144 results about "High-motion" patented technology

The invention discloses an event information guided image deblurring and high-frame-rate reconstruction method. The method comprises the following steps: step 1, obtaining a blurred image and an event stream corresponding to the blurred image to construct a training data set; 2, constructing a deblurring and frame insertion combined reconstruction network based on a dynamic cross-modal fusion module; step 3, training to obtain a trained joint reconstruction network based on the cross-modal attention mechanism and the UNet architecture; and step 4, inputting a to-be-reconstructed blurred image and a corresponding event stream into the trained deblurring and frame insertion combined reconstruction network based on the dynamic cross-modal fusion module to obtain a final multi-frame reconstruction image. According to the method, a higher weight dynamic state is given to an event mode in a high-speed motion scene, an image data weight is added in a static scene, and a scale feature fusion strategy is adopted for a seriously fuzzy scene, so that the problems of semantic difference and noise interference are reduced, and the image recovery quality of a fuzzy region is improved.

The invention belongs to the technical field of interventional robots, and discloses a method, device and equipment for automatically adjusting the collection frame rate and a medium, and the method comprises the steps: obtaining the current movement speed of an interventional robot; adjusting a corresponding collection frame rate according to the movement speed; and controlling a camera to perform data acquisition based on the acquisition frame rate. The appropriate frame rate is selected according to the real-time movement speed of the interventional robot, the high frame rate is provided during high-speed movement by dynamically adjusting the collection frame rate of the camera so as to reduce movement blur, and the frame rate is reduced in a low-speed or static state so as to save bandwidth resources. According to the method, unnecessary data transmission quantity is reduced, network congestion and processing burden are relieved, the overall performance and stability of the system are improved, real-time and accurate transmission of image information is ensured, smooth and clear visual feedback is provided, the accurate control capability in the intervention process is improved, and the safety of the intervention process is improved.

Ther present invention provides a technique for evaluating high-speed motion included in an operation of a processing unit. Firstly, a specific operation of the processing unit is shot by an event-based camera. In this way, event data is acquired, which includes information about only pixels whose luminance values have changed. Then, an evaluation value is calculated based on the event data. Thereafter, the specific operation of the processing unit is evaluated in accordance with the calculated evaluation value. The event data has recorded therein information about high-speed motion included in the specific operation of the processing unit. Accordingly, it is possible to evaluate the high-speed motion in accordance with the evaluation value.

The invention discloses a badminton tracking method and system based on three-dimensional vision, and relates to computer vision. Badminton motion video data of a left view and a right view are synchronously collected through a binocular camera, a left view frame sequence and a right view frame sequence which are aligned in time are obtained, and the collected video data are preprocessed; obtaining standardized left and right view input frame data; according to input frame data, constructing a 2D key frame detection model based on an improved YOLOv8 network, and extracting the sum of 2D key frame coordinates of left and right views; according to the 2D key frame coordinate sum of the left view and the right view, 3D space positioning is carried out on the badminton through stereo matching and track prediction, 3D track data are obtained, according to the 3D track data, a broken track is repaired through a frame leakage compensation mechanism, and a final 3D track is obtained. In order to solve the problem that in the prior art, key frames are prone to being lost and track breakage is caused during high-speed movement such as smash, the breakage track of the shuttlecock is repaired.

The invention discloses a motion capture method based on sports equipment training, and relates to the technical field of intelligent motion capture, and the method comprises the steps: extracting a skeleton key point set of a detected object from a training ground image data stream through employing a human body key point detection algorithm, and extracting a two-dimensional contour region of sports equipment through employing a target segmentation algorithm, meanwhile, recording time index information of the corresponding image frames, performing synchronous comparison by utilizing timestamps of the training event data streams, establishing a time sequence mapping relation, and obtaining time sequence action data; taking the time sequence action data as a space anchor point, carrying out middle frame reconstruction on the high-speed motion stage based on a time sequence mapping relation, recovering an equipment motion track, and carrying out joint matching to generate a time sequence fusion sequence; establishing a multi-view geometric constraint through a time sequence fusion sequence and camera pose parameter information, and recovering a human body three-dimensional skeleton point cloud and an initial six-dimensional pose of the equipment; the space-time consistency and reconstruction precision of motion capture in a high-speed dynamic training scene are effectively improved.

The invention discloses a contact network insulator damage detection method and device based on few-sample transfer learning. The method comprises the following steps: inputting a to-be-detected contact network insulator image into a two-stage comparison suggestion coding network; the encoder performs feature encoding and feature extraction on the insulator image, and extracts feature representation of the image; the adaptive feature fusion module obtains an optimal fusion weight through adaptive weight learning; a hierarchical feature extraction module receives output of the adaptive feature fusion module, and extracts local position information of small objects in a shallow network of the encoder, global information of large objects in a deep network and local and global intermediate semantic information in an intermediate network layer; the inter-class and intra-class comparison suggestion coding module receives the output of the hierarchical feature extraction module, calculates the semantic similarity between different classes, and achieves the damage detection of the contact network insulator in a complex environment and a high-speed motion scene. According to the invention, the accuracy and efficiency of contact network insulator damage detection are improved.

The invention relates to the technical field of image communication, in particular to a video slow-action frame insertion playback system based on a generative adversarial network, which comprises a video signal acquisition module, a signal processing module, a frame rate conversion module and a playback code output module. The acquisition module outputs an original video frame sequence through an annular buffer; the processing module separates the denoised detail components and the edge gradient features in parallel; the frame rate conversion module uses a geometric structure as a boundary locking condition to guide detail components to execute nonlinear motion compensation and intermediate frame reconstruction; and the playback module executes time base remapping and distributed coding transmission. According to the invention, through a depth generation architecture of structural constraint textures, in combination with space-time consistency verification and a nearest neighbor pixel backfilling mechanism and a virtual time base rate decoupling technology, real-time slow-action video redisk with high signal-to-noise ratio and no artifacts for a high-speed moving target is realized.

The invention provides an automatic sorting and rechecking method and system for a whole pack of instant lottery tickets based on super-resolution vision, and relates to the technical field of machine vision. Details of motion blur loss are recovered through dynamic inter-frame alignment and multi-scale feature fusion, and a high-resolution image is generated. Static visual features are extracted, lottery ticket scrape-open layer film fluorescence spectrum response features of the first page of the lottery ticket bag are obtained, film material distribution characteristics are obtained through spectrum decomposition and fused into multi-modal features, the multi-modal features are matched with a standard library, and a preliminary sorting result is obtained. In the sorting process, the grabbing time sequence consistency of the mechanical arm is monitored, re-checking is started and abnormal time period characteristics are backtracked if the result reaches the threshold critical value or the time sequence is abnormal, and a re-checking report is formed if a plurality of judgment results are not consistent, so that the accuracy and reliability of automatic sorting of the whole lottery ticket can be guaranteed.

For controlling reconstruction in emission tomography, the quality of data for detected emissions and / or the application controls the settings used in reconstruction. For example, a count density of the detected emissions is used to control the number of iterations in reconstruction to more likely avoid over and under fitting. The count density may be adaptively determined by re-binning through pixel size adjustment to find a smallest pixel size providing a sufficient count density. As another example, the detected data may have poor quality due to motion or high body mass index (BMI) of the patient, so the reconstruction is set to perform differently (e.g., less smoothing for high motion or a different number of iterations for high BMI). The quality of the data may be used in conjunction with the application or task for imaging the patient to control the reconstruction.

The invention relates to the technical field of computer vision and image processing, in particular to a foreground detection method fusing wavelet transform and a prompt mechanism, which is characterized in that in a dynamic background, high-speed motion and small target scene, F-measure is averagely improved by more than or equal to 0.30, and the detection precision is obviously superior to that of FFNet and ASCNet. The wavelet transform attention module suppresses background noise, highlights target edges and textures, and improves input feature purity. The CFF, MFR and PB of the decoder collaboratively fuse multi-scale features, redundant information is reduced, and target details and contour integrity are reserved. According to integral end-to-end training, single-frame reasoning only needs 28 ms, and real-time performance and accuracy are both considered. Therefore, the problems that in an existing neural network foreground target detection algorithm, input data are often influenced by noise and background interference, redundant information is easily introduced into a decoder in the multi-level feature fusion and transmission process, and consequently the detection result is inaccurate are solved.

The invention discloses an event camera image reconstruction method of a multi-frame fusion network based on optical flow guidance, and belongs to the technical field of computer vision and image processing. The method comprises the following steps of: 1, acquiring event data, and converting the event data into continuous and smooth space-time voxels by adopting a full-time interval voxel coding scheme based on Gaussian distribution; step 2, constructing an FMF-Net network guided by an optical flow; step 3, designing a comprehensive loss function used for training the FMF-Net network; 4, performing supervised training on the FMF-Net network by using the public event data set; and step 5, inputting space-time voxels by using the trained FMF-Net network, and outputting a high-fidelity reconstructed image. According to the method, long-time motion clues and time domain dynamic features can be fully utilized, high-fidelity image reconstruction is realized under high-speed motion and sparse event input, the problems of loss of reconstruction details and poor consistency of an existing method in a dynamic scene are solved, and the structural similarity and visual quality of a reconstructed image are remarkably improved.

The invention provides a camera-based AI visual recognition and prediction control method and related equipment, and the method comprises the steps: obtaining continuous image frames of a moving object, and recognizing the skeleton key point coordinates and appearance feature information of the moving object; inputting the skeleton key point coordinates and the appearance feature information into a preset time sequence neural network model to obtain a motion prediction track; performing space mapping on the centroid coordinates of the moving object according to the motion prediction trajectory, and determining focal length control parameters of the camera; meanwhile, angle mapping is carried out on the position offset of the moving object, and pan-tilt control parameters are determined; and tracking and shooting the moving object according to the focal length control parameter and the holder control parameter. Through the mode, the camera can complete the pre-adjustment of the focusing mechanism and the composition direction before the target motion trend occurs, thereby effectively reducing the delay error in the focal length switching process, and improving the clear imaging rate and composition stability of a high-speed motion main body.

The invention discloses an ultrahigh-speed imaging method, device and system of an event camera, and belongs to the technical field of image processing. The method comprises the following steps: acquiring a superpixel segmentation mask of a motion area according to an event trigger position and an image appearance-position feature, selecting event points in the superpixel segmentation area for continuous time point tracking, and calculating an optical flow field with continuous time and dense space by combining a point tracking time sequence track and the spatial superpixel mask. An imaging result of any to-be-imaged moment t between the two frames is calculated by using the optical flow field, and high-precision imaging of an ultra-high-speed motion scene can be realized.

The invention discloses a robot video stream inspection method based on AI real-time vision, and the method comprises the steps: 1, obtaining an inspection route, and dividing the inspection route into a plurality of non-stop route segments according to different holder angles of a robot; 2, the robot starts to inspect along the inspection route, when the robot is located at the identification starting point, the robot configures motion parameters of the robot, parameters of the pan-tilt camera and a target needing to be identified in the route section, then the robot moves along the inspection route, meanwhile, the pan-tilt camera starts to acquire target image information until the robot moves to the identification ending point, and identification is completed; the pan-tilt camera stops working; and step 3, identifying the target image information acquired by the pan-tilt camera, and judging whether there is an abnormality or not. According to the scheme, the visible light imaging definition in the movement process of the robot is guaranteed, it is guaranteed that the robot can still keep a clear shot picture in the continuous high-speed movement state, and the accuracy and reliability of image recognition are improved.

1. Name of the product in this design: Camera (High-speed camera - SH3). 2. Purpose of this design: This design is used for photographing high-speed moving targets. 3. The key design features of this product are its shape. 4. The image or photograph that best illustrates the design's key points: 3D view 1.

This invention relates to the field of 3D geometric modeling engine technology, specifically to a method for rapidly displaying Points of Interest (POI) information from a 3D real-world model. The invention first monitors the motion state of a virtual camera, reusing historical states during high-speed movement to avoid image jumps caused by aliasing. Second, it calculates the original occlusion distance of the POI and quantifies the physical depth difference between it and the scene. Then, by analyzing the local window depth distribution, it obtains discrete suppression weights to correct the original distance, adaptively distinguishing between solid and discrete structures, suppressing vegetation noise while maintaining high sensitivity to building edges. Finally, it constructs a state update cost based on the corrected distance and introduces hysteresis decision logic, setting a potential energy threshold for state switching, effectively reducing flickering in critical areas. This significantly improves the accuracy and stability of POI information display.

The present invention discloses a barcode decoding chip, method, electronic device and storage medium for parallel decoding, wherein the chip comprises: an MCU control unit, an XIP FLASH, a program RAM, a DVP / MIPI interface controller, a core decoding unit and a UART / USB communication interface; the MCU control unit performs unified scheduling; the XIP FLASH is used to store the program run by the MCU control unit; the program RAM is used to store program variables during operation; the DVP / MIPI interface controller is used to receive image data transmitted by a CMOS image sensor and transfer it to a core decoding unit; the core decoding unit is used for parallel barcode decoding; the UART / USB communication interface is used for the barcode decoding chip to communicate with a host computer. The present invention solves the problem of reduced decoding speed and inability to cope with high mobile adaptability scenarios caused by serial decoding.

The invention relates to a large-target-surface long-focal-length two-variable high-definition zoom lens and an imaging method thereof. The large-target-surface long-focal-length two-variable high-definition zoom lens comprises a lens body, and an optical system of the lens body is composed of a front fixed lens set, a zoom lens set, a compensation lens set and a rear fixed lens set which are sequentially arranged from left to right in the light incidence direction. The system is reasonable in design, realizes a continuous zoom closed-loop control function, a focusing closed-loop control function, a focal length feedback function and an image output function, can perform large-range search and tracking camera shooting on targets with far and near distances and high-speed movement, and is applied to requirements of unmanned monitoring, early warning, marginal and coast defense and the like.

The invention discloses a target intelligent tracking method, device and equipment based on multifunctional loop fusion, a storage medium and an unmanned aerial vehicle, and the method comprises the steps: determining image motion feature data of a motion process according to a tracking video collected by a video tracking device of the unmanned aerial vehicle for the motion process of a target object, determining signal motion characteristic data of the motion process according to a tracking signal acquired by a signal tracking device of the unmanned aerial vehicle for the motion process; determining adjustment motion feature data of the motion process through reciprocal enhancement of the signal motion feature data to the image motion feature data; and controlling the flight state of the unmanned aerial vehicle according to iterative reasoning of the adjustment motion feature data and the signal motion feature data in the annular attractor network. Through information fusion of a reciprocal enhancement technology and an annular attractor network, accurate target tracking in a high-speed motion scene is realized, and the problems of high delay and large error when an unmanned aerial vehicle tracks a target object are solved.

1. The name of this design product: Online vertical high-speed motion machine. 2. Application of this product design: Positioning and dispensing of micro-precision products. Driven by a high-speed linear motor, it can achieve high-speed and precise positioning. A micro-injection system is used to apply adhesive to the narrow locations of tiny products, such as wafers, FPCBs, COMS and other high-requirement products. 3. The key point of the design of this product lies in its shape. 4. The picture or photo that best illustrates the design points: three-dimensional picture.

A virtual stereovision imaging array system and a moving target three-dimensional reconstruction method, the system comprises multiple cameras and multiple galvanometer mirrors, the galvanometer mirrors and the cameras are matched one by one, and a real-time controllable virtual camera array is formed; through synchronous control of the galvanometer mirrors, each virtual camera simultaneously tracks and locks the moving target; based on the real-time pose relationship between the virtual cameras and combined with the synchronously acquired image information, real-time three-dimensional reconstruction of the moving target is completed. The reconstruction method comprises joint calibration of the matched galvanometer mirrors and the cameras, determination of camera internal parameters and virtual camera external parameters; through real-time synchronous adjustment of the galvanometer mirrors, each virtual camera cooperatively tracks the moving target, acquires the moving target image, and updates the virtual camera external parameters in real time; in each frame of image, stereo matching is performed, and combined with the real-time updated virtual camera external parameters, the three-dimensional point cloud of the moving target is solved and obtained. The present application can complete high-efficiency and high-precision three-dimensional reconstruction of a high-speed moving target in a large field of view.

The invention relates to a ping-pong robot track recognition and ball hitting posture control system, which comprises a table surface environment sensing module, and is characterized in that the table surface environment sensing module is used for acquiring three-dimensional track data, table surface environment parameters and event signals of ping-pong balls in real time through a high-speed camera array unit and an environment state sensor unit; and a time label and a frame number are added to each frame of data, and the data are uniformly output to the multi-stage track processor module. A high-speed camera shooting array and a multi-source environment sensing technology are adopted, the three-dimensional space track of the table tennis ball can be captured in real time, dynamic adjustment is conducted according to table surface environment parameters, the multi-stage track processor can effectively remove noise and accurately extract track characteristics through a Kalman filtering self-adaptive algorithm, and therefore the table tennis ball track detection accuracy is improved. Compared with a traditional system, the system has the advantages that track recognition errors can be greatly reduced, and more accurate ball hitting angle and opportunity control can be provided.

The application discloses a kind of ultra-high speed imaging method, device and system of event camera, belong to image processing technical field;The present application obtains the superpixel segmentation mask of motion area according to event trigger position and image apparent-position feature, selects event point in superpixel segmentation area to carry out continuous time point tracking, combines point tracking time sequence track and space superpixel mask to calculate continuous time and space dense optical flow field, uses optical flow field to calculate the imaging result between two frames at any imaging time t, can realize the high-precision imaging of ultra-high speed motion scene.

The present invention discloses a long-range and short-range scanning motion control system based on an outdoor online rapid detection CT device. The outdoor online rapid detection device is a portable and movable CT scanning system device. The main purpose is to realize the rapid task of non-destructive detection of workpieces by the device through remote operation. The functions are mainly concentrated on the design concepts of high precision of the motion axis of the device, high image quality, and high automation integration. The system is mainly composed of a ring track component and a motion control component, wherein the ring track component serves as the main mechanical device. It includes a supporting device, a ring base, a driving device, a motion slide, etc. The track of the ring track component is designed to be assembleable and detachable, the component can be clamped on the detection object, and a ray source and a detector can be installed, and the ray source and the detector can rotate synchronously. The remote control system is mainly composed of a remote control console, a remote emergency stop button box, a cable reel, a remote control box, and remote communication equipment.

The present invention discloses a high-speed motion control method applied to a phase modulation workbench of an LCOS system, which includes dividing a large-format processing pattern into several pattern blocks, generating two-dimensional physical coordinates and pattern block numbers corresponding to each pattern block, and sorting the two-dimensional physical coordinate set in the position file in ascending order row by row or column by column; the motion controller uploads the data row by row or column by column to the memory of the motion controller in sequence, and uploads the sub-bitmaps corresponding to the pattern block numbers to the memory of the LCOS board row by row or column by column; the workbench scanning axis triggers a timing pulse signal by position, and simultaneously sends it to the LCOS and the pulsed light source to form a fast pulse scanning exposure. The present invention utilizes the characteristics of high pulse laser energy, short pulse width, and high repetition frequency, and realizes single-frame polarization pattern recording based on multiple pulses. For the precise control of the motion of the workbench, it has achieved the advantages of large exposure area, high efficiency, and good reliability.

The invention relates to the technical field of image processing and the technical field of automation, and particularly discloses a woodworking table saw safety detection method based on machine vision, compared with a traditional mechanical limit switch (the response time is greater than or equal to 500ms), the time difference from dangerous action to safety response is greatly shortened, and the safety of a woodworking table saw is improved. According to the method, cutting injury caused by misoperation and distraction is effectively avoided, the safety of hands and limbs of an operator is protected, non-contact detection is adopted, interference of wood dust is avoided, a high-speed movement scene can be responded in real time, and the safety and reliability of woodworking operation are effectively improved.

The application discloses a high-speed motion three-dimensional point tracking and trajectory reconstruction method and system, and relates to the technical field of three-dimensional point tracking. The method comprises the following steps: synchronously collecting an RGB image sequence and an event stream through a binocular multi-modal observation device; performing time alignment on the RGB image sequence and the event stream, extracting an RGB feature map based on the RGB image sequence, and extracting an event feature map based on the event stream; mapping the RGB feature map and the event feature map to a three-dimensional space; supplementing a three-dimensional feature point cloud through a linear interpolation algorithm; balancing the spatial distribution of the supplemented three-dimensional feature point cloud through an anchor point sampling algorithm to obtain a fused three-dimensional feature point cloud; and generating high-speed three-dimensional point trajectory data based on the fused three-dimensional feature point cloud through a time correlation transformer. The application effectively fuses the texture fidelity of the RGB image and the high time resolution of the event data, and can realize high-frame-rate and high-precision three-dimensional point trajectory reconstruction in a high-speed motion scene.

The application discloses a motion training evaluation system and method based on cooperation of an event camera and a visual camera, and is applied to the field of computer vision, and aims at the problems that an existing training evaluation system based on an optical camera cannot capture fast motion trajectories and limb shapes, cannot effectively evaluate action quality, and cannot provide effective training guidance; the application provides continuous human motion events in the form of event streams, can achieve millisecond-level motion response, is not affected by motion blur effects of high-speed moving objects, and can provide a higher dynamic range, and can provide more effective motion training evaluation in scenes with strong light, backlight, and sharp changes in brightness. Through cooperation of the visual camera and the event camera, not only the accuracy of fast actions can be evaluated, but also standard action teaching and training in the form of visual scene interaction can be performed.