtain user evaluation data; inputting the chromaticity feedback data and the user evaluation data into a color correction model to obtain color adjustment data; classifying the display content data and calculating a type weight index through a squirrel optimization algorithm to obtain a weight index; and generating a color adjustment instruction according to the color adjustment data and the weight index, and performing adaptive adjustment on the display content. The method solves the problems that the color adjustment of the display screen has high requirements on a light source environment and is strong in subjectivity.

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 belongs to the field of screen color gamut correction, and discloses a mobile phone screen color gamut correction method and system, and the method comprises the steps: S1, obtaining ambient light data and screen content data; s2, acquiring color correction parameters based on the ambient light data and the screen content data; s3, obtaining personalized correction parameters based on the color correction parameters; s4, obtaining partition correction parameters based on the personalized correction parameters; s5, acquiring an adaptive feedback correction parameter based on the partition correction parameter; and S6, obtaining the display color of the screen based on the adaptive feedback correction parameter. The invention provides a nonlinear color gamut mapping model so as to ensure that parameters after color correction can be accurately mapped to a color gamut range capable of being displayed by a screen. In the mapping process, the nonlinear coefficient of the mapping function needs to be dynamically adjusted according to the actual display characteristics of the screen, and the consistency of color display under different brightness and contrast ratios is ensured.

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.