56 results about "Light perception" patented technology

The invention relates to the technical field of screen display adjustment and visual health protection, and discloses a screen color temperature intelligent adjustment method and system, and the method comprises the steps: obtaining a user face image sequence and ambient light perception data; according to the face image sequence, eye features are extracted, a dynamic change trend is analyzed, blinking frequency and eyelid closing duration data are calculated, and a visual fatigue evaluation value is obtained; according to the ambient light sensing data and the visual fatigue evaluation value, correcting the fatigue degree and classifying fatigue stages to obtain color temperature and brightness adjustment parameters; and transmitting the adjustment parameter to a screen display driver for gradual change processing to obtain a final screen display configuration. According to the method, personalized accurate adjustment of the screen parameters is realized, visual fatigue is effectively relieved, and the use experience and the visual health protection effect are improved.

The invention discloses a low-light image enhancement method and system based on a learnable YUV space, and the method comprises the following steps: S1, obtaining an original RGB image collected in a low-light environment, and carrying out the preprocessing of the original RGB image; s2, mapping the preprocessed RGB image to a learnable YUV color space, and decoupling to obtain a brightness component and a chrominance component; s3, obtaining an enhanced brightness feature by using the brightness component and introducing an illumination perception position coding mechanism; s4, performing multi-branch parallel denoising and pixel-level dynamic fusion on the chrominance component to obtain a purified chrominance component; s5, fusing the enhanced brightness component and the purified chrominance component, and performing color correction; and S6, the corrected YUV image is inversely converted into an enhanced RGB image. According to the method, the image is mapped to the learnable YUV space and is decoupled, and multiple enhancement and correction mechanisms are combined, so that brightness enhancement, color correction and quality improvement of the low-illumination image are realized.

The application relates to an adaptive control system for dynamic sensitivity adjustment of a photoelectric sensor, comprising: a photoelectric sensor, the sensitivity parameter of which can be adjusted online, used for collecting and outputting an image sequence; a target detection and feedback unit, used for carrying out target detection on the image sequence output by the photoelectric sensor, obtaining a boundary box of the target, a detection confidence and a local signal-to-noise ratio expectation value of the target area; an ambient light sensing unit, used for acquiring an ambient light intensity and generating a predicted ambient light intensity; a prediction model unit, used for predicting a scene displacement amplitude of a next frame based on a motion vector of a current image frame; and a parameter solving unit, which is internally provided with a sensor response model and a motion blur probability model, and is used for constructing a cost function with the sensitivity parameter as a variable; the application can realize better adaptive control.

This application relates to the field of autonomous driving technology, specifically providing a traffic light perception method, a device control method, a device, and a medium, aiming to solve the problem of accurately perceiving the state of traffic lights. To this end, the method provided in this application includes acquiring an environmental image collected by a smart device, the environmental image containing traffic lights; inputting the environmental image into a traffic light perception model for processing to obtain a virtual light corresponding to the environmental image; the virtual light is used by the smart device for driving control, the virtual light including multiple traffic direction indicators and the indication state of each traffic direction, the traffic direction indicators being used to indicate the driving direction of the smart device; the traffic light perception model is trained based on samples of the environmental image and their annotation information, the annotation information including the virtual light corresponding to the sample. Based on the above method, the traffic direction indicators and their indication states at intersections can be accurately obtained.

The application relates to the technical field of large structure measurement, and discloses a robot laser vision three-dimensional scanning measurement system for large structural parts. The system comprises a robot motion platform, a laser vision sensing module, an ambient light sensing module, a point cloud processing module and a motion control module, wherein the laser vision sensing module is arranged at the tail end of the robot motion platform. The ambient light sensing module collects ambient light intensity distribution data in real time, the motion control module generates multi-view dynamic scanning path instructions in combination with the data and three-dimensional model data of the large structural part to be measured, the robot motion platform executes the instructions to drive the laser vision sensing module to move, the module projects a laser stripe to the surface of the structural part to be measured and synchronously collects images, and the point cloud processing module generates three-dimensional point cloud data after adaptive filtering processing of the images, so that the efficient and accurate measurement requirement of the large structural part in a complex industrial environment can be met.

This invention discloses a vision-electrophysiological multimodal eye-tracking zoom control system and zoom glasses, relating to the field of zoom glasses technology. The zoom optical element has at least one control area. The multimodal sensing unit includes a vision detection module, an EOG detection module, and an ambient light sensing module, used to collect the wearer's eye state information, periocular potential information, and ambient light information, respectively, when the glasses are worn. A cross-modal adaptive calibration unit is used to calibrate the eye state information using periocular potential information when the ambient light information does not meet preset lighting conditions. The focus control unit is used to calculate the eye's gaze direction and gaze distance based on the eye state information, determine the target control area based on the gaze direction, generate focus control parameters based on the gaze distance, and drive the target control area to focus using the focus control parameters. This invention improves zoom performance by coordinating visual signals and EOG signals.

The invention discloses an illumination perception adaptive method and system for night pedestrian re-identification. The method comprises the following steps: S1, obtaining an input image; s2, processing the input image through an illumination perception image preprocessing network, and dynamically generating an enhancement coefficient graph and a noise confidence graph; s3, performing detail enhancement on the input image through an adaptive enhancement branch to obtain an enhanced image; performing noise suppression on the input image through a feature purification module to obtain a purified image; s4, performing feature extraction on the enhanced image and the purified image by using a shared backbone network to obtain enhanced features and purified features respectively; and S5, fusing the enhancement feature and the purification feature through an illumination perception controller to obtain a final identity representation. According to the invention, through end-to-end illumination perception adaptive processing, image enhancement and feature purification are effectively cooperated, and the discrimination capability and robustness of a night pedestrian re-identification model in a low-light environment are significantly improved.

The invention relates to the technical field of backlight intelligent adjustment, and discloses a keyboard backlight intelligent adjustment system and method with ambient light perception. The method comprises the following steps: collecting an environment illumination time sequence, calculating a stable illumination value, and synchronously obtaining a keyboard visual angle and a key pressing state; adjusting the first peak duty ratio according to the stable illumination value to obtain a second peak duty ratio and carrying out duty ratio distribution to obtain a target duty ratio of each local dimming unit and a brightness difference value between adjacent units; calculating a perception artifact intensity value, and converting the target duty ratio of each local dimming unit into rendering duty ratio data; and when the perceived artifact intensity value exceeds a preset artifact threshold value, outputting a PWM driving signal according to the rendering duty ratio data. According to the invention, backlight PWM modulation and dynamic rendering control of artifact suppression are perceived through the keyboard local dimming unit driven by ambient light, so that intelligent backlight adjustment in a total ambient light illuminance range is realized.

The embodiment of the present application provides a kind of light perception structure group, spectral imager and its use method.The light perception structure group includes hot light detector, including at least one feature unit structure, the feature unit structure includes multiple metal nano structures;And mobile device, including at least one moving component, the moving component is set to one-to-one group corresponding with the feature unit structure;The moving component is set to drive the feature unit structure to move, to change the relative position of the feature unit structure and the light source to be detected.The light perception structure group provided in the embodiment of the present application is set by moving component, and the feature unit structure is moved by moving component, to change the relative position of the feature unit structure and the light source to be detected, reduces the structural complexity of spectral imager, and realizes the perception of spectrum in ultra-wideband range.

This invention provides a multi-channel image fusion method and system based on coupled learning under ultra-low illumination conditions. The method includes preprocessing a dataset of low-light images with a preset sample size, followed by photometric feature extraction. This includes: constructing a multi-level attention model for light perception information extraction; constructing the photometric probability of the output image from the photometric information extraction network; building an auxiliary module for extracting common important features of the same target; and using convolutional dimensionality reduction to retain the optimal features selected from each channel image. Based on the images contained in the low-light image dataset, a multi-path image fusion framework is trained, including a synthesis learning stage and a reverse optimization stage, fusing the images to form the multi-path image fusion framework. The preprocessed images are input into the multi-path image fusion framework, and the fused image is output. The multi-channel image fusion method proposed in this invention can effectively preserve the light intensity and foreground / background information in each image while reducing the phenomenon of missing effective information and redundant invalid information during the network learning process.

This application relates to a method, system, device, and medium for detecting visual function depth in patients with no light perception. It is applied in the field of visual function testing technology. The method includes: acquiring basic information, historical testing data, and parameter fixing rules for the target patient; generating an initial testing plan based on the basic information, historical testing data, and parameter fixing rules; performing visual function testing on the target patient based on the initial testing plan, generating real-time testing data and real-time operational data; adjusting the initial testing plan in real-time based on the real-time testing data and real-time operational data to generate a visual function testing plan; acquiring full-process testing data and full-process operational data; and generating a visual function depth testing report based on the visual function testing plan, full-process testing data, and full-process operational data. This application improves the accuracy of visual function testing and evaluation in patients with no light perception.

The application provides a tunnel lighting energy consumption optimization method and system based on ambient light perception, relates to the technical field of lighting control, obtains a low-frequency light inertia component and a high-frequency light impact component by performing light fluctuation inertia decomposition on a time-series ambient light sequence; constructs a light field strain distribution map through a lighting unit grid, the low-frequency light inertia component and the high-frequency light impact component; further determines a compensation boundary according to a traffic flow prediction sequence and the light field strain distribution map; and performs multi-target light energy redistribution within the compensation boundary to obtain a light efficiency trade-off cluster, determines strain feedback values of different lighting units based on the light efficiency trade-off cluster; and relaxes and corrects the process of multi-target light energy redistribution according to all the strain feedback values. The application can realize decoupling perception of slow-changing trends and fast-changing disturbances of ambient light, and can fuse traffic flow forward-looking prediction and relaxation correction of light field strain feedback to improve the energy consumption optimization capability of tunnel lighting under multiple working conditions.

The application provides a vehicle 3D model light rendering method, system, electronic equipment and medium, and belongs to the technical field of vehicles. The method comprises the following steps: acquiring an aerial panoramic image collected by a surround-view camera; processing the aerial panoramic image to obtain a binary mask for marking a shadow area of a vehicle; performing main light source parameter estimation based on a vehicle 3D model, the aerial panoramic image and the binary mask to obtain a main light source parameter set; determining an ambient light parameter based on the aerial panoramic image and the binary mask; and performing 3D vehicle model rendering based on the main light source parameter set, the ambient light parameter, the vehicle 3D model and the aerial panoramic image. The application uses the shadow projected by the vehicle itself as an information source for light perception, realizes closed-loop light perception and can adapt to complex scenes. Through accurate light source direction calculation and full parameter estimation, the application provides a mathematical basis for generating correct shadow projection and mirror reflection effects, and significantly improves the realism of rendering.

The invention discloses an intelligent dimming system, method and device based on ambient light self-adaption, and belongs to the technical field of intelligent wearing and visual protection. The system comprises an ambient light acquisition module, a control decision module, a self-adaptive dimming module, a power supply and safety management module and a man-machine interaction module. The control decision module performs weighted fusion and sudden change detection on illumination data from multiple directions in the circumferential direction of the helmet, and generates a target light transmittance signal in combination with proportional-integral-differential control and a rate limiting algorithm so as to drive the electrochromic mask to realize smooth dimming; the power supply and safety management module automatically triggers a power-off recovery strategy to ensure the lowest view when power is low or abnormal; and the man-machine interaction module records user preferences and realizes personalized learning. According to the system, multi-dimensional light perception and self-adaptive closed-loop control are achieved, stable brightness and clear view can be kept in the environments of strong light, dark light and sudden change light, and riding safety and visual comfort are remarkably improved.

The application relates to the field of intelligent medical treatment, in particular to a dynamic data processing method, device and program product based on an eye refraction state. The method comprises the following steps: acquiring initial refraction data and environment data of an eye of a person to be measured; preprocessing the initial refraction data and the environment data to obtain preprocessing data; calculating the eye refraction data by using a refraction state influence function; and wherein the refraction state influence function is obtained by calculating the dynamic change relationship between the initial eye refraction data and the environment data. The application can solve the personalized expression of the difference in light perception of different myopia degrees, dynamically predict the brightness and color temperature parameters, drive the actual lighting equipment, realize the dynamic balance of visual comfort and environmental adaptability, and has good practical application value.

The present application relates to the technical field of geological disaster monitoring, and specifically discloses a slope disaster nimble sensing system, device and platform based on deep learning, which comprises a slope disaster sample library construction module, a slope disaster information real-time extraction model construction module, a global feature extraction module, a non-local feature extraction module, a slope disaster information real-time extraction model training module and a quantization compression module. The system can realize model quantization deployment on an embedded device, and the device is carried on a UAV platform. Image data is acquired through the camera module of the UAV, and is transmitted to the platform in real time. The platform extracts slope information from the image data, and transmits the information to the ground control terminal in real time, thereby solving the problems of slow speed and low accuracy in acquiring slope information during post-disaster rescue, and realizing real-time sensing of slope disasters in the post-disaster rescue area.

The invention discloses a low-dimensional material photoelectric detector based on a tunnel junction and a manufacturing method thereof. Comprising a metal electrode, a plasma waveguide structure, an insulating tunneling layer, a two-dimensional material conducting channel, an absorption layer, an input optical waveguide and an output optical waveguide, the metal electrode and the plasma waveguide structure adopt an I-like structure, a slit is formed in the middle of a strip-shaped structure in the middle of the I-like structure, and the slit is perpendicular to the direction of the strip-shaped structure; one end of the slit is provided with an input optical waveguide, and the other end is provided with an output optical waveguide; the outer surfaces of the metal electrode and the plasma waveguide structure are coated with an insulating tunneling layer, the input optical waveguide and the output optical waveguide are arranged at intervals with the insulating tunneling layer, a two-dimensional material conducting channel is arranged on the insulating tunneling layer, and an absorption layer is arranged on the middle part of the two-dimensional material conducting channel. The low-dimensional material photoelectric detector has the remarkable advantages of high gain, low dark current, high sensitivity, high response speed and the like, and is expected to be widely applied to various optical perception and photon measurement integrated circuits.

The invention relates to a pattern printing regulation and control method and system based on photochromic printing. The method comprises the following steps: performing multispectral space-time coding mapping on a target color pattern corresponding to a pattern printing task to obtain initial time sequence exposure sequence data; performing inverse problem optimization based on light-chemical kinetics on the initial time sequence exposure sequence data to obtain optimized time sequence exposure sequence data; according to the optimized time sequence exposure sequence data, performing multispectral structured light exposure perception analysis on a printing body corresponding to the pattern printing task to obtain actually measured color field analysis data; and according to the actually measured color field analysis data, closed-loop iterative optimization is carried out on the optimized time sequence exposure sequence data until the actual color error value meets a preset color error threshold value, and pattern printing control data is obtained. With the adoption of the method, the production throughput and yield can be effectively improved in the production process under comprehensive conditions so as to meet the production standard.

This invention discloses a digital multi-directional ambient light acquisition and control method and system based on the Internet of Things (IoT). Ambient light intensity data is simultaneously acquired by three sets of sensors in three directions. After Kalman filtering and normalization preprocessing, standardized light intensity data is obtained. This standardized data is input into a random forest recognition model, which, combined with a spectral feature library, acquisition time, and light intensity change rate, identifies the light quality of natural light or interfering light. Based on the judgment results, the natural light direction is selected, and dynamic fusion weights are assigned to each direction according to the time period of acquisition. Weighted fusion is then performed to obtain a fused light intensity value. A time-series sequence containing historical and current fused light intensity values ​​is input into an LSTM neural network model to predict future light intensity change trends and generate street light control commands. Finally, the commands are sent to the target controller to realize the switching on / off or brightness adjustment of the street lights. This invention significantly improves the comprehensiveness, anti-interference capability, and control foresight of ambient light perception.

The invention relates to the technical field of intelligent control, in particular to a device control method based on a light sensation module, an environment monitoring device and a storage medium, the device control method based on the light sensation module is applied to the environment monitoring device, and the environment monitoring device comprises an environment monitoring module, a light collection module and a processing module; the method comprises the following steps: receiving a brightness value of a surrounding environment collected by a light sensation module; judging whether the change of the brightness value in a preset time length meets a preset condition or not; and if the change of the brightness value in the preset duration meets the preset condition, the working state of the target equipment is controlled based on the environment data collected by the environment detection module. According to the technical scheme, the target device is controlled by sensing whether the change of the brightness value in the environment meets the preset condition or not through light, an existing switch control mechanism is replaced, control over the target device is more intelligent, switch assemblies are reduced, the attractiveness is improved, and meanwhile the cost is reduced.

The invention discloses a control method and device for an intelligent eye protection bookmark, and belongs to the technical field of intelligent stationery. The invention provides a dynamic compensation method for solving the technical problems that an existing eye protection bookmark is poor in distance measurement precision and high in false alarm rate under different environment illumination. According to the method, the distance from the book to the eyes of the user and the environment illumination intensity are synchronously detected in real time, and the corresponding distance adjustment value is selected to dynamically compensate the initial distance based on the preset threshold interval to which the illumination intensity belongs, so that the correction distance with higher precision is obtained. By comparing the corrected distance with a safety threshold value, a reminding operation is executed when the distance is too close. The environment light sensing and dynamic compensation algorithm is integrated on the bookmark carrier, so that the interference of environment light is effectively overcome, the full-scene high-precision distance monitoring is realized, and meanwhile, the interference on reading is reduced to the greatest extent while the bad reading posture is effectively corrected through a humanized graded reminding mechanism.

The application relates to a target detection method for efficient vehicle-vehicle cooperation, comprising the following steps: collecting point cloud data under the scene of the ego vehicle and the connected vehicle; based on the point cloud data, point column fusion and feature extraction are carried out to obtain a pseudo image of the point cloud data; based on the pseudo image of the point cloud data, multi-scale feature extraction and dimension reduction processing are carried out to obtain light perception features; based on the perception features, a feature confidence map is generated through deep supervision of feature labels, wherein the feature confidence map is updated with the change of the communication round; based on the feature confidence map, collaborative sharing features are selected, and feature fusion between vehicles is carried out in combination with the perception features to obtain fused perception features; and a pre-trained target detection model is used to carry out target detection on the fused perception features to obtain a target detection result. Compared with the prior art, the application has the advantages of improving the efficiency of the perception task.

The application discloses a kind of self-adaptive anti-light interference Micro-LED display systems for building facade, including display module, optical control layer, ambient light perception module and central controller.Display module has Micro-LED pixel array.Optical control layer includes microfluidic cavity unit aligned with each pixel, which encapsulates conductive and insulating liquid, forms variable optical interface, and changes curvature by voltage applied to its transparent electrode.Environmental light perception module real-time acquisition environmental light intensity and angular distribution.Central controller calculates the light beam control parameters of each pixel based on environmental light information and pre-stored viewing area coordinates, generates independent driving voltage, and controls the deformation of corresponding variable optical interface.Thus, the system synchronously realizes the convergence of pixel display light to the viewing area, and directs the environmental reflected light away from the viewing area, thereby significantly improving the contrast and visibility of the screen in outdoor complex light environment.

The application discloses a traffic light perception method and device based on automatic learning of historical frame memory, and belongs to the field of automatic driving. The method comprises the following steps: detecting a lamp group frame of each group of traffic lights in a current frame image in a real-time timing image; judging the state of each lamp group frame in the detected current frame image in real time to obtain state information of each lamp group frame in the current frame image; tracking each lamp group frame in the detected current frame image in real time to obtain a one-to-one correspondence relationship between each lamp group frame in different frame images, and then determining each same lamp group frame which is one-to-one corresponding between different frame images; and using the state information of each same lamp group frame in the preset number of historical frame images adjacent to the current frame image and the state information of the corresponding lamp group frame in the current frame image to perform real-time automatic learning to obtain the current timing state of each same lamp group frame. The application has real-time performance and high accuracy in the aspect of traffic light state perception.

The present application relates to the field of light supplement intelligent regulation, in particular to a lamp-microphone integrated cold and warm color temperature self-adaptive regulation method based on ambient light perception, comprising: a lamp-microphone integrated device suitable for integrating microphone, main control chip, light supplement component and light sensor. The original ambient light signal output by the light sensor is collected, data compensation correction is carried out by using multi-channel spectral response fusion, and the ambient color temperature value and the illumination intensity value are accurately analyzed by relying on the improved color temperature estimation algorithm. The ambient light parameters are input into the trained color temperature mapping model, the target light supplement color temperature parameters and the brightness parameters are solved, the cold and warm light pulse width modulation signal proportion and the signal duty cycle are calculated respectively, and the adaptive light supplement component driving control signal is generated. The driving signal is used to regulate the working state of the cold and warm white light emitting element, and the light source ratio and the luminous intensity are dynamically adjusted. The method optimizes the ambient light data correction and color temperature analysis capability, and realizes the full-automatic self-adaptive regulation of the light supplement color temperature and brightness.

The application relates to the technical field of display control, and discloses a COB display screen system and a control method for intelligent dimming, the COB display screen system for intelligent dimming comprises a light field sensor array module, which generates a light field distribution by collecting ambient light in real time; an super-pixel segmentation module, which extracts super-pixel features according to a display image and light field information; a model prediction controller module, which models based on the super-pixel features and generates an optimal brightness control signal; a reinforcement learning engine module, which dynamically optimizes feature generation and control parameters according to an operating state; and a distributed muLED driving circuit module, which drives a muLED light-emitting unit according to the control signal. The application realizes accurate perception of display ambient light and fine regional division of display content by introducing the light field sensor array module and the super-pixel segmentation module for ambient light perception, and improves the environmental adaptability and local contrast of the display screen under various illumination conditions.

The invention provides a rhythm lighting device, a control system, a control method and a construction method. The rhythm lighting device comprises a lamp mounting frame, a variable-angle lamp bin, a lamp cluster module, a secondary phase change heat storage material bin and a capillary network heat exchange assembly. The rhythm lighting control system comprises a plurality of rhythm lighting devices, an external light sensing and stepped dimming control module, a stepping rhythm lighting control module and a waste heat recycling management and control module. According to the rhythm lighting device, the first-stage phase change heat storage material bin and the second-stage phase change heat storage material bin are integrated, and through the heat storage and release process of phase change materials, the phase change materials are recycled and converted into a zero-carbon heat source which has an available grade and can be subjected to space-time transfer; according to the rhythm lighting control system and the control method, through preset rhythm lighting target parameters, the illuminance and the color temperature of a space are dynamically adjusted, and the change of natural light is simulated, so that the biological clock of a user is favorably adjusted, the psychological state and the sleep quality are improved, and the rhythm lighting control system and the control method are especially crucial to an underground space lacking natural light.

The invention provides an illumination perception lightweight defect detection method, system and equipment in a low-light environment, and belongs to the field of intelligent inspection and automatic defect identification. According to the method, an illumination perception lightweight YOLO framework is constructed, and the following operations are executed in sequence: obtaining a low-light environment image; low-light enhancement and lightweight feature extraction are realized on a feature level by using an illumination adaptive enhancement feature extraction network; performing multi-scale feature fusion through a hybrid path aggregation network; and outputting a detection result based on a dynamic space attention mechanism by adopting a dynamic feature fusion detection head. By adopting the illumination perception lightweight defect detection method, system and equipment in the low-light environment, the problems of poor image quality, large model calculation amount, small target leak detection and strong background interference in the low-light environment are solved, and the method, system and equipment have the advantages of high detection precision, few model parameters and high reasoning speed; the system is suitable for intelligent inspection of infrastructures such as sewers and pipe galleries.

The invention relates to an image processing method and device, electronic equipment, a storage medium and a program product. The method comprises the following steps: determining a histogram associated with an image to be processed; determining a target pixel value range to be adjusted in the histogram; based on a first cumulative distribution curve corresponding to the histogram, determining a target pixel value of which the slope is greater than a preset slope threshold value according to a pixel value decreasing direction, and based on the target pixel value, adjusting the number of pixels of each pixel value in the range of the target pixel value in the histogram to obtain an adjusted histogram; and determining a processed target image based on the adjusted histogram and the to-be-processed image. Through the method, the light sensation can be enhanced, and the contrast in the target image can be improved.

The application provides a backlight module operation method and system based on artificial intelligence, the method comprises the following steps: S1: acquiring the motion speed and angular speed data of the user's head, and predicting the head motion trend; S2: establishing a backlight brightness calculation model, taking the head motion trend as the input, and acquiring the theoretical value of the backlight module brightness; S3: based on the theoretical value of the backlight brightness, establishing a curve of the backlight brightness changing with time, and performing smoothing processing on the curve of the backlight brightness changing with time through smoothing filtering; S4: converting the curve of the backlight brightness changing with time after the smoothing processing into the control signal of the backlight module, and sending the control signal to the backlight driving circuit in real time, so as to realize the control of the backlight module. Through the fusion of head motion data prediction and ambient light perception, the dynamic backlight brightness calculation model is established, the 'brightness lag' problem caused by the fact that the traditional backlight control does not consider the head motion state of the user is solved, and the risk of motion sickness caused by the visual discomfort of the user is reduced.