213 results about "High frame rate" patented technology

The invention discloses a dynamic monitoring and analyzing method for a thermal management component molten pool based on image recognition, and relates to the technical field of laser powder bed melting additive manufacturing. The method comprises the following steps: continuously capturing an original thermal management component molten pool image and temperature field distribution data during laser powder bed melting additive manufacturing; and optimizing the original thermal management component molten pool image to generate an optimized thermal management component molten pool image. Molten pool images and temperature field data are captured in real time through a high-frame-rate synchronous camera and an infrared sensor, defect types are recognized online in combination with a lightweight classification model, classification results are fed back to a control system to dynamically adjust laser power or scanning speed, interlayer defect accumulation can be inhibited in time, and the defect quality is improved. The defect diffusion problem caused by response lag of a traditional off-line analysis method is avoided, and the forming precision and the process stability of the heat management component are remarkably improved.

The invention discloses a high-speed imaging method, system and device based on an SPAD array and a time counting circuit. The method comprises the following steps: acquiring original data of a photon event to obtain an original photon counting matrix of each frame; performing statistical modeling based on the original photon counting matrix to obtain a dynamic threshold matrix; performing threshold filtering based on the dynamic threshold matrix in combination with the original photon counting matrix to obtain a sparse matrix; and performing accumulation and image reconstruction based on the multi-frame original photon counting matrix to output a final image. The high time resolution of the SPAD array and the TCSPC is combined with the BNQSA algorithm, the noise problem of high frame rate imaging under extremely low illumination is solved, the system has the characteristics of high sensitivity, real-time performance and low power consumption, and a breakthrough solution is provided for a weak light scene.

The invention discloses a three-dimensional voxel geometry collision detection method based on feature layering and multiple detection strategies, and relates to the technical field of computer graphics and game engines, the method comprises bit compression storage optimization, feature layering extraction and multiple collision detection, through the feature layering and multiple detection strategies, the unnecessary calculation amount is effectively reduced, and the detection efficiency is improved. The overall performance of the algorithm is improved, efficient memory compression is achieved while the detection precision is guaranteed, the requirement for computing resources is reduced, the technology can stably run in the resource-limited environment, unified collision detection processing of various geometries is supported, the universality and flexibility of the system are improved, and the system performance is improved. According to the method, integration and application in different application scenes are facilitated, the real-time rendering capability is optimized, the mobile terminal and the VR equipment are supported to run a complex physical simulation scene at a high frame rate, and the user experience and the interaction effect are improved.

The invention provides a large-view-field high-resolution compound eye camera array system based on bionic human eye vision. The system is composed of a curved surface support and an industrial camera array arranged on the curved surface support. Reverse extension lines of optical axes of all the cameras intersect at the same point to form a concave surface structure similar to the retina, and the fixed view field overlapping rate of the adjacent cameras is kept. The industrial camera array is used for collecting a target scene image, large-view-field information is obtained by fusing and splicing all camera images, and a high-resolution image is obtained by conducting super-resolution reconstruction on a plurality of related images in a view field center interested area. The system provides three working modes, namely a low-resolution mode, a conventional-resolution mode and a super-resolution mode, which can be switched by adjusting camera parameters. Finally, the system can perceive the dynamic change of the edge of the field of view in a high-frame-rate and low-resolution mode, magnify the details in the center of the field of view in a super-resolution mode, realize efficient non-uniform imaging, and optimize the information acquisition and processing efficiency and the structure compactness.

The invention provides a fast color single-pixel imaging system and method based on an FPGA and a DLP projector, the fast color single-pixel imaging system comprises the DLP projector, a single-pixel photoelectric detector, an AD data acquisition card, a Raspberry Pi and the FPGA, the Raspberry Pi is adopted as an upper computer, the FPGA and the AD data acquisition card are dispatched to work cooperatively, and the DLP projector and the single-pixel photoelectric detector are integrated. The rapid and stable projection of the substrate pattern and the accurate sampling of the corresponding reflected light intensity information are realized, and the efficient reconstruction of the color image of the target scene is further realized. In a data acquisition stage of an imaging system, an HDMI image data output task is executed by the FPGA, and the FPGA outputs an image frame synchronization signal, so that the stability problem and the signal synchronization problem when a substrate pattern is played at a high frame rate (60Hz) are solved by making full use of the advantages of stable and controllable sequential logic and no software level scheduling delay of the FPGA, and the stability problem and the signal synchronization problem when the substrate pattern is played at a high frame rate (60Hz) are solved. And the influence of image tearing, frame loss and frame repetition on image reconstruction is eliminated.

Video data transmission with prioritized frame sequences is disclosed for faster processing and play of a segment of a content item. High and low priority video frame transmission sequences are determined. Depending on an indication of the time remaining until play of the video segment, when sufficient time remains for reception of only the high priority frames, for example, I-frames and perhaps some P-frames, then only those are transmitted. These may be played at a lower frame rate before continuing with a subsequent video segment. In response to determining that, before start of play of the segment, sufficient time remains for reception of additional frames, for example, some B-frames, the lower priority frames may be transmitted. In this case, the segment may be played at a higher frame rate. Throughput may be determined according to an adaptive bitrate (ABR) implementation.

The invention relates to a self-supervision diagnosis method for welding quality abnormity, and aims to solve the problems of unstable welding seam state characterization, high abnormity diagnosis false alarm rate, insufficient adaptability and the like caused by multi-view image acquisition time sequence difference, complex illumination interference and characteristic drift in the welding process. According to the core scheme, the method comprises the steps of synchronously collecting multi-view-angle continuous images of a welding area through multiple cameras at a high frame rate, conducting time sequence synchronization, area focusing, denoising and brightness normalization processing on the original images, extracting normalized frame-level features through a pre-trained convolutional neural network, improving feature space semantic stability through a semantic anchor point generation and dynamic alignment mechanism, and improving the accuracy of image fusion. And abnormal detection and multi-stage dynamic loss adjustment are introduced, so that welding quality abnormal judgment and model self-adaptive optimization are realized. According to the method, the consistency and robustness of welding visual representation can be effectively enhanced, and the accuracy of welding quality anomaly detection and the system generalization ability are improved.

The invention provides an Electron master screen optimization method based on polymorphic rendering and state awareness, and is applied to the technical field of data processing. According to the method, aiming at an Electron advertisement screen application, a window focus, a power supply state and user interaction are monitored through BrowserWindows API and Node.jPowerMonitor, and three playing states, namely an active playing state, a low-frequency playing state and a background playing state, are judged. Rendering modes are dynamically switched according to the states, GPU acceleration is + 60 fps high frame rate in the active state, CPU software rendering is + 15 fps low frame rate in the low frequency state, and off-screen rendering is conducted on cached frame data in the background state. And the local redrawing is realized by combining the Offscene Canvas and the WebWorker, so that the invalid calculation is reduced. Resources such as DOM nodes and GPU memories are actively recycled in the background state, quick recovery is achieved after focus obtaining, users do not perceive the whole process, resource occupation and energy consumption are greatly reduced, and operation stability is improved.

The invention discloses a grayscale image translation motion blur recovery method and system based on optical flow guidance, and belongs to the technical field of image processing. A target area is determined based on a video stream H; calculating a translational motion vector field matrix between every two adjacent frames in the video stream H by adopting an optical flow method, obtaining a translational motion vector located in a target area, further constructing a track representation matrix for reflecting a motion track of a motion target generating translational motion, normalizing the track representation matrix to serve as a blurring kernel, and obtaining a motion vector field matrix; and translational motion blur of the target area is removed in a targeted manner. According to the method, the high-density time sampling information provided by the video stream H with the high frame rate and the low signal-to-noise ratio is utilized, and the complex translational motion track of the blurred image B with the low frame rate and the high signal-to-noise ratio in the exposure period can be accurately captured. The fuzzy kernel synthesized based on the accurate translational motion trails can highly approach a real physical fuzzy process, and an image with a high signal-to-noise ratio and high definition can be reconstructed.

The invention discloses a visible light image and sound wave data-based visual fusion display method and system, and relates to the technical field of image and sound wave fusion display, and the method comprises the steps: data collection: collecting image frames through an industrial visible light camera, collecting sound wave data through an eight-channel microphone array, synchronizing timestamps, and enabling a dynamic scene to be high in frame rate; a preprocessing step: denoising and sharpening the image, filtering interference by sound waves, and carrying out space-time registration; a feature extraction step: extracting image edge texture and sound wave frequency energy features; a fusion calculation step: dynamically adjusting the weight and generating a fusion feature matrix in combination with an attention mechanism; and a visual display step: constructing 2D, 3D and AR interfaces, superposing sound wave information and supporting multi-modal interaction and parameter control. According to the method, the image and sound wave fusion accuracy is improved, scene adjustment parameters are dynamically adapted, multi-dimensional display is visual, interaction is convenient and fast, the exception recognition and response capability is enhanced, and the method adapts to multi-scene requirements.

The invention discloses a video intelligent monitoring system and method based on cross-modal time-frequency fusion, and relates to the technical field of new energy power monitoring and safety management, and the method comprises the following steps: obtaining multi-modal physical data; detecting a waveform characteristic of the electrical signal, and when the waveform characteristic of the electrical signal meets a preset electrical abnormal condition, performing high frame rate sampling and frame rate compensation on the visible light video to obtain video data with enhanced time sequence continuity; converting the video data, the thermal infrared image, the acoustic signal and the electrical signal to a time-frequency domain to obtain a multi-modal video feature, and inputting the multi-modal video feature to a cross-modal fusion network to obtain a fusion feature vector; and performing anomaly type prediction on the fusion feature vector based on a long-short term memory network in combination with a semantic map model to obtain an anomaly type recognition result and a risk level judgment result. According to the method, the problem that the multi-modal data lacks a unified time reference and fusion mechanism can be solved.

The invention discloses a high-speed snapshot system and method, and relates to the technical field of image acquisition. The system comprises a trigger detection module, an image acquisition module, a processing and control module, a DDR cache chip and a storage and transmission module. The image acquisition module adopts a high-speed CMOS (Complementary Metal-Oxide-Semiconductor Transistor) image sensor and works in a high-frame-rate mode which is not lower than 120 frames per second under a preset resolution ratio; the processing and control module adopts a system-level chip integrated with an image signal processor and a hardware encoder; the DDR cache chip is connected with the processing and control module through a memory bus and serves as a high-speed data buffer pool. Through cooperative work of a high-frame-rate sensor and a hardware-level encoder and cooperation of independent DDR cache, clear, continuous and frame-loss-free snapshot of high-speed moving targets such as flying insects is realized, and the problems of image blurring and incomplete data caused by insufficient frame rate and limited data processing capability in the prior art are solved. The system is high in integration level, flexible in deployment and suitable for field monitoring and laboratory research.

Changes in tissue stiffness have long been associated with disease. Systems and methods for determining the stiffness of tissues using ultrasonography may include a device for inducing a propagating shear wave in tissue and tracking the speed of propagation, which is directly related to tissue stiffness and density. The speed of a propagating shear wave may be detected by imaging a tissue at a high frame rate and detecting the propagating wave as a perturbance in successive image frames relative to a baseline image of the tissue in an undisturbed state. In some embodiments, sufficiently high frame rates may be achieved by using a ping-based ultrasound imaging technique in which unfocused omni-directional pings are transmitted (in an imaging plane or in a hemisphere) into a region of interest. Receiving echoes of the omnidirectional pings with multiple receive apertures allows for substantially improved lateral resolution.

The invention discloses a traffic light fault real-time identification and alarm method based on improved Yolov5, and relates to the technical field of intelligent traffic, and the method comprises the steps: S1, building a traffic light fault data set in advance, and collecting traffic light images and video data under different scenes, illumination conditions and weathers; step S2, constructing an improved Yolov5 model; and S3, extracting images of a real-time video stream to be detected according to frames, inputting the images into the trained improved Yolov5 model, outputting position information, light color states and fault probabilities of traffic lights, and analyzing and judging fault types in combination with a preset threshold value and a multi-frame time sequence. Real-time video stream processing and multi-frame time sequence analysis are combined, the high-frame-rate real-time detection requirement can be met, time sequence faults can be accurately judged, and the limitation that manual inspection is low in efficiency and poor in real-time performance is broken through; the fault response and handling period is greatly shortened, and powerful technical support is provided for guaranteeing normal operation of the traffic lights and improving urban traffic management efficiency.

To display a display object to be superimposed on an imaging apparatus at a high frame rate, while preventing a reduction in the visibility of the display object.SOLUTION: An imaging apparatus of the present invention has: drawing means that draws a display object; superimposition means that superimposes the drawn display object on a picked-up image; and control means that performs control to display, on a display, the picked-up image on which the display object is superimposed. When predetermined conditions are not satisfied, the drawing means draws the display object in a predetermined size, and when the predetermined conditions are satisfied, draws the display object in a size smaller than the predetermined size.SELECTED DRAWING: Figure 3

This invention provides a lossless compression and decoding method for depth images. Lossless compression includes: dividing sequential data into multiple independent image blocks according to predetermined partitioning rules; selecting a corresponding thread model based on the characteristics of the depth image; calling a thread based on the thread model and using a reversible encoding algorithm to independently encode each image block; wherein, at the start of encoding for each image block, the encoder state is reset so that the encoding of each image block does not depend on the data of the preceding image block; generating metadata containing position index and compressed data length information and assembling it with the encoded image block for output. Lossless decoding includes: reading the metadata and decoding at least one image block based on the metadata. Through the above methods, parallel encoding and decoding are achieved; precise positioning via physical offsets and random access and on-demand region decoding are supported, improving the processing response of high frame rate depth streams under low computing power environments while ensuring lossless restoration.

The invention relates to a belt conveyor material flow real-time analysis system based on active 4D stereoscopic vision. The system comprises a 3D laser vision module, wherein the 3D laser vision module comprises three groups of 3D high-frame-rate industrial cameras and corresponding laser emitters; the 3D high-frame-rate industrial cameras are arranged at the head part, the middle part and the tail part of a belt conveyor and are synchronously triggered in time; the motion compensation modules are arranged at the head and the tail of the belt conveyor; the data processing terminal is respectively connected with the 3D laser vision module and the motion compensation module through special cables; and the data display and control terminal is in communication connection with the data processing terminal and is used for receiving the processing result and displaying the 4D dynamic model, the flow data and the alarm information in real time. By means of the software and hardware collaborative design and algorithm innovation, high-precision, real-time and non-contact three-dimensional visual monitoring and intelligent analysis of the material flow of the belt conveyor are achieved.

The application discloses a video time variable sampling method and device based on a reversible network and a medium, belongs to the technical field of video coding, and solves the problem of serious loss of information in the down-sampling and coding stages during video time variable sampling coding; the reversible time domain wavelet transform structure of multiple input and multiple output is adopted, input high frame rate video is decomposed into odd and even sequence frames, a bidirectional reference frame mechanism is introduced, a time domain low frequency subband and a high frequency subband are generated, high-quality video time frequency band decomposition can be realized without transmitting explicit motion information between forward transformation and inverse transformation, a gradient agent network simulating the compression behavior of a traditional encoder is introduced, motion vectors and quantization parameters are taken as input, a reversible affine coupling transform model encoder perceiving coding quality is adopted to code the distortion of the time domain low frequency, and the defects that the existing agent network depends on motion vector transmission or fixed coding parameters and is difficult to adapt to actual variable application scenarios can be overcome.

To provide a technique advantageous for achieving both a frame rate and distance measurement accuracy.SOLUTION: A distance image creation device comprises a plurality of pixels, and an image creation unit for creating a distance image in each of a plurality of distance measurement frame periods. In each distance measurement frame period, a plurality of sub-frames are acquired by a plurality of detection operations different from each other in the time from light emission timing in a light source until an exposure period in which each pixel detects light. The distance image creation device further comprises an event detection unit that, for each of the plurality of pixels, detects a change in a signal value between at least two distance measurement frame periods. In each distance measurement frame period, for the pixel for which the event detection unit detects the change, the image creation unit acquires the pixel value of the distance image on the basis of the plurality of sub-frames. For the pixel for which the event detection unit does not detect the change, the image creation unit does not acquire the pixel value of the distance image, or when a set condition is satisfied, acquires the pixel value of the distance image on the basis of the plurality of sub-frames.SELECTED DRAWING: Figure 14

The application discloses a kind of based on visible light image and acoustic wave data's visual fusion display method and system, it is related to image acoustic wave fusion display technical field, including data acquisition step, image frame is collected with industrial visible light camera, 8 channel microphone array acquires acoustic wave data, synchronous time stamp and dynamic scene adjustable high frame rate;Preprocessing step, to image denoising sharpening, acoustic wave interference is filtered and space-time registration;Feature extraction step, extract image edge texture and acoustic wave frequency energy characteristics;Fusion calculation step, dynamically adjust weight and generate fusion feature matrix in combination with attention mechanism;Visual display step, construct 2D, 3D and AR interface, superimpose acoustic wave information and support multimodal interaction and parameter control.This method improves image and acoustic wave fusion accuracy, dynamically adapts scene adjustment parameter, multidimensional display intuitive and interaction is convenient, enhances abnormal identification and response capability, adapts to multi-scene demand.

The application discloses a cross-view multi-target real-time trajectory tracking method, which combines a machine vision image acquisition system with a master control platform to realize distributed acquisition and centralized processing system architecture, realizes multi-target multi-view real-time image acquisition in a large scene through four sets or more than four sets of large field high-speed cameras, and realizes multi-target motion trajectory tracking. The application uses no less than four sets of acquisition systems to realize full-scene view coverage, solves the problems of poor target positioning accuracy and target position information loss caused by mutual shielding in the single view acquisition mode. Compared with a target positioning method based on a deep learning model, the multi-camera joint solution of the target position can realize higher positioning accuracy, better positioning robustness and higher frame rate.

The invention relates to the technical field of unmanned aerial vehicle control, and discloses an unmanned aerial vehicle accurate landing method based on image recognition, which comprises the following steps: an unmanned aerial vehicle receives a guide signal or a GPS coordinate from a landing platform, and flies to the sky of a landing area; the unmanned aerial vehicle vertically and downwards shoots an image containing a preset landing mark through an airborne camera; preprocessing and feature enhancement are carried out on the shot image, then the image is input to a target detection network, and a center pixel coordinate of a landing mark and contour information of the landing mark in the image are identified; and combining flight height sensor data of the unmanned aerial vehicle according to the corresponding relationship between the pixel size of the identified landing mark and the real-world size of the landing mark. The method is switched to a high-frame-rate image acquisition mode in a short-distance landing stage, realizes sub-centimeter-level position alignment precision through real-time visual servo fine adjustment, effectively eliminates accumulated deviation before final grounding, and provides key space alignment guarantee for stable and accurate landing of the unmanned aerial vehicle.

The application relates to the technical field of pattern recognition, and discloses a notebook computer intelligent wake-up method and system based on pattern recognition, which introduces a brightness difference judgment in a low-power mode, effectively avoids starting high-power image processing when the ambient light changes are not obvious, and thus saves system resources. When the ambient brightness changes reach a preset threshold, the system is switched to an active working mode with high resolution and high frame rate, a second environment image with higher clarity and detail is acquired, and a user's spatial posture sequence is extracted based on the second environment image. In this way, the similarity between the spatial posture sequence and a pre-stored wake-up posture sequence is judged, the recognition difficulty in a complex scene of traditional face recognition is effectively avoided, accurate intelligent wake-up operation can be realized, the success rate of intelligent wake-up and the user experience are significantly improved, and the recognition failure problem caused by damaged image quality and face feature shielding in the prior art is overcome.

The application discloses a kind of non-contact physiological signal monitoring systems based on image recognition, comprising: evoked collection module, for output light stimulation sequence and gaze guide sequence, and the high frame rate video image of the body area of target object is collected;Unit mapping module is used to construct multiple physiological response units, generate physiological response unit topology chart;Demodulation extraction module is used to perform encoding demodulation processing, generate unit evoked response feature set;Transmitting configuration module is used to construct physiological response transmission atlas;Separation correction module is used to separate and inhibit unit evoked response feature set;Inversion analysis module is used to carry out inversion, generate physiological inversion parameter set;Calibration compensation module is used to construct individual response calibration model and carry out compensation correction;Abnormal output module is used to generate abnormal monitoring result.The application multi-region image recognition, realize non-contact physiological signal monitoring.

The invention discloses a multi-focus composite Fresnel phase diagram rapid generation and power equalization method and system for one-to-many free space laser communication. According to the method, aiming at a scene in which a plurality of user targets are located at different directional angles and different propagation distances, a focusing + directional single-beam phase is constructed for each target on the basis of analyzing a Fresnel zone lens phase and a linear tilt phase, and the phase is taken after complex field superposition is performed according to a preset power weight, so that the target target is obtained. A composite phase diagram for a phase-type spatial light modulator (SLM) is directly obtained. The power weight is preset according to a link budget or a task demand so as to realize on-demand distribution and equalization of multi-beam output power; and meanwhile, fixed phase bias can be introduced to each beam to suppress inter-beam interference fringes. According to the method, frame-by-frame iterative solution is not needed, the calculation complexity is low, and high-frame-rate and low-delay online updating is easy to realize.

The application discloses a long-distance rail recognition and obstacle detection method and system, a long-focus optical system is combined with a super-high-speed industrial camera on a hardware level to build a high-frame-rate and long-distance optical detection system, a region of interest for obstacle detection is demarcated by recognizing and visually segmenting left and right rail lines on a software level, and a target detection-based track obstacle intrusion detection algorithm and other advanced visual tasks are executed, and finally high-frame-rate recognition and detection of long-distance rails and track obstacles are realized. The Schmidt-Cassegrain optical system with a focal length of 2000mm is combined with a super-high-speed industrial camera with a resolution of 1920*1080 and 3000 frames per second to build a long-distance high-frame-rate optical detection platform and erect on a driving position of a train, railway conditions within a range of 6km are detected in real time, and serious accidents caused by a too long braking distance of the train due to high-speed driving can be prevented. Compared with traditional train driver eye observation and laser radar scanning imaging modes, a long-distance optical observation platform and a rear-end real-time detection system can realize a longer detection distance, better detection and recognition robustness and a higher frame rate.

The present application relates to the technical field of electronic devices. Provided are a frame rate adjustment method, an electronic device, a chip system and a storage medium. In the method, an application interface displayed by an electronic device may comprise a plurality of views, and when user operations are performed on different views, frame rates during the execution of response events corresponding to the user operations may be determined on the basis of the views on which the user operations are performed. A response event may be a switching process of switching from the current interface to another interface, which process is triggered by a user operation. For the user operations performed on different views, the frame rates during the execution of the response events may also be different. In this way, frame rates during the execution of some response events with high smoothness requirements may be adjusted to relatively high frame rates, so as to improve the smoothness during interface switching; and frame rates during the execution of some response events with low smoothness requirements may be adjusted to relatively low frame rates, so as to avoid excessive power consumption caused by increasing the frame rates.

The application discloses a kind of facial expression muscle dynamic coordination evaluation system based on deep learning, including data acquisition module, for collecting the multi-object high frame rate facial dynamic video of preoperative baseline period of subject and the multi-object high frame rate facial dynamic video of postoperative review period;Data preprocessing module is used to generate preoperative three-dimensional facial coordinate dataset and postoperative three-dimensional facial coordinate dataset;Vector field extraction module, extract preoperative full-face expression muscle three-dimensional displacement vector field and postoperative full-face expression muscle three-dimensional displacement vector field;Feature extraction module, extract the physiological asymmetry reference feature set of bilateral corresponding muscle area before operation, and the motion feature set of bilateral corresponding muscle area after operation;Model inference module, output eliminates the quantitative value of diagnosis and treatment related muscle movement symmetry deviation and dynamic coordination degree change quantitative value after innate physiological asymmetry;Result generation module generates the expression muscle dynamic coordination change evaluation result of corresponding subject before and after oral diagnosis and treatment.

To simultaneously obtain a high frame rate moving image for recording or a high frame rate moving image for display while maintaining a continuous shooting speed when continuously shooting still images. [Solution] The device comprises a plurality of pixels, each pixel having a sensor means for outputting a pulse signal at a frequency corresponding to the frequency of receiving photons and a counting means for counting the number of said pulse signals; a control means for controlling the timing of resetting the count value counted by said counting means and the timing of reading out the count value; and a generation means for generating a first signal at a predetermined first frame rate based on the count values ​​read out at a plurality of different times and the timing at which the count value was read out, and for generating a second signal at a second frame rate corresponding to an exposure time longer than each frame period of the first frame rate.

The invention provides an image rendering method and apparatus, an electronic device and a computer program, and relates to the technical field of image processing, and point cloud positions and color information of point clouds are stored in textures, and point clouds are directly sorted and screened on a processor side, so that the image rendering efficiency is improved. The texture of the stored point cloud information and the index data after point cloud sorting are transmitted to a graphics processor, namely a preset accelerator, for image rendering processing, data required by rendering can be prepared without the support of a calculation shader and a struct Buffer, frequent data transmission between a CPU and a GPU is not needed, meanwhile, the requirements for hardware and a platform are low, and the implementation is easy. According to the image rendering method, the requirements of high frame rate and cross-platform can be met, so that the problems of how to reduce the computing power overhead of image rendering and improve the applicability of the image rendering method can be solved, and the technical effects of reducing the computing power overhead of image rendering and improving the applicability of the image rendering method are achieved.