50 results about "Video stitching" patented technology

The invention relates to the technical field of digital image processing and computer vision, and discloses a remote multi-view video stitching and monitoring method and system based on digital twinning, and the method comprises the steps: constructing a digital twinning model containing geometric, material and semantic information, and calibrating and initially registering a multi-view camera; based on the model and camera parameters, collecting a preprocessed video stream, and refining the camera pose in combination with the model; predicting expected visual content by using the model and the refined pose, and performing non-rigid alignment on the preprocessed video frame; based on the aligned video frames, a model semantic optimization splicing suture line is utilized to generate a reconstructed video, and information loss is repaired in combination with a model context; and finally, performing integrated monitoring interaction on the repaired reconstructed video and the digital twin model, comparing and detecting abnormality, and updating the model by using the reconstructed video. According to the invention, the problems of traditional remote monitoring in the aspects of scene comprehensive perception, intelligent anomaly detection and synchronism of environment digital representation and physical reality are solved.

The invention discloses a video processing method and device, equipment and a medium. The method comprises the following steps: acquiring a plurality of initial videos collected by a plurality of cameras; performing picture feature extraction based on the plurality of initial videos to obtain a plurality of static features and a plurality of dynamic features; performing feature fusion on the plurality of static features and the plurality of dynamic features to obtain an interested image, the interested image being used for representing that the initial videos collected by the at least two cameras comprise images of the same area; and based on the interested image, performing video stitching on the plurality of initial videos to obtain a panoramic video. According to the embodiment of the invention, a panoramic image of a blind area can be provided for a vehicle owner in real time, the possibility of an accident is reduced, and a clear video image can be conveniently provided after the accident occurs.

1. Name of the product in this design: Visible light splicing monitoring equipment. 2. Purpose of this design: To use multi-channel video stitching for wide-angle observation of a scene. 3. The key design features of this product are its overall shape. 4. The image or photograph that best illustrates the design's key points: a 3D model.

A video coding mechanism for view-dependent video coding is disclosed. The mechanism includes receiving a spherical video signal spliced from a multi-directional video stream. The spherical video signal is mapped into a plurality of sub-picture video signals, each of which includes a sequence of sub-pictures. The plurality of sub-picture video signals are coded into a plurality of sub-picture bitstreams such that, when decoded in a decoder, each pixel in each sub-picture has a value equal to a corresponding pixel in a whole picture composed of the sub-pictures after decoding. The plurality of sub-picture bitstreams form a plurality of sub-picture tracks, and it is indicated that the sub-picture tracks conform to a specific video profile. The sub-picture bitstreams are sent to a decoder to support decoding and displaying a virtual reality video view.

This application discloses a panoramic stitching method, apparatus, device, and storage medium based on multi-camera systems, relating to the field of image processing technology. The method includes: acquiring calibration images collected by multiple cameras, wherein the calibration images include common calibration areas of adjacent cameras; identifying calibration board corner features in the calibration images and obtaining calibration parameters for each camera based on these features; generating a configuration file according to the calibration parameters; and processing the video streams collected by the multiple cameras based on the configuration file to obtain a panoramic video stream. This method solves the problems of low calibration accuracy and reliance on manual experience and complex online calculations in existing technologies under long-distance, large field-of-view conditions. It achieves standardization and automation of the calibration process and enables efficient, high-precision real-time panoramic video stitching on embedded devices, reducing the system's dependence on high-performance processing platforms and overall cost.

The embodiment of the invention provides a bucket wheel machine unattended system and method based on video stitching, and the system obtains the global high-precision visual information of a bucket wheel machine operation area and an accurate material pile semantic segmentation mask image through the panoramic image stitching and image recognition of the original video streams of a plurality of cameras. Meanwhile, the external parameters of the dynamic camera are solved in real time by combining with the PLC pose data of the bucket wheel machine, the two-dimensional semantic segmentation mask graph and the synchronized laser radar point cloud are efficiently fused, the material pile edge features are accurately mapped to the three-dimensional space, the high-precision three-dimensional material pile edge point cloud is obtained, and therefore the defects of the laser radar in semantic recognition are overcome. And finally, based on the three-dimensional material pile edge point cloud updated in real time and the current pose data of the bucket wheel machine, the system can intelligently carry out operation path planning, the operation path planning is decomposed into PLC control instructions, and autonomous, safe and accurate operation of the bucket wheel machine in the complex and changeable material pile environment is achieved.

The invention relates to a marine unstructured camera video stitching method, which comprises the following steps: S1, acquiring video stream data of a shipborne camera, the video stream data being initial data required for calculating stitching parameters; s2, the initial data obtained in the step 1 are processed, splicing mapping parameters are obtained, and the splicing mapping parameters comprise cylindrical projection mapping parameters, homography matrixes between adjacent cameras, self exposure compensation parameters and optimal suture lines; splicing mapping parameters are stored in a file form, and the parameters are loaded to a memory in a GPU mapping table form during subsequent splicing; and S3, on the basis of the splicing mapping parameters obtained in the step S2, carrying out online splicing on the video images. According to the method, the problem that the ship camera array is difficult to calibrate is solved, a more stable splicing effect is achieved in different illumination scenes, and compared with a traditional video splicing method, the method is higher in dynamic scene adaptability.

A kind of distributed video splicing device, it is related to video splicing technical field, including with several local input modules of external image device connection, with the management module of several local input modules connection, with the output module of management module connection, with the network streaming media input module of management module connection, output module is connected with external display device, local input module includes with the input interface of external image device connection, with the input conversion chip of input interface electrical connection, with the input FPGA of input conversion chip electrical connection, input FPGA is electrically connected with management module, input conversion chip is used to output RGB signal to input FPGA.The technical scheme provided by the utility model aims to realize integrated design, and can solve the technical problem of network streaming media data processing.

Disclosed herein are an apparatus and method for 360-degree video stitching. The apparatus for 360-degree video stitching includes memory for storing at least one program, and a processor for executing the program, wherein the program is configured to stitch features of multiple input images based on at least one parameter included in a 360-degree stitching function description template, and then creating a single 360-degree video, the 360-degree stitching function description template includes a configuration parameter that is an array of function parameters, the configuration parameter includes a stitching parameter, a camera parameter, a feature parameter, and a projection parameter, the feature parameter includes a method for extracting respective features from multiple input images, and the projection parameter includes a projection type that is a kind of a projection plane onto which the multiple input images are projected.

The present invention provides a video splicing method and system based on object tracking, which relate to the technical field of video splicing. The method and system include the following steps: obtaining a video file to be processed, converting the video file to be processed into a frame sequence with a timestamp through a decoder, calculating feature differences and motion vectors based on a key frame recognition algorithm, and determining feature frames in the frame sequence; performing grayscale conversion on the feature frames to generate grayscale frames and spectrograms corresponding to the grayscale frames, removing image noise in the spectrogram and performing color correction to obtain a standard image; tracking an object in the standard image through an optical flow tracking algorithm based on the standard image to generate an image analysis result; determining a Hessian matrix corresponding to each pixel point in the standard image based on the image analysis result, constructing a scale space based on the Hessian matrix, determining key points and generating feature descriptors, performing image matching based on the feature descriptors, selecting an optimal matching pair, and performing image splicing based on an image stitching algorithm to obtain a spliced image.

The invention provides a video stitching method, system and related equipment, which are applied to the technical field of data processing, and the video stitching method comprises the following steps: obtaining multiple paths of video streams input by monitoring equipment, and decoding the multiple paths of video streams to obtain multiple paths of decoded video data of the multiple paths of video streams; performing feature extraction on the multi-channel decoded video data through a neural network processor to obtain multi-channel video feature information of the multi-channel video streams; performing feature matching on the multi-channel video feature information through a neural network processor to obtain a multi-channel feature matching result of the multi-channel video streams; when the multi-channel video feature information is subjected to feature matching to obtain a multi-channel feature matching result of the multi-channel video stream, removing mismatching points in the multi-channel feature matching result in parallel; and through a neural network processor, aligning the multiple paths of video frames according to the effective feature matching points in the multiple paths of feature matching results, and generating target video stitching data. The video stitching efficiency and the resource utilization rate can be improved.

The invention discloses a time-space consistency video stitching method and device, and relates to the technical field of video stitching. The method comprises the step of realizing high-precision video stitching through dual-channel feature extraction and spatio-temporal joint optimization. The method comprises the following steps: firstly, respectively extracting shallow layer and deep layer features of two paths of video sequences by adopting a StarNet-s050 model; constructing a space distortion module comprising a context correlation layer, RegressNet1 and RegressNet2 to generate a space distortion matrix before optimization, and obtaining a final space distortion matrix through an auxiliary training head; a time sequence distortion module is used for extracting space-time dynamic features, and space-time smooth increment is calculated in combination with smooth constraints; and finally, inputting the corrected space-time distortion matrix and an original video into a splicing module to generate a fusion sequence. According to the method, the problems of deformation difference of a multi-view video in a space dimension and fuzziness on a time axis are effectively solved, and the video stitching quality is remarkably improved through hierarchical feature fusion and space-time consistency modeling.

According to embodiments of the present disclosure, methods and apparatuses for remote assistance are provided. The method includes presenting an assistance interface associated with an autonomous vehicle; and presenting, in the assistance interface, a multi-path video stream corresponding to a plurality of viewing perspectives of the autonomous vehicle based on video data received from the autonomous vehicle, wherein the multi-path video stream includes a first video stream corresponding to a forward viewing perspective and a second video stream corresponding to a rearward viewing perspective, the first video stream and the second video stream are generated based on a video stitching model associated with the autonomous vehicle, the video stitching model is constructed based on a plurality of images captured by a plurality of cameras deployed on the autonomous vehicle. In this way, embodiments of the present disclosure can improve the reliability of remote assistance, thereby improving the driving safety of the autonomous vehicle.

The invention relates to the technical field of computer vision, and discloses a multi-camera video stitching method based on regionalized symmetric weighting. The method comprises the following steps: realizing multi-camera frame-level synchronous acquisition (time sequence jitter is less than or equal to 10ms) through an event-driven multi-thread mechanism; obtaining distortion parameters (k1, k2 and k3) by adopting a Zhang Zhengyou calibration method, and correcting the image in real time according to a nonlinear model; dynamically constructing a fusion region: firstly expanding pixels of an overlapping region We belonging to [100, 200] to compensate a registration error, then generating an optimal suture line through a graph cutting method, forming a suture line region through morphological expansion, and finally dividing the optimal suture line region into a suture line region and a transition region; during partition fusion, an image source with the minimum pixel difference is directly selected in a suture line area to eliminate ghosts, and a dynamic boundary weight strategy is adopted in a transition area to achieve seamless transition. Finally, two fusion problems of ghosting elimination and splicing seam elimination are realized based on the two, image transition becomes smoother and more natural, and the method is suitable for panoramic security and protection monitoring and the like in industrial complex scenes such as wind power and the like.

The application discloses a kind of multi-view video splicing methods based on deep learning, steps are as follows: first, using Airsim simulator is collected at the image and depth data of set virtual public viewpoint, generates the dataset for video splicing task, and the image is cylindrical projection and so on Preprocessing.Then, using convolutional neural network designs artifact elimination module and smooth transition module respectively, the former considers the feature correlation of overlapping area, and the overlapping area is aligned by viewpoint regression to eliminate the artifact after fusion;The latter according to the feature information of image, the deformation rule obtained in the overlapping area is propagated to the non-overlapping area, to guide the smooth transition between regions to improve visual perception.Finally, according to the predicted displacement field, the original viewpoint image is distorted and transformed, and the splicing result is obtained by weighted linear fusion.The application can achieve real-time splicing performance while removing splicing artifacts, and can meet the online splicing needs in practical applications.

The present invention discloses an FPGA-based vehicle-mounted video image stitching method and system. The system utilizes a cross-temporal processing module, an input frame storage module, a storage controller, an output frame storage module, an output buffer unit, a video stitching module, an output timing generation module, and a windowing processing module. The output buffer unit is used to buffer image data retrieved by the output frame storage module to obtain a first image and a second image to be stitched together; the output timing generation module is used to generate a corresponding timing signal based on the resolution parameters of a third image; the windowing processing module is used to generate effective window signals for the corresponding images based on the resolution parameters of the first image, the resolution parameters of the second image, and the timing signal; and the video stitching module is used to stitch the first image and the second image together based on the effective window signal to form a third image, and output the third image to a display screen. The present invention provides efficient, convenient, and real-time video processing and intuitive preview functions.

The present application provides a video stitching method, system and computing device based on digital twin scenes. Among them, a set of video clips to be stitched is obtained; according to the real scene coordinates of the multiple video clips, the multiple video clips are mapped into a virtual scene to construct a spatial layout; according to the timestamps of the multiple video clips, the initial video sequence is obtained, and the initial video sequence is mapped into the virtual scene to construct a temporal layout; based on the spatial layout and the temporal layout, a spatiotemporal layout is constructed, and in the spatiotemporal layout, the visual features and scene semantic tone between the multiple video clips are identified, and based on the visual features and scene semantic tone between the multiple video clips, the perspectives and positions of the multiple video clips are adjusted to generate video clip adjustment results; based on the video clip adjustment results, the multiple video clips are stitched to generate a digital twin display video. The technical solution provided by the present application improves the video stitching effect.

The invention discloses a parallel video stitching method based on multi-band fusion, which comprises the following steps of: reading a plurality of video files in parallel, aligning timestamps and unifying the sizes of image frames to obtain an image frame sequence corresponding to the plurality of video files, and storing the image frame sequence into a cache pool; reading each image frame sequence, judging whether the obtained image frame is an initial frame or not, if so, extracting image features for feature matching, estimating camera parameters and taking as a registration template, and otherwise, entering the next step; the processing thread multiplexes the template to process subsequent image frames in parallel, and a splicing result of the image frames at the same moment in the multiple video files is obtained; splicing results of all the image frames are synthesized according to the time sequence, and a final video is obtained. According to the method, the real-time requirement of the video can be met while the video splicing effect is ensured.

This invention provides a vehicle trajectory extraction method and related equipment based on video stitching, comprising: Step 1, acquiring multiple traffic video segments within a target traffic area; Step 2, detecting target vehicles in each traffic video segment to obtain multiple detection results, and tracking the target vehicle in each detection result to obtain the trajectory coordinates of the target vehicle in each traffic video segment; Step 3, extracting the trajectory of the target vehicle based on the trajectory coordinates in each traffic video segment to obtain the driving trajectory of the target vehicle in each traffic video segment; Step 4, matching and stitching the driving trajectory in the current traffic video segment with the driving trajectory in the current traffic video segment to obtain the trajectory stitching result of the target vehicle during its driving process. Compared with the prior art, this method improves the accuracy and stability of trajectory extraction and has good scalability.

A video stitching system combines video from different cameras to form a panoramic video that, in various embodiments, is temporally stable and tolerant to strong parallax. In an embodiment, the system provides a smooth spatial interpolation that can be used to connect the input video images. In an embodiment, the system applies an interpolation layer to slices of the overlapping video sources, and the network learns a dense flow field to smoothly align the input videos with spatial interpolation. Various embodiments are applicable to areas such as virtual reality, immersive telepresence, autonomous driving, and video surveillance.

The embodiment of the invention discloses a video stitching method and device, electronic equipment and a computer readable storage medium, and relates to the technical field of video processing. The method comprises the following steps: acquiring real-time state parameters of a plurality of cameras; determining a target camera and a visual angle parameter of the target camera by taking minimization of a splicing error and processing time delay as a target under the condition that the constraint of the real-time state parameters of the plurality of cameras is satisfied; based on the target cameras and the visual angle parameters of the target cameras, optimizing the pose parameters of the plurality of target cameras; and according to the optimized pose parameters, splicing the videos collected by the plurality of target cameras. Therefore, according to the scheme, video stitching can be performed dynamically in real time and with high quality on the basis of considering the isomerism of the cameras.

The invention relates to a multi-dimensional video content intelligent editing method and device, equipment and a medium. The method comprises the following steps: extracting multi-dimensional video features including visual features, audio features, semantic features and motion trail features according to a multi-camera video stream; fusing the multi-dimensional video features to obtain a fused feature vector; classifying the video frames based on the fusion feature vector to generate a scene label sequence; reasoning and generating an editing decision sequence according to the scene label sequence through a decision tree reasoning engine; positioning a lens switching point according to the editing decision sequence to obtain an editing time point set; and splicing the multi-camera video stream based on the set to generate a target edited video. By adopting the method, the problems of one-sided editing decision and poor scene adaptability in the prior art can be solved, the content integrity and the scene adaptability of multi-camera video editing are improved, and the high-quality presentation requirement is met.

This application discloses a video stitching method, apparatus, electronic device, and storage medium for multi-camera surveillance, aiming to solve the problems of poor regional adaptability, inaccurate feature matching, lack of multi-dimensional synchronization, single parameter tuning mechanism, and insufficient balance between data storage and security in the prior art, and to achieve high-precision, seamless, and adaptive panoramic stitching of large-scale multi-camera surveillance videos.

The present disclosure relates to the technical field of image processing, and provides a video splicing method, device, equipment, medium and program product. The video splicing method comprises: acquiring source video frames; performing correction preprocessing on each source video frame to obtain a corrected video frame and a corrected video frame group; sequentially acquiring an overlapping area of a first corrected video frame and a second corrected video frame of each corrected video frame group; acquiring an optical flow of the overlapping area according to a deep learning model; sequentially acquiring a non-overlapping area of the first corrected video frame and the second corrected video frame of each corrected video frame group; completing the optical flow of the non-overlapping area to obtain an overall optical flow; sequentially mapping the first corrected video frame in each corrected video frame group according to the overall optical flow to obtain a mapped video frame; and splicing the first corrected video frame and the mapped video frame in each corrected video frame group to obtain a spliced video frame. The video splicing method can improve the image splicing quality.

The present invention discloses a multi-view surveillance video stitching method and system based on energy graph estimation, comprising obtaining video data and camera positions of multiple surveillance cameras on a road section to be stitched; extracting video frame features of each camera video, dividing pixels in the video frame into background pixels or foreground pixels, and matching background pixels; using a multi-layer RANSAC method to perform visual depth stratification on the video frames; performing layer-by-layer local matching, layer-by-layer stitching, and stitching layer fusion on video frames with overlapping areas acquired at the same time by cameras at two different locations; stitching the video frames captured by all cameras to complete the stitching of multi-view surveillance videos and obtain a panoramic video. The present invention has the characteristics of low computational complexity, high computational speed, and good stitching effect, maintaining a balance between algorithm efficiency and stitching accuracy, and providing a highly efficient and robust method for the field of surveillance video stitching.

The embodiments of the present invention relate to the field of video processing and disclose a method, device, electronic device and storage medium for video stitching in dynamic scenes. The method includes determining a first-frame registration image from each frame of images to be stitched extracted from a video stream from a multi-camera, using the transformation matrix used by the first-frame registration image in the registration process as the initial transformation matrix, and its stitching line as the initial stitching line. An initial background model is established based on the first-frame registration image. For subsequent frames to be stitched, when the background model detects that the current video frame image contains a moving object, the transformation matrix is ​​updated based on the current frame to be stitched to re-register and determine a new stitching line, and the background model is updated. Otherwise, the transformation matrix, background model and stitching line of the previous frame are maintained unchanged, and real-time fusion is performed based on the stitching line of each frame to be stitched to obtain a stitched video. The method meets the stability and real-time requirements of panoramic video stitching of mobile unmanned carriers.

The invention discloses an embedded real-time video stitching method based on dynamic suture line optimization and time domain smoothing. The method comprises the following steps: performing multi-thread synchronous acquisition and preprocessing on left and right video streams; extracting features on the key frame and obtaining an initial homography matrix, smoothing the time domain of the homography matrix, and multiplexing or restricting updating when the matching quality is insufficient to suppress picture jitter; constructing an energy diagram in the overlapped region ROI (region of interest), searching an optimal vertical suture line with the minimum accumulated cost from top to bottom by utilizing dynamic programming, and reducing dynamic ghosting; a hard mask and a soft mask are generated in a suture line neighborhood and are respectively used for a high-frequency layer and a low-frequency layer for multi-band fusion, high-gradient side forced retention is performed on a position where a pixel difference exceeds a threshold value in a mixed band, and finally, a Laplacian pyramid is only constructed near an overlapping region, and memory copying is performed in a non-overlapping region. The real-time performance and the splicing visual quality can be considered.

The invention discloses a video stitching method and device based on optical flow interpolation. The method comprises the following steps: projecting a received multi-view video frame to a public cylindrical coordinate system to obtain a projection image under each view; for overlapped areas of the projection images under two adjacent visual angles, calculating bidirectional optical flow by using the optical flow estimation sub-network and then performing zooming, and performing optical flow interpolation on the two overlapped areas based on the zoomed optical flow to obtain a plurality of slice distorted frames; generating two refined optical flows and a visibility graph by using an optical flow refining sub-network based on the slice distorted frame and the scaled optical flow; calculating a fusion interpolation slice based on the refined optical flow and the visibility graph to generate a fusion image and cover the overlapping region to obtain a spliced video frame; and designing a composite loss function based on unsupervised learning to carry out network training. According to the method, ghosting and fracture artifacts at the video splicing boundary can be effectively eliminated, a high-quality panoramic video with time-space coherence is obtained, and the method is particularly suitable for wide-baseline camera deployment scenes such as automatic driving and security monitoring.

The present invention discloses a method for surveying and mapping water depth in a nearshore sea area based on dual-UAV video splicing. The method comprises the following steps: completing the calibration of the internal parameters of the cameras of the two UAVs; the cameras carried by the two UAVs face the sea and are distributed along the coastline, shooting videos with a spacing maintained to ensure that the camera fields of view have an intersecting part, and recording the motion characteristics of the waves by shooting videos with optical cameras; then, using the video splicing technology, the videos shot by the two UAVs are spliced; an orthophoto image of each frame is obtained based on the position and attitude information of the UAV cameras; a straight line is fixed in a direction perpendicular to the coastline as a research area, and a time stack diagram of orthophoto corrected images of image key frames of the shot video at the position of the fixed straight line is obtained; and finally, the water depth of the nearshore sea area is obtained by using a cBathy water depth estimation method.

The application discloses a kind of camera equipment parameter-independent fast multi-view fish-eye image and video splicing method, comprising the following steps: S1, the fish-eye image of fish-eye camera shooting is preprocessed, the pre-processing includes image correction and inter-lens parallax optimization;S2, the image after pre-processing is registered using the method based on grid transformation;S3, image registration is optimized;S4, dynamic video splicing is carried out, and panoramic image and video are obtained.The application has lower computational complexity, can quickly capture the scene information around camera, can effectively improve the accuracy, adaptability and computational efficiency of image and video splicing, is conducive to being combined with computer vision and computer graphics and other computer tasks;The application method has wide application range and strong robustness, can still realize high-precision panoramic splicing quality in different types of natural scenes, and can be applied to related computer applications with high requirements for panoramic image and video quality.