2333 results about "Frame rate" patented technology

The invention relates to the technical field of traffic management, in particular to a video monitoring traffic intelligent optimization system which comprises a time sequence fragment evaluation module, a path priority adjustment module, a traffic scheduling optimization module and a buffer strategy adaptation module. According to the invention, the transmission efficiency and quality of the video monitoring data are improved by analyzing the video stream in real time and adjusting the frame rate and the compression rate, the importance of each time sequence segment in the video stream is evaluated, the frame rate is adjusted according to the importance, more resources are ensured to be obtained by important events, unnecessary data transmission is reduced, network congestion is effectively reduced, and the transmission efficiency of the video monitoring data is improved. The network transmission path is monitored in real time, and the data transmission proportion is adjusted, so that the video stream passes through the network path with higher quality more preferentially, the stability and speed of video transmission are enhanced, the priority and bandwidth allocation are dynamically adjusted, and the video stream with high priority is protected to ensure that the video quality of a key monitoring area is not influenced by network fluctuation.

The invention discloses an improved YOLOv11-based high-reflection and high-transmittance material surface defect detection method, which comprises the following steps: S1, acquiring a mobile phone screen surface defect image, preprocessing and labeling, and generating a training data set containing three defects of scratches, edge breakage and cracks; s2, constructing a defect detection model; s3, averagely dividing an input image into four independent detection regions, adopting a bounding box overlapping area weight distribution strategy for cross-region defects, and performing partition counting on the image by using a defect detection model; s4, constructing a surface defect detection network meeting the real-time requirement of the industrial production line, and outputting a detection result and a processing frame rate; s5, pixel-level mask segmentation is carried out on the scratch defect, and contour coordinates and geometric features are extracted; and S6, fitting the actual damage size of the scratch defect on the surface of the high-reflection and high-transmittance material according to the segmentation result. According to the method, the detection speed is high under the condition that the accuracy is ensured, and a reliable solution is provided for surface flaw detection of the high-reflection and high-transmittance material.

The invention provides a game cartoon character display method based on a virtual reality technology. The method comprises the following steps: acquiring three-dimensional model data of a game cartoon character in a target display area through a user interaction terminal; the virtual reality content management platform determines a dynamic rendering precision level according to the model data, and generates a real-time rendering strategy including a model patch reduction coefficient, a texture compression rate and a skeleton animation updating frequency in combination with terminal performance parameters; the strategy is sent to a virtual reality supervision platform and a user interaction terminal, and a virtual reality rendering engine platform is instructed to execute real-time rendering; and the virtual reality supervision platform monitors the frame rate fluctuation data of the head-mounted display device, calculates the scene rendering stability, sends a rendering optimization instruction if the scene rendering stability is lower than a threshold value, and adjusts the model data acquisition frequency and the video memory cleaning period to optimize the performance. The rendering efficiency and the system stability can be improved, and the hardware load and the frame rate fluctuation are reduced.

Systems and methods are described for video coding using generalized bi-prediction. In an exemplary embodiment, to code a current block of a video in a bitstream, a first reference block is selected from a first reference picture and a second reference block is selected from a second reference picture. Each reference block is associated with a weight, where the weight may be an arbitrary weight ranging, e.g., between 0 and 1. The current block is predicted using a weighted sum of the reference blocks. The weights may be selected from among a plurality of candidate weights. Candidate weights may be signaled in the bitstream or may be derived implicitly based on a template. Candidate weights may be pruned to avoid out-of-range or substantially duplicate candidate weights. Generalized bi-prediction may additionally be used in frame rate up conversion.

The invention discloses a global ultra-precision strain measurement method, and relates to the technical field of strain measurement. The method comprises the following steps: continuously shooting moving images of a target area by using a high-frame-rate high-definition camera, and recording accurate time; and carrying out image correction, feature extraction and tracking and data normalization. And after Gaussian white noise is added, singular value decomposition and reconstruction are carried out. And a Lucas-Kanade optical flow method is adopted to calculate the displacement of the feature points in the reconstruction matrix. And a displacement smoothing stage: smoothing the displacement data by using an LOESS method. And carrying out global strain calculation by adopting a window sliding method, and calculating the strain through the spatial derivative of the displacement field. According to the method, the quantization effect can be relieved, the continuity of displacement calculation is improved, low-energy noise and irrelevant features are removed, main motion information is reserved, meanwhile, smoothness is enhanced, local features are captured in a high-precision mode, and measurement sensitivity is improved. The method is suitable for strain measurement of large-scale structures such as bridges and buildings.

The invention discloses an intelligent track foreign matter detection system and method based on image recognition, and particularly relates to the technical field of image recognition. A real-time image is acquired, an area-of-interest is extracted in combination with an image segmentation algorithm, and potential foreign matters are identified; the space-time consistency of the detection result is verified by analyzing the space-time data of the track foreign matter so as to judge the real threat; extracting multi-dimensional features such as shape, texture, color and size from a real threat target, and outputting classification confidence to evaluate model classification stability; the detection accuracy is evaluated by combining the space-time consistency and the classification stability, the detection results are divided into different categories, the abnormal degree of subsequent detection is predicted for the incomplete accuracy detection result, and the image acquisition resolution or frame rate is dynamically adjusted to improve the detection definition. The problems of missing detection and frequent false alarm of small and medium-sized foreign matters in the prior art are solved, the accuracy and reliability of track foreign matter detection are greatly improved, and the running safety of a high-speed train is guaranteed.

The invention discloses a container application on-screen method based on texture full-process optimization, which comprises the following steps: taking a swan-gap system as a host and an Android system as a container, distributing a plurality of first buffers by the host, screening out a first texture format by the container, writing original textures of the format generated by rendering into frame buffers, identifying a dirty area of the rendered textures, and displaying the original textures in the frame buffers; packaging the texture data of the region, storing the packaged texture data into a shared memory, transmitting a file descriptor FD to a host, binding an idle first buffer setting priority, a state, a generation timestamp and a texture data pointer at the same time, and obtaining the texture data by the host through the FD; the host establishes a fixed thread task pool, executes multiple tasks in parallel to obtain on-screen texture data, and then updates the state of the first buffer and a texture data pointer; and finally, the host queries the first buffer with the processed state, reads the texture data after sorting according to the priorities and the generation timestamps to finish on-screen, and resets the state of the first buffer to be idle, so that the on-screen delay is effectively reduced, and the actual frame rate of the Android application is improved.

The invention relates to an image frame insertion method and device in virtual shooting and a storage medium. The method comprises the following steps: acquiring at least two frames of reference images generated by a rendering engine; obtaining motion information and depth information of at least two frames of reference images generated by a rendering engine; and based on the motion information and the depth information of the at least two frames of reference images, determining a pixel value of a frame insertion image between the at least two frames of reference images, the frame insertion image and the at least two frames of reference images being used for sending to a display screen for display, and the display screen serving as a shooting background in virtual shooting. According to the embodiment of the invention, on-screen content can be smoothly played without improving the performance of a rendering end, the picture quality of a picture is remarkably improved, the data output capability of a rendering engine is fully played, redundant calculation is avoided, the computing power is saved, the remarkable frame rate improvement can be realized at relatively low cost, and the user experience is improved. The method meets the requirements of a virtual shooting scene, and has good stability and robustness.

The invention discloses a non-contact heart rate detection method, system and device based on visual Transform and multi-scale feature aggregation and a medium. The method comprises the steps that a face visible light video is obtained, the unified video frame rate is re-sampled through the frame rate, face key point positioning and region division are carried out on each frame of image, and a face visible light video sequence is obtained; performing time migration operation on the video sequence to obtain a difference frame sequence, performing channel fusion on the video sequence and a difference frame, and performing down-sampling on a spatial dimension to obtain a low-resolution feature tensor; constructing a non-contact heart rate extraction model, inputting the low-resolution feature tensor into the non-contact heart rate extraction model, and outputting a heart rate value of the target; the non-contact heart rate extraction model comprises a feature enhancement module, a multi-scale mask feature aggregation module, a Transform time sequence modeling module and an rPPG predictor, the system, the device and the medium are used for achieving the non-contact heart rate detection method based on visual Transform and multi-scale feature aggregation, and the precision of rPPG signal extraction is improved.

The invention relates to the technical field of digital fusion, in particular to an electronic chart drawing method and system based on a data fusion technology, and the method comprises the steps: S10, building and dynamically updating a mixed index structure based on a preset electronic chart database and an incremental data packet collected in real time; s20, matching the same-name elements, fusing the identified space overlapping regions, and outputting a de-duplicated global sea chart data set; s30, dividing a plurality of sub-regions, constructing a quadtree-R tree index, and outputting a quadtree-R tree double-layer mixed index structure; s40, converting the screen coordinates into geographic coordinates, screening visible elements, and outputting a visible region element set; and S50, based on the visible area element set and a preset style rule, allocating a rendering task, optimizing and matching a GPU instruction set, and outputting a real-time sea chart picture with a preset frame rate. According to the method, the real-time processing efficiency and the visualization fluency of the electronic chart are remarkably improved, and the user interaction experience is optimized.

The invention discloses a visual precise plastic mold surface milling system and method, and the method comprises the steps: obtaining and analyzing the surface topography data of a milling region and a tool displacement track in real time through an optical sensor, and extracting wear-related micro-deformation features through multi-band filtering processing; generating a deviation vector matrix through three-dimensional mapping of the deviation vector matrix and a reference curved surface, and realizing dynamic calculation and path correction of the cutter offset; the high efficiency and stability of the compensation cutting process are ensured by combining the self-adaptive adjustment of the rotating speed and the feeding rate of the main shaft; meanwhile, the compensation effect is projected to a visual interface in real time to form a comparison layer, hardware acceleration is started to maintain the system response speed when the frame rate fluctuates, and finally the material removal volume is evaluated according to the deviation vector matrix to intelligently control the machining cycle termination time. Therefore, the problem of microtopography deviation caused by tool abrasion in the milling process of the complex curved surface mold is effectively solved, and the machining precision and efficiency as well as the robustness and the automation level of the system are remarkably improved.

The invention discloses a hierarchical traffic prediction-based multi-terminal video display adaptive method, which comprises the following steps of: acquiring network traffic, user behaviors and equipment state information in real time by constructing a multi-dimensional feature acquisition module, and generating a dynamic feature matrix containing traffic, interaction and performance features; processing the feature matrix by using a deep learning model, and generating and dynamically adjusting a network traffic grading prediction result; formulating an optimized video content distribution strategy based on a prediction result and equipment performance parameters, and coordinating multi-terminal resource distribution; through user behavior analysis and network state monitoring, a self-adaptive video display control strategy is generated, dynamic adaptation of video resolution, frame rate and playing logic is realized, a full-link collaborative optimization module is constructed, terminal, network and application layer resource allocation is coordinated, a video transmission and display strategy is optimized, and network flow prediction and multi-terminal interaction requirements are combined to realize multi-terminal interaction. And generating a dynamic video layout and content switching strategy.

The invention discloses a sports motion recognition method based on 3D space-time attention and a slowfast network, and the method comprises the steps: obtaining an original human body motion video, sampling the original human body motion video through different frame rates, generating Slow branch and Fast branch input images, and taking the Slow branch and Fast branch input images as training samples; constructing a dual-branch network based on spatio-temporal feature extraction; designing a loss function, and training the dual-branch network based on spatial-temporal feature extraction by using the training sample; and sampling a to-be-identified human body behavior video through different frame rates to obtain corresponding video frame images, and inputting the video frame images into the trained dual-branch network based on spatial-temporal feature extraction to obtain an identified human body behavior category. According to the sports action recognition method based on the 3D space-time attention and slowfast network, the problems that in the prior art, the locality of the dependency relationship between the features in the space-time dimension is captured, and the model complexity is high are solved.

The invention relates to the technical field of ruin three-dimensional construction, in particular to a ruin three-dimensional model construction method fusing SLAM point cloud and image features, which comprises the following steps: acquiring a depth image and RGB data, aligning and eliminating inconsistent data according to a timestamp, calculating a frame rate to node ratio, establishing a binding relationship between an image and a point cloud, and extracting three-dimensional coordinate points. Recognizing and classifying geometric structures, evaluating texture and edge response, adjusting resolution, analyzing static and dynamic structures, eliminating dynamic interference, calculating geometric curvature and fitting error, optimizing three-dimensional model display, and obtaining detail reduction degree scores. According to the method, through accurate synchronization of the point cloud data and the RGB image, strict verification of timestamp matching and data consistency is allowed, data errors and noise are significantly reduced, the accuracy and reliability of the model are ensured, structural elements are identified, dense areas of geometric structures are refined and analyzed, richer data level support is provided, and the method is suitable for large-scale popularization and application. And higher-quality data is provided for archaeological research.

The invention relates to a video frame data segmentation right confirmation and dynamic transaction method and system based on a block chain. The method comprises the following steps: segmenting video stream data according to a preset frame rate to generate independent frame images, and carrying out anti-collision hash calculation on the independent frame images to generate a unique identifier; generating a comprehensive value score through a multi-modal analysis model in combination with the independent frame image and the corresponding script text data; generating NFT assets anchored to the block chain according to the comprehensive value score and the unique identifier; and dynamically adjusting the income distribution proportion of the NFT assets through the smart contract based on the user film watching data. According to the method, uniqueness right confirmation of frame data is realized through precise segmentation and anti-collision hash coding, value evaluation is performed by using a multi-modal analysis model, and capitalization and on-chain right confirmation are completed by means of a block chain technology. In addition, the income distribution proportion is dynamically adjusted in combination with the smart contract, efficient transaction and right distribution of the video frame data are realized, and the commercial value and transaction efficiency of the video data are improved.

The invention discloses a video stream adaptive low-delay real-time transmission method and system based on edge calculation. The method comprises the following steps: receiving a real-time video stream from a network camera, creating a pipeline queue, adding timestamp information for each video frame, and setting a queue protection mechanism; the coded video frames are taken out from the input queue, and the frames in the video are processed through hardware acceleration decoding; the resource use condition of the system is monitored in real time; executing a self-adaptive frame skipping decision according to a performance monitoring result; timestamp generation: dynamically calculating a timestamp interval according to an actual processing frame rate; receiving the decoded original video frame and the corresponding timestamp information, accelerating decoding by using hardware, and executing a video coding operation; and packaging and transmitting the coded video data, and providing a standard protocol interface to be connected with a client for playing. According to the scheme, stable low delay and relatively low resource occupation can be kept, and meanwhile, the video quality is remarkably improved.

The invention relates to the technical field of data processing, and discloses an automatic visual large-screen display processing method based on a control model and data driving, which comprises the following steps: optimizing large-screen information display, and switching parameters through layout density, visual attention and scenes; dynamically adjusting a data display strategy, and calculating data freshness, abnormal fluctuation and correlation parameters; user interaction experience is improved, and hot area response and multi-dimensional drilling parameters are optimized; enhancing information readability, and calculating graphic cognition and color conflict parameters; the system performance is stabilized, and the rendering frame rate and the data throughput are monitored; the business value, the attention decision response and the abnormity discovery timeliness are measured; dynamic weight, abnormal fusing, self-learning and multi-dimensional evaluation systems are adopted in intelligent optimization. According to the method, dynamic weight distribution, an abnormal fusing mechanism, self-learning optimization and a multi-dimensional evaluation system are combined, an intelligent, real-time and precise large-screen display system is achieved, and information display reasonability, interaction experience and system stability are improved.

The invention discloses a three-dimensional model lightweight reconstruction and rendering method based on multi-strategy collaboration, and the method comprises the steps: 1, extracting geometric information, appearance information and semantic attribute information of a three-dimensional model, separating the geometric information from the appearance information and the semantic attribute information, and storing the semantic attribute information to a three-dimensional model database; 2, instantiating components with the same geometric structure in the three-dimensional model, realizing material sharing through a material reference mechanism, and reducing rendering overhead on the premise of not changing the structure of the model; step 3, carrying out lightweight processing on the exported geometric and appearance information to obtain reconstructed lightweight models with different precision grades; and 4, dynamically adjusting the geometric complexity of the lightweight model through the sight distance and the frame rate by using a hierarchical calculation algorithm for rendering, and meanwhile, obtaining component semantic attribute information and synthesizing the semantic attribute information by calling a three-dimensional model database interface to realize visual display of the reconstruction model.

The present invention relates to the field of video image processing technology, and specifically discloses a video image quality diagnosis and analysis detection system and detection method. By extracting images from an input video stream frame by frame and performing preprocessing, the key feature areas in the image are identified based on edge detection and color segmentation algorithms, and consistency features, frame rate stability features, and spatial distribution density features are extracted. By calculating and analyzing these features, a consistency feature index, a frame rate stability feature index, and a spatial distribution density feature index are generated. Finally, the image quality score of each key feature area is obtained by comprehensive processing. Through this process, the quality change of the video image can be accurately evaluated to ensure that it meets the preset quality standards. The present invention also has an adaptive adjustment capability, and can dynamically adjust the parameters of image quality detection according to real-time monitoring results, such as optimizing the frame rate calculation threshold and improving the feature extraction accuracy.

The invention discloses a reasoning resource allocation optimization method and system for multi-camera real-time video monitoring, and relates to the field of multi-camera real-time monitoring. According to the invention, through reasonable reasoning of resource allocation and combination of a video frame rate dynamic adjustment strategy, optimization processing of video streams of a plurality of cameras is realized. Particularly, in the method, different reasoning resources are allocated according to the priorities of the detection tasks of different cameras, so that the cameras with abnormal event detection requirements obtain more computing resources, and the cameras without abnormal events use fewer resources, thereby achieving the balance between the optimal performance and the computing resources.

The invention discloses a webpage 3D rendering and control method, which comprises the following steps: step 1, asynchronous resource loading and scene initialization: carrying out network-aware asynchronous resource loading by adopting an intelligent prediction driven block loading technology, optimizing memory occupation through a self-adaptive space block and LRU cache strategy, and carrying out scene initialization; meanwhile, constructing a hierarchical scene tree to manage object transformation and a bounding box; and step 2, dynamic rendering pipeline execution: deploying a hierarchical visual degradation engine, dynamically switching multiple effects of soft shadow / PCF hard shadow, SSR precision and I BL sampling based on a five-level frame rate threshold, combining a PBR material adaptive rendering and motion perception LOD system, performing seamless detail level switching through normal reservation simplification, GPU-driven Morph transition and an asynchronous pre-calculation assembly line, and performing dynamic rendering on a dynamic rendering pipeline. The rendering optimization coordinator integrates the multi-dimensional parameters to generate a degradation instruction, and visual consistency is maintained; and step 3, user interaction and control feedback.

The invention provides an intelligent video sound box regulation and control system based on AI. The intelligent video sound box regulation and control system comprises a video data processing module, a user behavior analysis module, an environment perception module, a computing power scheduling module, a parameter optimization module, a real-time interaction module and a data storage module. The video data processing module analyzes the video stream and extracts multi-dimensional features; the user behavior analysis module generates behavior tags by analyzing user actions and voice instructions; the environment sensing module collects environment light intensity, space size and sound field parameters; the computing power scheduling module dynamically allocates GPU and TPU computing power resources; the parameter optimization module generates sound box regulation and control parameters based on the user behavior label and the environment parameters; the real-time interaction module adjusts the volume, the frequency response and the video playing frame rate of the sound box according to the regulation and control parameters; and the data storage module synchronizes video streams and regulation and control parameter historical data through distributed storage nodes. The system operation efficiency and the resource utilization rate can be improved.

The invention provides an intelligent identification and real-time alarm system for video monitoring. The intelligent identification and real-time alarm system comprises a video sensor, a real-time preprocessing module, a deep learning module, a risk assessment module and an early warning module, the video sensor collects video information in an environment and sends the video information to the real-time preprocessing module, and the video sensor adopts one of a network camera IPC, an analog camera AVC and an NVR video processor; the real-time preprocessing module preprocesses the video data, the preprocessing comprises clipping, size adjustment, enhancement and denoising, standard video image formation, resolution and frame rate unification and video noise reduction, and the standard video image obtained after preprocessing is sent to the deep learning module; and the deep learning module performs target identification, target detection and abnormal behavior detection on the standard video image through a deep learning model, and analyzes the video according to the output detection target and the detection abnormal result.

The invention discloses a video stream concurrent access front-end dynamic scheduling control system and method based on a digital twinborn scene, and relates to the technical field of computer software and network communication, the system comprises three core modules: a self-adaptive request queue module manages UE rendering resources based on a session token pool, distributes tokens through preemptive scheduling, and sends the tokens to a server; in combination with a GPU frame rate feedback dynamic adjustment strategy, queuing through a Promise asynchronous queue when the request fails; the front-end fusing and backoff retry module monitors the connection failure rate, when the connection failure rate reaches a threshold value, fusing is triggered, retry is delayed by adopting an exponential backoff strategy, and a semi-open state tends to recover; and the local cache collaboration module intercepts the request through Service Worker, caches the latest video clip, pushes the local content when the request is delayed, and ensures the freshness through ETag verification. The method and the device are used for efficiently managing loading and interaction of multiple users on real-time rendering pictures at a browser end.

The invention discloses an excavation part surrounding rock image-based blasting parameter real-time adjustment technology, which comprises the following working steps of: S1, equipment selection and arrangement: selecting photographic equipment with a frame rate of 100,000 frames per second and a resolution ratio of 4K or more, arranging a plurality of cameras to shoot a blasting process from different angles, and then configuring strong lighting equipment, and a strain sensor, a vibration sensor, a pressure sensor and a sonic sensor are installed, and blasting data are collected in real time. By improving the performance of the high-speed photographic equipment and applying technical means such as a three-dimensional reconstruction technology, a real-time feedback control system, AI auxiliary analysis, sensor fusion, numerical simulation, unmanned operation and the like, the precision and efficiency of researching the expansion rule of the blasting crack can be further improved. According to the improved technology, more accurate and dynamic support is provided for blasting design, blasting damage control is optimized, and the safety and efficiency of engineering application are improved.

The embodiment of the invention discloses a safety monitoring method and system for building construction, and the method comprises the steps: collecting the original video data of a construction site, carrying out the denoising, illumination correction and frame rate adjustment, and outputting a standardized video data stream; extracting attitude features of the constructors and representing the attitude features as a feature matrix to form an attitude feature matrix set containing spatio-temporal information; the sensitivity and correlation of the feature matrix are analyzed, calibration noise is added after dimension reduction, and feature data conforming to differential privacy are generated; and extracting data advanced representation by utilizing a pre-training model, and completing behavior classification, dangerous area judgment and safety violation detection. And the violation risk is evaluated in combination with the risk level of the construction area, graded early warning is generated, and meanwhile violation information is recorded to form a traceable management mechanism. According to the embodiment of the invention, accurate and efficient safety violation behavior detection is realized, and intelligent technical support is provided for safety management of building construction.

A method performed by a user equipment (UE) includes: receiving, from an access network node, information for indicating a start offset of an on-duration period of a discontinuous reception (DRX) cycle relative to a specific system frame number (SFN), and non-integer number of milliseconds of the on-duration period of the DRX cycle, the non-integer number of milliseconds corresponding to a video frame rate; and configuring the on-duration period of the DRX cycle based on the information.

The invention provides a visual fatigue relieving method based on ambient light self-adaption and an AI algorithm, and relates to the technical field of visual health protection. The visual fatigue relieving method based on ambient light self-adaption and the AI algorithm comprises the following specific steps: S1, data acquisition: acquiring a user eye image sequence in real time through a high-frame-rate camera; and S2, parameter extraction: when the user uses the eye for the first time, testing the eyes by combining the adjustable light source with ambient light. Multi-dimensional features (such as eyeball movement, blinking mode, pupil function and the like) of eyes are collected in real time through a high-frame-rate camera, an individualized base line is established and a fatigue rate value is dynamically calculated in combination with data of an ambient light sensor, and conversion from passive response to active prevention is realized. Through a hierarchical intervention strategy (such as brightness adjustment, blue light control and forced rest), the visual load is remarkably reduced, the intervention efficiency is improved, and the problem of insufficient adjustment hysteresis and individual adaptability in the prior art is solved.

The invention relates to the technical field of computers, and discloses a real-time rendering and interaction method and system for an immersive virtual reality scene. The method comprises the following steps: fusing tuner inertial data and eyeball tracking data, and constructing a prospective state prediction model; generating a predictive focus field in combination with scene visual saliency; synthesizing an anisotropic temporal-spatial resolution graph according to the predicted head angular velocity; gPU variable-rate coloring is driven to realize non-uniform rendering; and re-projection or dynamic fuzzy correction is executed in a self-adaptive manner according to the attitude prediction error before display. According to the technical scheme, the perception delay and the rendering load are remarkably reduced, and the frame rate stability and the visual immersion in a high-dynamic scene are improved.

The invention provides a backlight dynamic refreshing method and system based on content change frequency, and is applied to the field of image data processing. According to the method, the inter-frame variable quantity of the current image content of the display screen is pre-collected, whether the image refreshing speed is matched with the backlight response or not is judged, the pixel change rate in unit time is calculated based on the frame difference method, the content change frequency index is reasonably divided, the backlight PWM parameters are dynamically adjusted in combination with user setting, and the display quality is improved. The response coordination of the display screen under the dynamic image is effectively improved, when the frame rate fluctuation is recognized, the gray scale compensation frame is introduced and the brightness change slope is limited, and the problems of smear, splash screen and the like caused by asynchronous refreshing can be relieved.