1201 results about "Multiple frame" patented technology

The invention relates to an optical film detection method, device and equipment based on image processing. The method comprises the following steps: collecting multiple frames of images of a multilayer optical film under different illumination conditions, and carrying out preprocessing and characteristic value calculation on the multiple frames of images to obtain a characteristic value response matrix; calculating an optimal weight coefficient of each frame of image according to the feature value response matrix, and performing multi-frame image feature fusion to obtain integrated feature representation; performing multi-scale defect feature extraction on the integrated feature representation to obtain a defect candidate region; spectral response characteristics are extracted based on the defect candidate area, matching degree calculation is carried out on the spectral response characteristics and a preset wavelength-film thickness mapping relation matrix, and a multilayer film defect distribution diagram is obtained; and performing autoregression prediction and processing control parameter optimization on the multilayer film defect distribution diagram to obtain a closed-loop control scheme. According to the invention, accurate identification and classification of different film layer defects are realized, and closed-loop control of defect detection results and manufacturing parameter optimization is further realized.

An image enhancement method using multi-frame stacking comprises the steps of storing multiple frames of a target scene captured by a frame-based camera during an acquisition interval; storing a series of events produced during the acquisition interval by an event-based camera viewing the target scene; synchronizing timestamps of the events and timestamps of the frames; selecting an anchor frame among the multiple frames; aligning a current frame with respect to the anchor frame, based on stored events having timestamps corresponding to an interval between the anchor frame and the current frame; and merging the aligned frame and the anchor frame.

The invention discloses an intelligent asphalt pavement disease detection method based on a YOLOv5 algorithm, and relates to the technical field of intelligent expressway and road maintenance, and the method comprises the steps: obtaining video data through a vehicle-mounted or airborne pan-tilt camera, and constructing an asphalt pavement disease image data set through manual marking; a YOLOv5 target detection model is adopted, an efficient multi-scale attention mechanism is introduced, and preliminary training is carried out; detecting a real-time database on the basis of a pre-trained improved YOLOv5 target detection model, and manually checking a detection result so as to optimize the model; and performing redundant data de-duplication on continuous multi-frame image information by using a dynamic planning method, correcting the image by using a chessboard method to obtain the actual size of the target, and performing evaluation according to a disease standard. Therefore, by adopting the method, the labor cost and the calculation cost can be saved, the pressure of storage requirements can be reduced, the real-time detection effect can be realized, and the method can be widely applied to asphalt pavement disease detection.

The invention provides an improved multi-frame image target detection network, namely, TFA-Net (Temporal Fusion Attention Network), which is oriented to a welding seam defect detection task. According to the network, continuous multiple frames of images are used as input, and spatial features of each frame of image are extracted through a ResNet backbone network sharing parameters. On the basis, a multi-stage feature fusion module is fused and introduced, effective integration among features of different scales is realized, and the perception capability for small-size and weak-contrast defects is improved. In order to further capture dynamic information of the target in the time dimension, a time sequence modeling module is designed, modeling is carried out on a multi-frame feature sequence, and continuous features of the target changing along with time are extracted. And then, the network adopts a gating fusion mechanism to carry out adaptive weighted fusion on the static space features and the dynamic time sequence features, and the robustness and the discrimination capability of feature representation are enhanced. Finally, the fusion features are input into a decoder module, the category probability of the defects is predicted through a classification sub-network, anchor frame position offset is calculated through a frame regression sub-network, and accurate positioning and recognition of the multiple types of defects in the weld seam image are achieved. The network has the advantages of clear structure, strong generalization ability, high adaptability and the like, and is especially suitable for the problems of small target size, unclear texture, strong motion continuity and the like in a welding seam detection scene.

The invention provides a power transmission working vehicle detection method and system based on a frame sequence, and the method comprises the steps: carrying out the frame division of a target video related to a power transmission working scene, so as to form multiple frames of image data, carrying out the depth extraction, so as to obtain depth features, carrying out the time fusion of the depth features corresponding to each frame of image data, so as to obtain a fusion feature map, therefore, by combining the time sequence information of the multiple frames of images, the detection precision and robustness of the target under the conditions of shielding, motion blur and scale change are effectively improved, then target detection about the detected target is performed to obtain the candidate target frame and the confidence score corresponding to the candidate target frame, and the target detection accuracy is improved. According to the method, weighted average is carried out based on the confidence score to obtain a smoothing result score, and the smoothing result score is compared with a pre-obtained threshold to confirm a detection result of the detection target, so that dynamic confidence evaluation and adaptive threshold adjustment are carried out based on multi-frame information, single-frame false detection and missing detection can be remarkably reduced, and the detection stability is enhanced.

The invention relates to a multi-moving-target tracking method for a remote sensing video and a storage medium. The method comprises the following steps: firstly, establishing a plurality of detection subsequences based on multiple frames of images of an acquired remote sensing video, then respectively extracting a space-time fusion feature containing a static feature and a dynamic feature of each detection subsequence, and obtaining a detection frame of each frame of image based on the space-time fusion feature; then, according to the target library information of each frame, prediction states of multiple frames of images are obtained through Kalman filtering in sequence, and an optical flow matrix of two adjacent frames of images is calculated based on background feature points of the two adjacent frames of images; based on the optical flow matrix, the prediction state of each frame of image can be corrected and matched with the detection frame of each frame of image, and a first target library sequence composed of the target libraries of each frame of image is obtained. And finally, performing post-processing operation of interpolation reconstruction and static target elimination on the first target library sequence based on the optical flow matrix to obtain a second target library sequence. Therefore, the multi-moving-target tracking precision of the remote sensing video can be improved.

Embodiments are disclosed for performing universal segmentation to mask objects across multiple frames of a video. The method may include determining an image segmentation mask which masks an object of a frame of a video sequence using the frame and an image segmentation module of a segmentation system. The method further includes determining a mask propagation mask which masks the object of the frame of the video sequence using the frame, a representation of a previous frame of the video sequence, and a mask propagation module of the segmentation system. The method further includes determining a frame mask which masks the object of the frame of the video sequence based on a comparison of the image segmentation mask and the mask propagation mask. The method further includes displaying the frame mask of the video sequence.

The invention discloses a multi-frame photoacoustic image reconstruction method based on optical flow alignment and depth feature fusion. The method comprises the following steps: S1, obtaining photoacoustic signal data; s2, reconstructing a photoacoustic cross-sectional image; s3, performing optical flow calculation and image alignment; and S4, training the deep feature fusion network. According to the method, through optical flow motion correction and a potential space learning mechanism, space-time information and complementary features in the aligned multiple frames of images are dynamically integrated, complementary information in the multiple frames of images is adaptively fused, noise is suppressed, and finally reconstruction of high signal-to-noise ratio and high spatial resolution images of biological tissues is achieved. Experimental results show that the method can significantly improve image quality, recover image distortion and detail loss caused by motion and noise, and provide a new effective scheme for promoting robust clinical application of a photoacoustic imaging technology.

The invention relates to the technical field of intelligent retail terminals, solves the problem of low commodity replenishment accuracy in an unmanned vending cabinet in the prior art, and provides a retail terminal inventory replenishment method, device and system based on multi-modal data. The method comprises the following steps: decomposing real-time video data into multiple frames of real-time images according to the real-time video data of the unmanned vending cabinet in a commodity transaction scene; performing multi-modal feature extraction on the commodity region image to determine commodity feature information; performing human body feature extraction on the user area image in the historical commodity transaction scene, and updating user group feature information; inputting the user group feature information as incremental data into the commodity demand prediction initial model, and determining a commodity demand prediction target model; and inputting the commodity feature information into a commodity demand prediction target model, and screening out a target commodity from a preset commodity list according to a prediction result, and supplementing and putting the target commodity on a shelf. According to the invention, the replenishment accuracy of the unmanned vending cabinet can be improved.

Embodiments of the present invention provide a physiological state detection method and apparatus, an electronic device, a storage medium, and a program. The method comprises: acquiring a video stream collected by a photographing device; extracting multiple frames of face images of a target object from multiple frames of images in the video stream; determining at least one smooth area in the face images; performing weighting processing or area screening on the at least one smooth area on the basis of area attribute information, so as to obtain information to be extracted that is related to a physiological state; and performing physiological state information extraction on the information to be extracted, so as to obtain a physiological state detection result of the target object. According to the embodiments of the present invention, the physiological state detection is implemented on the basis of an imaging processing mode, real-time measurement can be performed anytime and anywhere, the practicability is better, and the accuracy of measurement can be improved by means of the constraint of preset conditions.

The invention provides a video coding method and device, electronic equipment, a chip and a medium, and relates to the field of video coding, and the method comprises the steps: determining a plurality of initial regions in each frame of picture for a plurality of frames of pictures in an original video; determining the change rate of each initial region based on the pixel points in the plurality of initial regions; determining at least one coding region and a coding strategy corresponding to each coding region based on the change rate; and performing video coding on each coding region by using the coding region corresponding to each coding region to obtain target data. According to the coding method provided by the invention, the change frequencies of different regions are identified, the regions needing to be coded are determined, and different coding modes are adopted according to the change frequencies of the coding regions, so that efficient and flexible dynamic regional coding is realized, the coding efficiency is improved, the calculation amount and the transmission amount are reduced, and the network bandwidth requirement is reduced.

The invention relates to an audio book video generation method and device, electronic equipment, a medium and a program product, and belongs to the technical field of computers. The audio book video generation method comprises the following steps: acquiring a multi-frame image corresponding to a story text, wherein the multi-frame image is used for representing a key plot of the story text; determining target audio data in the audio data corresponding to the story text; and generating an audio book video corresponding to the story text based on the target audio data and the multiple frames of images.

The invention discloses a method, a device, equipment and a medium for embedding a digital watermark in a video, and relates to the field of image processing, and the key points of the technical scheme are as follows: obtaining multiple frames of images of the video, converting a part of the image at any position in each frame of image into a YUV format, and extracting a brightness channel of the YUV format; dividing a brightness channel at any position of each frame of image into a plurality of N * N first image blocks, and performing discrete cosine transform on each first image block to obtain an N * N frequency domain coefficient matrix; coding a randomly generated digital watermark to obtain a binary coding sequence; wherein the digital watermark refers to a character string with identification information; and selecting a frequency domain coefficient pair from the frequency domain coefficient matrix, and embedding a binary coding sequence of a one-bit digital watermark in each image block based on the frequency domain coefficient pair, so that each frame of image of the video is embedded with the digital watermark. According to the invention, the problem of insufficient processing efficiency and robustness of a video watermarking algorithm provided by a related technology is solved.

The invention discloses a wall surface water seepage automatic detection method based on a visible light camera. The method comprises the following steps: acquiring a wall surface image through an optical lens; performing frame cutting operation on the wall surface image to obtain an RGB image of each frame of image of the wall surface image; a classification model is trained to classify the RGB images, and wall images with the water seepage risk are screened out according to the classification result; acquiring continuous multi-frame images of the wall surface image with the water seepage risk to form a time sequence image; extracting a change region of the time sequence image through a dynamic target perception model; if the change area is greater than a preset threshold value, determining that the wall surface image with the water seepage risk is a water seepage wall surface image; and performing reclassification on the water seepage wall surface image through the water seepage semantic segmentation model, generating a segmentation mask of the high-confidence water seepage area, and outputting the water seepage wall surface image covered with the mask. The method has the advantages that the wall surface water seepage in indoor and outdoor environments can be quickly, accurately and automatically detected without auxiliary equipment.

The invention relates to a laser radar camera calibration method and device, and a medium. The method comprises the steps: collecting multi-frame laser radar point cloud data and synchronous corresponding image data in a construction scene; carrying out multi-frame point cloud fusion and dense reconstruction to generate a laser dense point cloud; visual sparse point cloud reconstruction is carried out, and cross-modal scale unification and space alignment are carried out on an initial visual point cloud obtained through reconstruction and the laser dense point cloud; generating a visual dense point cloud through three-dimensional Gaussian splashing; and performing registration on the laser dense point cloud and the visual dense point cloud by adopting a point-to-line iterative nearest point algorithm, and performing calculation to obtain an external parameter calibration matrix of the camera and the laser radar. Compared with the prior art, the method has the advantages of high precision, low cost, high stability and the like.

The invention is suitable for the technical field of computers, and provides an image processing method and electronic device.The method comprises the steps that firstly, continuous multiple frames of images to be processed are input into an encoder of a preset image processing model, and a first feature map is obtained; inputting one frame in the multiple frames of images to be processed into a preset visual large model to obtain a second feature map containing advanced semantic information; splicing the first feature map and the second feature map to obtain a third feature map; and finally, inputting the third feature map into a decoder of an image processing model to obtain a target image. Therefore, the image processing model is guided to better complete the image processing task through the advanced semantic information extracted by the visual large model, and the image processing effect is further optimized.

A no-reference video assessment framework employs a multi-resolution input representation and a patch sampling mechanism on a video having multiple frames 302 to aggregate information across different granularities in spatial and temporal dimensions. The framework effectively models complex spacetime distortions that occur in user generated content-type videos. According to one aspect, the framework embeds video clips 302 as multi-resolution patch tokens using complementary modules. This includes a multi-resolution video embedding module 322, and a space-time factorized Transformer encoding module 324, 326. The multi-resolution video embedding module 322 is configured to encode multi-scale quality information in the video, capturing both global video composition from lower resolution frame and local details from larger resolution frames. The space-time factorized Transformer encoding module 324, 326 aggregates the spatial and temporal quality from the multi-scale embedding input, and is configured to output a quality score 330 for the input video.

The invention discloses a recognition method, device and system for putting food materials in two hands and a storage medium, and belongs to the technical field of household appliances. The method comprises the following steps: acquiring multiple frames of first images; performing hand and food material detection and recognition on the multiple frames of first images to obtain hand and food material detection and recognition results corresponding to the first images in the multiple frames of first images; according to the hand and food material detection and recognition results corresponding to the first images in the multiple frames of first images, tracking the two-hand actions of the user, and determining whether the action of at least one hand in the two-hand actions of the user is food material putting or not; and under the condition that at least one of the actions of the two hands of the user is to put the food materials, determining a target shelf area in which the two hands put the food materials on the basis of a target image of a bounding box in which the hand and food material detection and recognition result in the multi-frame first image comprises the food material taking by the hand. By detecting the hands and the food materials and tracking the actions of the two hands of the user, accurate recognition of the food materials put into the two hands is achieved.

A frame apparatus, a kit of parts which includes multiple frames and a connector bracket for connecting the frames together, and a method of interconnecting a plurality of frames and hanging the same from a support surface. The frame apparatus may be a front-loading frame whereby display items are inserted into a display cavity of the frame through an opening in the front surface of the frame through which the display cavity is viewed. The frame may include an outer annular wall that defines the display cavity, an inner annular wall that is spaced apart from the outer annular wall, and a floor that extends between the inner and outer annular walls. The floor may comprise a plurality of apertures to allow for attachment of the frame to various accessories including hanging brackets, connector brackets, trays, and the like.

The invention relates to the technical field of medical image processing, in particular to an endoscopic surgery video real-time structure analysis method and system, and the method comprises the steps: carrying out the frame-by-frame semantic segmentation of real-time video data, and generating a segmentation mask of each frame of image; calculating a comprehensive quality score of the target frame based on the segmentation masks of the target frame and the previous frame of the target frame; analyzing a motion amount index between adjacent frames; generating the current length of a sliding time sequence window according to the comprehensive quality score and the exercise amount index, and fusing multiple frames of segmentation masks in the sliding time sequence window to generate a reference mask; extracting a key point from the reference mask, and obtaining a displacement vector of the key point from a previous frame of the target frame to the target frame; generating a pixel-level displacement field according to the displacement vector, deforming the segmentation mask of the previous frame of the target frame to the target frame, and generating a prediction mask of the target frame; and performing superposition display on the prediction mask and the image of the target frame. According to the scheme, the time sequence consistency and stability of the video semantic segmentation result can be enhanced.

The invention relates to a video generation method based on time sequence similarity, and is applied to the field of video generation. Specifically, the video generation method based on the time sequence similarity comprises the following steps: acquiring generated video information; generating a key video frame sequence with frame rate information based on the text information, wherein the key video sequence is separated by a plurality of frame marks; performing recursive interpolation processing on the key video frame sequence, fusing front and back key frame features through a preset attention mechanism, and generating an initial intermediate frame between adjacent key frames; extracting visual features of a plurality of key frames and intermediate frames included in the key video frame sequence, calculating cosine similarity of the visual features of adjacent frames, and adjusting intermediate frame generation parameters based on the similarity to optimize inter-frame coherence so as to obtain an optimized intermediate frame; and combining the key video frame sequence with the optimized middle frame to generate a complete video clip which is consistent with the text information and has a coherent inter-frame time sequence.

The invention discloses a high-precision registration method for multi-view point clouds of welding workpieces, which is characterized by comprising the following steps of: firstly, carrying out spot welding on welding grooves of two workpieces to obtain a to-be-welded workpiece; a structured light camera is used for collecting multiple frames of original point clouds of a to-be-welded workpiece at different visual angles, background point clouds are removed, and multiple frames of workpiece point clouds at different visual angles are obtained; then extracting the point cloud of the upper surface of the workpiece containing the welding groove, and performing coarse registration on the point cloud of the upper surface of each frame of the workpiece; the mass weight of each point in the point cloud of the upper surface of the workpiece is calculated, then the point clouds of adjacent frames are subjected to precise registration through a weighted ICP algorithm to optimize the poses of the adjacent frames, precise splicing of the point clouds of the upper surface of the workpiece at multiple frames of different view angles is achieved, and the complete point cloud of the upper surface of the workpiece containing the welding groove is obtained; the method has the advantages that the influence of point cloud distortion on point cloud precise registration is well reduced, and the precision of point cloud registration is improved, so that the precision of subsequent three-dimensional model reconstruction and the precision of automatic welding are ensured.

The invention provides a display method and device.According to the method, modal information of a target structure under a preset working condition is obtained, the modal information is used for representing deformation characteristics of the target structure under the preset working condition, and animation data of the target structure under the preset working condition are generated and displayed based on the modal information and target data; the animation data comprises multiple frames of images, each frame of image comprises a deformation state of a target structure at a corresponding moment, the target data comprises a predetermined change trend of a scaling factor and / or a specified scaling factor, and the predetermined change trend comprises a predetermined corresponding relationship between the scaling factor and the moment; the change rate of the scaling factor at each moment is less than or equal to a predetermined change rate, and the specified scaling factor is determined by responding to an input operation of the scaling factor of the specified component in the target structure. According to the display method, the modal information can be clearly and effectively displayed.

The invention discloses an ultrasonic image analysis method and an ultrasonic imaging system. The method comprises the following steps: acquiring multiple frames of ultrasonic images of the heart of a target object; automatically determining a myocardial contour of the multi-frame ultrasonic image; at least determining the image quality of the myocardial contour of the multi-frame ultrasonic image; determining a modification priority level of a myocardial contour region of each multi-frame ultrasonic image based on the image quality; and displaying at least one frame of ultrasonic image in the multiple frames of ultrasonic images and the corresponding identification information for identifying the modification priority. According to the ultrasonic image analysis method and the ultrasonic imaging system provided by the invention, the modification priority level of the ultrasonic image is determined, and the ultrasonic image and the corresponding identification information for identifying the modification priority level are displayed, so that the visual prompt for recommending the preferential modification frame is realized, and the operation and use efficiency of a doctor is optimized.

The invention discloses a tomato raw material loading, unloading and sorting method and system fused with AI visual recognition, and relates to the technical field of AI vision. A tomato raw material loading, unloading and sorting method fused with AI visual identification comprises the following steps that multiple frames of images are collected, qualified images are reserved through quality detection, the qualified frames are subjected to pixel-level segmentation, tomato segmentation masks are generated through multi-frame fusion, and blind areas are complemented; based on the complemented segmentation mask, high residual target points are judged, space attributes are extracted, the optimal moving path and action queue of the crane pipe are obtained, and a dynamic complementing and scanning queue is inserted to be issued and executed; and in the execution process, residual changes are monitored, the flushing effect is judged, dynamic recognition, complementary scanning and queue updating are conducted, parameters are adjusted, and sorting is conducted till discharging is completed. Accurate recognition, efficient path planning and dynamic supplementary scanning in the tomato loading, unloading and sorting process are achieved, and then the problems that in the prior art, due to insufficient recognition precision, path planning is unreasonable, and residual areas are missed in scanning are effectively solved.

The invention discloses a sports equipment management personnel identification method, system and equipment, and the method comprises the steps: starting and initializing a camera through detecting a sports equipment use trigger signal, and stopping automatic focusing; and shooting multiple frames of images at different focal lengths according to a preset interval, determining a clear area by using a gradient magnitude algorithm, and performing image registration and fusion to form a composite image. And if the whole area is not covered, shooting and splicing are carried out again. And through composite image splicing, distortion cutting, noise reduction and normalization processing, a final image is output for determining the identity of a person. According to the invention, through multi-frame shooting and accurate image processing, a high-quality image is obtained, and information limitation and quality defects of a single image are effectively avoided. Various algorithms are fused to ensure that the image is clear, complete and standardized, the accuracy and reliability of personnel identity recognition are remarkably improved, an accurate image basis is provided for sports equipment management, the normalization and safety of equipment use are guaranteed, meanwhile, the image collecting and processing efficiency is improved, and the management cost is reduced.

The invention discloses a sound feature-based recording denoising method and system, electronic equipment and a storage medium, and relates to the field of recording processing. In the method, a to-be-denoised record is divided into multiple frames, the short-time energy and the short-time zero-crossing rate of each frame are calculated, and each frame is an audio signal with a preset time length; dividing the recording to be denoised into a voice segment and a voice-free segment according to the short-time energy and the short-time zero-crossing rate; determining frequency spectrum characteristics of the voice-free segment, and determining noise characteristics according to the frequency spectrum characteristics through a preset statistical model; and de-noising the voice segment according to the noise characteristics. By implementing the technical scheme provided by the invention, the effects of effectively reducing noise interference and improving the recording quality are achieved.

The invention discloses a steam pipeline leakage detection method and device based on high-definition infrared, a storage medium and computer equipment. The method comprises the steps that a high-definition infrared dual-mode video corresponding to a to-be-detected steam pipeline is acquired; determining multiple frames of target high-definition images from the high-definition infrared dual-mode video, inputting the multiple frames of target high-definition images into a preset leakage detection model, and determining a first leakage area according to a detection result; determining multiple frames of target infrared images from the high-definition infrared dual-mode video, constructing a target background image based on a first frame in the multiple frames of target infrared images, and determining a second leakage area according to the target background image and other frames in the multiple frames of target infrared images; and performing registration processing on the first leakage area and the second leakage area of the to-be-detected steam pipeline, and determining a target leakage area corresponding to the to-be-detected steam pipeline according to a registered overlapping area.

The invention discloses a method for detecting juggling times in football training and a computer readable storage medium. The method comprises the following steps: step 1, acquiring a juggling training video; 2, intercepting a juggling training video into multiple frames of images, and sequentially inputting the multiple frames of images into the trained football juggling key point detection network to obtain human skeleton point location information and football point location information in each frame of image; 3, based on the human skeleton point location information and the football point location information in the image, judging whether a juggling condition is met or not according to the relevance between the football point location and the human skeleton point location in the juggling process, and recording juggling once if the juggling condition is met; 4, the images are traversed in sequence, and the juggling times of football training are obtained. According to the football training method and device, the needed football training video is collected through the user equipment with the camera shooting function, the football training juggling times of the football trainee can be accurately detected through subsequent processing, and the mode that in the existing football training process, a coach or co-trainee observes and counts all the time is changed.

The invention discloses a target screening method and system, a vehicle and equipment. The target screening method comprises the steps that continuous multiple frames of historical data are acquired, and the multiple frames of historical data comprise multiple frames of steering wheel angle information and multiple frames of yaw rate information; according to the multi-frame steering wheel angle information and the multi-frame yaw rate information, whether the vehicle runs on a target road or not is judged, and the target road at least comprises a lane-line-free road or a lane-line-poor-quality road, a curve or a continuous curve; if yes, predicting a driving track of the vehicle according to the current speed and acceleration of the vehicle and the multi-frame historical data; and performing target screening according to the driving track. By the adoption of the method and device, when it can be accurately judged that the vehicle is located on the target road such as a complex curve, a continuous turning road and a lane-line-free road, the vehicle data are effectively utilized, and the more accurate driving track of the vehicle is predicted.