99 results about "Light perception" patented technology

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 a light sensation self-adaption and white balance cooperative adjustment method and device for an LED display screen, and the method comprises the steps: collecting the illumination value of current ambient light and the spectral distribution of the ambient light, and calculating the color temperature value of the ambient light; according to the color temperature value, inquiring a pre-stored color temperature-gain parameter corresponding relation library to determine a corresponding white balance gain parameter; according to the illumination value, a backlight brightness adjustment amount is calculated through a pre-constructed logarithm compensation model; associating and binding the white balance gain parameter and the backlight brightness adjustment amount, and outputting the white balance gain parameter and the backlight brightness adjustment amount to a pulse width modulation signal generation unit and a digital-to-analog converter through a microcontroller; and outputting the white balance gain parameter to a digital-to-analog converter, outputting the backlight brightness adjustment amount to a pulse width modulation signal generation unit, generating a synchronous adjustment signal to drive an LED display unit, and carrying out cooperative adjustment of backlight brightness and white balance so as to achieve the purpose of unified regulation and control of visual comfort and color rendition authenticity.

The invention discloses a control method of a video monitoring system, which relates to the technical field of video monitoring, and comprises the following steps of: acquiring continuous image frames through the video monitoring system, extracting brightness channels, edge structures, direction gradients and contrast changes of images, constructing a reflective perception vector group, and calculating an included angle change trend by combining a target motion direction vector, determining whether a reflection offset condition consistent with the target direction appears in a picture in a camera attitude control process; after it is determined that the reflection offset condition consistent with the target direction appears in the picture, the inter-frame change tensor of the target area and the reflection area is extracted, and a time sequence track consistency matrix is constructed; according to the invention, the problem of wrong adjustment of the camera caused by misjudgment of light reflection in video monitoring is solved, attitude regulation and control based on image displacement abnormal mode recognition are realized, and the tracking stability and the monitoring accuracy are improved.

The invention provides an automatic driving test scene generation method based on real traffic data, and solves the problems of low accident data utilization rate, SIL / HIL test splitting and insufficient boundary coverage in the prior art. Comprising the following steps: acquiring multi-source heterogeneous traffic accident data; cleaning data by adopting a joint interpolation-anomaly detection mechanism; vehicle dynamic sudden change characteristics within 0.5 second before braking are extracted through LSTM and DTW algorithms; constructing a three-dimensional scene pipeline driven by a physical engine, and dynamically associating the pavement slippery coefficient with the rainfall intensity; analyzing the accident text into simulation parameters by using a semantic-physical parameter converter; performing SIL-HIL cooperative verification: performing extreme illumination perception test and narrow road planning verification in an SIL environment, and realizing 1ms step length fault injection test in an HIL environment; positioning failure parameters based on Bayesian optimization; a GAN is adopted to generate a long-tail scene, and a test boundary is expanded by coupling extreme conditions such as rainstorm / low visibility; and outputting a standard scene library containing the collision probability thermodynamic diagram. The safety verification efficiency under the extreme working condition is remarkably improved.

The invention relates to the technical field of large-scale structure measurement, and discloses a robot laser vision three-dimensional scanning measurement system for a large-scale structural member. 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, and the motion control module combines the data with three-dimensional model data of the large-scale structural member to be measured to generate a multi-view dynamic scanning path instruction. The robot motion platform executes an instruction to drive the laser vision sensing module to move, the module projects laser stripes to the surface of a to-be-measured structural member and synchronously collects an image, the point cloud processing module performs adaptive filtering processing on the image and then generates three-dimensional point cloud data, and the requirement for efficient and accurate measurement of a large structural member in a complex industrial environment can be met.

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 liquid crystal display brightness adjusting system and method based on ambient light perception, and the system comprises a high-precision ambient light sensor which obtains the ambient light illuminance and color temperature data in real time; the analog-to-digital converter is used for converting the analog optical signal into a digital signal; an embedded microcontroller; the temperature sensor is tightly attached to the liquid crystal panel backlight unit; and the control input end of the liquid crystal driving chip is connected with the driving signal output end of the embedded microcontroller through a serial peripheral interface bus. The technical normal form of a liquid crystal display dimming system is fundamentally reconstructed: in a physical layer, photoelectric signals and human eye spectral response offset are corrected through a spectral separation mechanism, a carrier recombination effect is inhibited based on a thermodynamic equation, and the physical authenticity of brightness output is ensured; in a control layer, a motion state compensation model and a spatial topology perception algorithm are constructed, and brightness space-time consistency control in a dynamic scene is realized.

The invention discloses an HDR image reconstruction method based on progressive feature alignment and quality guide fusion, and the method comprises the steps: inputting a to-be-processed LDR image sequence into a trained progressive quality guide image reconstruction model, and obtaining an image reconstruction result; according to the model, after an input LDR image sequence is linearized, a progressive variable feature alignment module aligns non-reference frame features through a multi-scale pyramid and cascade deformable convolution, and multi-scale features are output through exposure perception modulation; the quality guide motion compensation module iteratively optimizes an optical flow field and a confidence coefficient mask through a cascade optical flow quality refining structure block; and the structure maintenance fusion module aligns the HDR sequence by using the optical flow field, performs dynamic weighted fusion in combination with a confidence mask, and finally enhances details through a Laplace attention mechanism and outputs a ghosting-free HDR image. According to the method, through progressive alignment and fusion of quality perception, the balance problem of ghosting and detail loss in dynamic HDR imaging is solved.

The invention provides an automobile atmosphere lamp illumination uniformity detection method and system, detection points of a simulated automobile cabin are determined, detection parameters of the detection points are set, and simulated human eye light sensation visual detection in the automobile cabin is realized by setting the detection points; by means of illumination detection data of all detection points on atmosphere light, global illumination distribution of a vehicle cabin is constructed, a non-uniform illumination area in the global illumination distribution is determined, and non-uniform illumination space distribution formed under the current atmosphere light illumination condition is accurately positioned; a target atmosphere lamp suitable for eliminating the non-uniform illumination area is determined in combination with the spatial relationship between the non-uniform illumination area and the atmosphere lamp layout, illumination change information of the target atmosphere lamp is determined, it is ensured that global atmosphere lamp uniformity illumination detection is implemented for the specific cabin environment in the design stage, and by changing the light emitting illumination state of the atmosphere lamp, the uniformity of the atmosphere lamp is improved. The overall lighting quality of the cabin is improved.

The invention discloses a fine-grained feature matching vehicle re-identification method for a license plate shielding scene, and the method comprises a vehicle detection stage based on illumination perception and adaptive prediction, and a fine-grained Transform feature matching stage based on implicit semantic prototype perception. Comprising an illumination sensing module and an adaptive prediction module. The illumination sensing module is used for realizing image adaptive enhancement under different illumination conditions; the adaptive prediction module suppresses a redundant prediction frame through a self-attention weight mechanism; in the fine-grained Transform feature matching stage based on implicit semantic prototype perception, an implicit semantic prototype learning module and a fine-grained Transform matching module are included; the implicit semantic prototype learning module unsupervised decouples vehicle structural components through a group of learnable semantic prototypes to generate a soft semantic distribution diagram; and the fine-grained Transform matching module is used for introducing semantic affinity bias in cross attention. According to the method, the accuracy and stability of vehicle detection and identity matching in a complex environment can be improved.

The invention discloses a lighting system for industrial robot navigation, a control unit and a method, and relates to the field of intelligent robots. The problems that a traditional robot is single in illumination, insufficient in environment perception and low in data interaction and processing efficiency are solved. The system comprises an intelligent lighting module, an ambient light detection module, a positioning module, a data processing module, a navigation control module and a central control module. According to the system, through linkage of multi-thread data processing, dynamic path planning and an intelligent lighting strategy, closed-loop control of ambient light perception-navigation planning-lighting adjustment is realized; through cooperation of multiple modules, deep fusion of intelligent illumination and precise navigation is realized, and the environmental adaptability and operation reliability of the robot in a complex environment are remarkably 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 invention relates to the technical field of image processing, discloses an image display method and device of a display screen, a vehicle, a medium and a program product, and realizes multi-dimensional light perception of a complex environment by acquiring environment data of an environment where the display screen is located and multi-dimensional light data in multiple different directions and / or different types. And performing comprehensive analysis based on the environment data and the multi-dimensional light data, determining an image display parameter corresponding to at least one object type in the to-be-displayed image, and further performing partition adjustment on the to-be-displayed image to obtain a target display image. Therefore, the display screen is prevented from being too bright or too dark, the display effect of the objects associated with different object types in the target display image can be matched with the actual visual demand of a driver, and the driving safety and the user experience are improved.

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 present invention relates to the field of image correction and proposes an image correction method, device, system, and storage medium. The method involves synchronously capturing a color image and three-dimensional point cloud data of a target object using an RGB-D sensor, constructing an elastic mesh model (including stiffness attributes), and achieving high-precision surface unfolding based on finite element analysis to generate a geometrically corrected image. Multispectral shadow separation and generative adversarial network (GAN) inpainting techniques are combined to eliminate occluded shadows and generate textures with consistent illumination. Finally, global illumination uniformity is optimized through dynamic compensation based on ambient light perception. This technical solution aims to reduce errors in unfolding correction of non-planar objects, efficiently distinguish between real content and shadow areas, adapt to dynamic ambient light changes in real time, and improve the ability to generate complex textures.

The invention provides an unsupervised thermal imaging video enhancement method based on an event-assisted traffic sign sketch. According to the method, the characteristics of low light perception but texture missing of an infrared camera and low light, high dynamic, noise and incompleteness of event signals are fully combined, a dual lifting mechanism of an infrared frame and the event signals is provided for the traffic semantic reconstruction problem in the driving environment, and high-quality traffic sign sketch drawing without supervision is achieved. According to the method, accurate motion estimation is provided by utilizing infrared signals to serve as a time reference for aligning event signals so as to align incomplete event signals. Event signals are utilized to provide texture details which are usually not perceived by an infrared camera, and event consistency correction is introduced to improve the continuous perception effect between adjacent frames. According to the unsupervised thermal imaging video enhancement method provided by the invention, the applicability of the infrared camera in a low-light traffic environment is improved, and the improvement of the visual task performance in the middle and downstream of automatic driving is facilitated.

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 a two-dimensional indium selenide optical sensor with a motion trail recognition function and a preparation method thereof. The light sensor device comprises a SiO2 / Si substrate, a gamma-InSe semiconductor light absorption layer located on the substrate and asymmetric Au electrode structures arranged at the two ends of the light absorption layer. A gamma-InSe semiconductor material with a non-centrosymmetric structure is selected, and an asymmetric electrode configuration design is combined, so that the device generates a photo-pyroelectric effect and a photo-thermoelectric effect under the condition of temperature change caused by illumination, and remarkable positive and negative pyroelectric response peak current is formed in a zero-bias self-driven mode. The device can directly analyze and reconstruct the motion trail of an object according to the dynamic behavior of the reverse attenuation current after light removal, does not need to depend on an external calculation unit, and achieves the function of integrating light perception, information storage and motion trail calculation in a single device.

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 discloses a non-uniform illumination underwater image enhancement method, and belongs to the technical field of image processing. The method mainly comprises the following steps: constructing an illumination-perceived non-uniform illumination underwater image enhancement network, wherein the illumination-perceived non-uniform illumination underwater image enhancement network comprises a trunk enhancement network for outputting a sharp image and an illumination attention map estimation branch network for outputting an expected illumination attention map; training the illumination perceived non-uniform illumination underwater image enhancement network based on the non-uniform illumination underwater image data set; and obtaining a to-be-processed non-uniform illumination underwater image, inputting the to-be-processed non-uniform illumination underwater image into the trained illumination perception non-uniform illumination underwater image enhancement network, and outputting a clear underwater image through the decoder module. According to the method, the detail information of the non-uniform illumination underwater image can be effectively enhanced, the brightness information and the color information are adjusted, and the quality of the underwater image is remarkably improved.

The invention belongs to the technical field of intelligent automobile lighting, and particularly relates to a dynamic glare suppression method and system based on multi-automobile cooperative perception, a vehicle and a computer readable storage medium. According to the method, a glare sensitivity distribution diagram which is sent by an opposite vehicle and based on the visual angle of the vehicle is received through V2X vehicle wireless communication, vehicle-vehicle information sharing is achieved, and the sensing limitation of a single vehicle is broken through; constructing a human eye glare sensitivity model based on the CIE standard, converting the physical brightness into subjective glare perception to generate a smooth weight map, and performing curve and ramp dynamic geometric compensation on the map to eliminate perspective distortion; and finally, generating a pixel-level dimming instruction by using the multi-agent depth deterministic strategy gradient network in combination with the lighting requirement of the vehicle, and driving the pixelated headlight to execute accurate brightness adjustment. According to the method, the problems of multi-vehicle meeting game conflicts, rough control strategies and failure of complex road conditions are effectively solved, and collaborative and accurate glare suppression and remarkable improvement of subjective comfort are achieved.

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.

The invention discloses a VR display parameter adaptive setting method based on ambient light perception, and particularly relates to the technical field of virtual reality display control, electrical and optical calibration of an ambient light sensor is completed under a unified time base and a fixed step length, and physical quantities such as illumination intensity and related color temperature after unit conversion and noise suppression are obtained; environment and content features are synchronously extracted in the sliding window, time sequence alignment is carried out, and an environment / content double-baseline and hardware reachable domain model is established; executing priority arbitration according to a threshold value and a shortest residence criterion, linking brightness, white points, gamma and black bits in a reachable domain, and planning smooth transition of an asymmetric rate; a closed loop set in a display pipeline is grounded through binocular consistency control and read-back check of frame synchronization, and user preference superposition and evidence filing are supported.

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 discloses an automatic driving traffic light perception method and device based on high-precision map matching, and belongs to the field of automatic driving. The method comprises the following steps: obtaining 3D position information of each lamp group frame and indication direction information of each lamp group frame from a high-precision map according to a current frame identification image; projecting the 3D position information of each lamp group frame into the current frame identification image to obtain each envelope frame corresponding to each lamp group frame; matching each envelope frame with each lamp group frame identification frame in the current frame identification image; determining the type of each lamp group frame by using the corresponding indication direction information of the lamp group frame for each pair of envelope frame and lamp group frame identification frame that is matched successfully; and obtaining the time sequence state of the same lamp group frame of the type according to the type of the lamp group frame and the time sequence state of each same lamp group frame. The application has real-time performance and high accuracy in the state perception of traffic lights.

The invention relates to the technical field of display, and discloses a display screen color management method based on ambient light perception, and the method comprises the steps: collecting original illumination data containing incident angle data and sensor space coordinates, and calculating the initial position of a light source; determining light field azimuth information in combination with the equipment attitude data; constructing a three-dimensional light field model based on light direction features and intensity distribution features of the light field azimuth information; comparing the current light field distribution with the standard light field distribution, and generating a display parameter adjustment set containing color temperature, brightness and contrast; the display parameter adjustment set is converted into control instruction data, and dynamic adaptation processing of the screen display effect is completed. The problem that picture display of the display screen is distorted or unnatural under the influence of ambient light is solved, and the effects of adjusting the display effect of the display screen according to the ambient light and improving the display quality are achieved.