1624 results about "Panorama" patented technology

The invention discloses a historical block scene three-dimensional reconstruction method and system based on Gaussian sputtering, and the method comprises the steps: collecting a historical block video sequence through a lightweight panorama camera, extracting a multi-frame panorama, and generating an image data set through a projection converter; monocular depth and normal estimation is carried out through a pre-training visual model, and a prior depth and normal graph data set of a historical block scene is constructed; sparse reconstruction is carried out on the multi-view image data set based on the SfM technology, initial point cloud and camera pose information are acquired, and a Gaussian ellipsoid is optimized in combination with prior depth and normal information; dynamically calculating the geometric width estimation value of the street, and guiding and adjusting the adaptive density of the Gaussian ellipsoids of the vertical surfaces on the two sides; rendering the optimized Gaussian ellipsoid through an improved rasterization renderer; and designing a multi-modal loss function and a regularization mechanism to optimize reconstruction and rendering results. According to the method, high-fidelity three-dimensional reconstruction of the historical block scene is realized, and the adaptability of the Gaussian sputtering method to the complex block scene is enhanced.

The invention discloses an integrated Beidou monitoring machine system integrating panoramic photographing and machine vision deformation monitoring, and relates to the technical field of safety monitoring. The system comprises a hardware structure unit and a software function unit, the hardware structure unit comprises a Beidou positioning module, an inertial navigation compensation module, a panoramic vision acquisition module, a machine vision processing module, a multi-mode communication transmission module and a power management module; the software function unit comprises a multi-source data fusion engine, a panoramic three-dimensional modeling sub-module, an intelligent early warning decision module and a cloud collaborative resolving interface. According to the invention, through real-time fusion of Beidou positioning data and panoramic vision imaging, an improved dense optical flow method is adopted to track local crack propagation, and global displacement monitoring of Beidou is combined, so that cross-scale synchronous sensing from macroscopic displacement to microscopic deformation is realized, and the comprehensive monitoring precision is improved.

Disclosed is a method for constructing a bionic binocular active visual simultaneous localization and mapping (SLAM) system. The method includes: S1, constructing a binocular active visual system, peripheral vision is simulated using a panoramic camera, a panoramic value map is constructed based on the panoramic camera, and a binocular bionic eye gaze control strategy based on the panoramic value map is proposed; S2, designing a SLAM algorithm framework which is suitable for motion of the two bionic eyes, where relative pose optimization of left and right cameras based on a Perspective-n-Point algorithm and depth calculation for binocular matching points based on triangulation are adopted in a SLAM tracking thread; and S3, with the assistance of camera poses estimated by the SLAM system and sparse landmark point coordinates, training a self-supervised depth estimation network, to provide dense depth estimation for a mapping module of the SLAM system, achieving dense mapping.

The invention provides a building construction monitoring method, which comprises the steps of obtaining multi-view video image data of a construction site, and performing fusion processing on the multi-view video image data by adopting an image splicing algorithm to obtain a panoramic three-dimensional scene model of the construction site; acquiring an image frame in the panoramic three-dimensional scene model, and analyzing the image frame by adopting a pre-trained work type identification model to obtain position information of operating personnel and equipment of each work type; acquiring position information of the operating personnel of each type of work, and analyzing postures of the operating personnel by adopting a pre-trained human body posture estimation model to obtain action state information of the operating personnel; and acquiring the position information and the action state information of the operating personnel of each type of work, and judging the specific operation state of the operating personnel of each type of work in combination with a pre-established work type operation knowledge base.

The embodiment of the invention provides a three-dimensional panoramic scene understanding method and device based on multi-view consistency. Relates to the field of three-dimensional scene reconstruction. The method comprises the following steps: inputting a multi-view image of a scene to be reconstructed into a pre-trained three-dimensional panoramic radiation field model, a pre-trained three-dimensional panoramic radiation field model uses a two-dimensional panoramic segmentation algorithm to segment geometric features, semantic features and color features of each view angle image in the scene to be reconstructed, and view angle consistency processing is carried out on the segmented geometric features, semantic features and color features; geometric features, semantic features and color features with consistent visual angles are obtained; and reconstructing the scene to be reconstructed through a pre-trained three-dimensional panoramic radiation field model according to the geometric features, the semantic features and the color features with consistent visual angles, and obtaining a panoramic image of the scene to be reconstructed. Therefore, the problems of semantic ambiguity and geometric structure distortion under multiple view angles are solved, and the precision and consistency of reconstruction and understanding of a three-dimensional panoramic scene are improved.

The invention discloses a multi-view overlapped video fusion splicing method and system, and relates to the technical field of video fusion splicing, and the method comprises the following steps: carrying out the basic processing of images collected by all cameras, and guaranteeing the consistent brightness and color of the images before splicing; extracting key feature points from the image by using a feature point detection algorithm; and matching the key feature points of the two images by using the feature descriptors to find similar feature point pairs in adjacent images. According to the method, matching errors are intelligently sensed, real-time detection and optimization are carried out in combination with a machine learning model and a correction algorithm, it is ensured that feature points meet geometric consistency, and accurate alignment is achieved through a homography matrix. Through brightness and color unified processing and overlapping region fusion, the generated panoramic image is excellent in visual effect, the accuracy of target identification and behavior analysis can be improved, and the method is especially suitable for high-quality splicing demand scenes such as security monitoring and the like.

The embodiment of the invention provides a GIS (Geographic Information System)-based metropolitan area safety video monitoring method and system. The method is applied to the technical field of image processing and comprises the following steps: acquiring a video picture of a coverage area in real time through a camera; performing real-time analysis on the video picture by using a target detection algorithm, and identifying a target in the video picture; converting the position of the target in the video picture into an actual geographic coordinate based on coordinate system conversion; continuously tracking the target in different camera coverage areas through the geographic coordinates; based on perspective transformation, converting the video image into an aerial view angle, and splicing aerial views to form a panoramic view; and visualizing the geographic coordinates of the target in the aerial view. In this way, the efficiency and accuracy of the city monitoring system can be improved, and therefore the requirement for city safety monitoring can be better met.

The invention discloses a cross-source data three-dimensional reconstruction method and system based on improved Gaussian sputtering, and the method comprises the steps: collecting an unmanned plane inclined image and a ground panoramic image of a target region, and constructing a time-space correlation data set; based on multi-view geometric constraints, space-time coding matching point pairs are established through an adaptive feature pyramid, intelligent incremental cross-source data sparse reconstruction is carried out, and point cloud and camera parameters are output; adopting improved Gaussian sputtering, compressing a three-dimensional Gaussian kernel into a two-dimensional Gaussian primitive through double tangent vector constraint, and fitting surface geometry to realize multi-scale reconstruction; and optimizing primitive parameters by using a differentiatable renderer, completing multi-scale fine reconstruction through gradient back propagation, and generating a high-precision three-dimensional model. According to the method, multi-scale accurate geometric prior input and accurate camera poses are provided for three-dimensional reconstruction, the dependence on professional manual operation in a traditional three-dimensional reconstruction method is greatly reduced, and meanwhile, the geometric accuracy and visual fidelity of a reconstruction result are remarkably improved.

The invention relates to the field of industrial cameras, and particularly provides a panoramic splicing type industrial camera device for a complex scene and a splicing method, and the panoramic splicing type industrial camera device comprises a multi-camera array, a synchronous control module, an image processing module, a calibration module and a communication module. The multi-camera array is distributed in an annular or matrix mode. The synchronous control module realizes sub-microsecond synchronization (error is less than 0.8 microsecond) based on an LVDS hardware trigger architecture, and eliminates splicing dislocation of a high-speed moving target. The image processing module carries an FPGA hardening assembly line and completes image distortion correction, optimization ORB feature matching and multi-band fusion in real time. The calibration module integrates a multi-mode sensing unit, and dynamically adjusts exposure, focal length and white balance through improved Kalman filtering and a deep reinforcement learning decision algorithm. In a strong interference environment, the panoramic stitching precision reaches 0.01 mm, the defect detection sensitivity is 30 [mu] m, the power consumption is only 12 W, and the system is suitable for various industrial scenes.

The invention discloses a single-view large-scale outdoor scene three-dimensional reconstruction method based on three-dimensional Gaussian splashing, and the method comprises the steps: collecting a pseudo aerial image, and constructing a panoramic multi-mode supervision end-to-end single-view three-dimensional reconstruction model; meanwhile, panoramic consistency supervision, semantic constraint depth regularization and a radial weighted luminosity loss and Gaussian cutting mechanism are introduced, so that the defect of insufficient geometric constraint of traditional single-view three-dimensional reconstruction is effectively overcome, and high-efficiency and high-fidelity three-dimensional modeling of a large-scale outdoor scene under single image input is realized; the method is suitable for various actual scenes such as smart city construction, automatic driving simulation, virtual reality / augmented reality, digital twinning and the like.

The invention relates to the technical field of image compensation, in particular to a reflection compensation method based on image processing, and provides the following scheme: acquiring an environment panoramic image by using a panoramic camera to establish a scene global coordinate system, and acquiring a multi-view original image in combination with a camera array arranged in the circumferential direction of an object; determining a rotation symmetry axis according to the multi-view contour features, reconstructing a three-dimensional geometric body, and calculating normal distribution and curvature change; generating a prediction image based on diffuse reflection and specular reflection hypothesis in the surface expansion domain through virtual visual angle disturbance, identifying a reflection region according to color and gradient consistency, and generating a reflection mask; and performing texture reconstruction on the reflective area by using geometric registration and multi-view compensation, and finally performing splicing and fusion to obtain a non-reflective high-fidelity panoramic image. The method does not need to change the field illumination condition, and can achieve the precise recognition and compensation of the complex curved surface reflection in the cultural relic in-situ collection environment.

The invention discloses a structural deformation measurement method based on geometric correction of a multi-view panoramic camera. A method for measuring bridge displacement by using a single multi-view panorama camera is provided, multi-view segmentation is performed on a panorama image according to a panorama camera equivalent model and a cube projection method, and independent calibration and correction are performed to obtain a distorted image capable of covering a 360-degree full-field range; therefore, a single panoramic camera is equivalent to a vertical four-camera system without overlapped view fields, so that the reference target in any direction can be used for displacement correction. The invention further provides a camera disturbance elimination method based on a multi-view circle center array target and pose transformation matrix purification optimization, and a coordinate system transformation matrix after purification optimization is obtained through a high-precision multi-feature point tracking algorithm from camera single-view moving target pose measurement. And obtaining a multi-view geometric correction theoretical model of any view of the measurement target and the reference target in a 360-degree range by utilizing a multi-view equivalent camera fixed connection relationship.

Systems and methods for view synthesis and three-dimensional reconstruction can learn an environment by utilizing a plurality of images of an environment and depth data. The use of depth data can be helpful when the quantity of images and different angles may be limited. For example, large outdoor environments can be difficult to learn due to the size, the varying image exposures, and the limited variance in view direction changes. The systems and methods can leverage a plurality of panoramic images and corresponding lidar data to accurately learn a large outdoor environment to then generate view synthesis outputs and three-dimensional reconstruction outputs. Training may include the use of an exposure correction network to address lighting exposure differences between training images.

The invention relates to the technical field of computer vision and artificial intelligence, and discloses a computer vision-based hundred-million-pixel panoramic situation awareness method and system, and the method comprises the steps: synchronously collecting original local field-of-view images through multiple cameras; independently executing target detection and semantic segmentation in an original image domain; constructing local-to-global coordinate mapping based on the calibration parameters; projecting the target features to a global coordinate system and detecting a cross-view-field target; extracting multi-view-field texture, edge and color features, and performing weighted fusion according to a visible area; according to the method, through identification preposition and semantic level feature fusion, geometric splicing distortion is avoided, the cross-boundary identification precision is improved, the calculation load is reduced, target continuous tracking and situation real-time output in a high-density scene are realized, and the method has high engineering suitability and industrial popularization value.

The invention discloses a virtual fire extinguishing training system and method based on deep learning flame recognition. The virtual fire extinguishing training system comprises a flame image acquisition module, a deep learning flame recognition module, a fire scene generation module, a fire extinguishing equipment simulation module and a scene customization module. And the flame image acquisition module is used for acquiring flame images and video data in different environments in real time through a high-definition camera, an infrared thermal imager, a panoramic camera and a sensor network. According to the invention, feature extraction and model training are carried out on mass flame images by using a deep learning flame recognition algorithm, accurate recognition of multi-dimensional information such as flame form, color, dynamic features and the like is realized, the flame detection capability in a complex environment is remarkably improved, and meanwhile, the system combines a physical engine and a scene generation module, so that the system is more accurate and reliable. The three-dimensional fire scene can be dynamically generated according to the real-time recognition result, the effects of fire spreading, smoke diffusion and the like are achieved, the constraint of a preset scene is eliminated, and training is more flexible and authentic.

A camera system has at least a first and a second camera which are attached to a common platform, each camera having a lens and an image sensor. Active areas of the image sensors of the first and second camera are determined. Image data only gathered from active areas of image sensors establish a panoramic image, which may be called an extended image space. Position sensors allow a processor to determine a location and a pose of the camera system. Coordinates of the extended image space are associated with a position of an object in physical space relative to a pointing direction of the camera system. A screen displays image data of a window of preset size around the image of the object in extended image space. A neural network is used to train the camera system to predict a position of an object based on camera rotations.

The invention discloses a bridge and tunnel inspection and maintenance management system and method based on a three-dimensional panorama and a GIS map, and relates to the field of bridge and tunnel inspection and maintenance. The method comprises the following steps: processing and fusing collected bridge and tunnel multi-dimensional environment data to obtain preliminary three-dimensional map data, performing super-resolution enhancement on a turbid shadow area to construct a high-precision three-dimensional digital model, and fusing the model with GIS data to obtain a digital twin data volume; microcosmic spectrum features are extracted, spectrum power authenticity judgment is carried out, and a health state time sequence is generated; planning an autonomous inspection path of an inspection machine, and introducing a quantum annealing algorithm to optimize scheduling and solve an optimal path; and constructing a knowledge graph associated historical maintenance record and an expert experience library, and mining a hidden association rule to generate a maintenance suggestion. Through fusion of multi-source data and intelligent analysis and optimization technologies, high-precision inspection, accurate damage evaluation and intelligent maintenance decision making are realized, and the intelligent level of bridge and tunnel management is improved.

The invention discloses a loopback SLAM (Simultaneous Localization and Mapping) method based on three-dimensional Gaussian sputtering and multi-camera input. According to the invention, fusion of three-dimensional Gaussian sputtering and multi-camera input is utilized to realize autonomous panoramic data acquisition and scene reconstruction with higher acquisition efficiency; according to the method, the constraint is constructed by using the overlapped part between the cameras, so that more accurate camera pose estimation and high-quality scene modeling are realized; according to the method, timestamp attributes are added to gauss, the gauss are classified according to the timestamp attributes, and the loopback is rapidly and effectively detected through different classes of gauss proportions under a current frame camera view angle; after the loopback is detected, the camera pose is adjusted, the problem of camera drifting is solved, meanwhile, a Gaussian map can be updated according to adjustment of the camera pose, and an accurate three-dimensional model is kept. According to the two-stage binding adjustment strategy provided by the invention, the global camera pose is finely adjusted by using the multi-view rendering image loss and the pose image constraint.

The invention relates to the technical field of panoramic monitoring, and discloses an image splicing method and system for a low-computing-power camera module array, and the method comprises the steps: collecting a panoramic image of a target scene through an array formed by a plurality of camera modules, configuring an initial priority weight in combination with a key marking instruction of a monitoring user, and carrying out the image splicing through the initial priority weight. A camera module is divided into a key module and a non-key module, timing dynamic detection is performed on the non-key module, real-time dynamic detection is performed on the key module, the weight is updated when a dynamic block is found, trajectory tracking is performed on the dynamic block by adopting a Kalman filtering algorithm, and the motion trajectory of the dynamic block is predicted. According to the scheme, the monitoring resource distribution of the camera module can be dynamically optimized, the response speed of a key area is improved, the real-time performance and accuracy of image splicing are improved, the monitoring efficiency and precision are effectively improved, and the method and the device have the advantages of being high in practicability and easy to popularize. The problem that in the prior art, a low-computing-power camera module array is difficult to achieve efficient and accurate image splicing is solved.

A method and an apparatus for predicting a road traffic carbon emission based on panoramic images, a device and a medium are provided, relating to the technical field of data prediction. In the method, a historical street view image of an observation area is acquired from the Internet, feature analysis is performed on the historical street view image to obtain a historical feature vector, and a road traffic carbon emission predicted value is obtained based on the historical feature vector and a carbon emission prediction model. With the method or the apparatus, auxiliary explanations for carbon emission sources in cities can be provided based on features of street views.

Systems and methods relate to improving image quality of panoramic images. A system generates for display on a device, a user interface for capturing a panoramic image, receives image data from a camera of the device from a plurality of view angles, and generates for display on a device a preliminary panoramic image based on the image data. The system determines that a position corresponding to a particular view angle of the preliminary panoramic image is problematic, and in response to the determining, generates for display an indicator for the preliminary panoramic image prompting for the camera of the device to be repositioned to the particular view angle of the preliminary panoramic image that was determined to be problematic.

The invention discloses a new view angle synthesis three-dimensional reconstruction method and system based on a single panoramic image. The system comprises a panoramic image conversion grid module, a grid completion module and a grid conversion three-dimensional Gaussian field module which are connected in series. A panoramic image is generated from panoramic images captured by any camera at a single location. Comprising the following steps: firstly, constructing a preliminary grid from an input panoramic image, then iteratively optimizing the grid through a panoramic complementing device, and collecting a three-dimensional consistent pseudo new view; and finally, the optimized grid is converted into a three-dimensional Gaussian field, and training is carried out by using the collected pseudo new view. According to the method, the three-dimensional scene of the real world can be reconstructed only according to input of one panorama, the data acquisition cost of three-dimensional reconstruction is remarkably reduced, the situation of large-area shielding can be effectively processed, details of fine textures can be reserved, and a new realistic view with a detailed geometric structure can be synthesized.

Systems and methods for generating a panorama image. Captured images are coarsely aligned, and then finely aligned based on a combination of constraint values. The panorama image is generated from the finely aligned images.

According to the panorama camera and 3D laser scanner mobile measurement matching method, distortion correction, camera calibration and multi-lens relative orientation matching of the panorama camera are carried out based on the characteristics of the panorama camera for a monocular camera and the panorama camera; establishing collaborative matching between the laser data and the image data and a matching and fusion basis between the laser data and the image data; based on a pinhole imaging model, all parameters of camera calibration are introduced to complete camera calibration, and the relative orientation relation between the laser scanner and the panoramic camera is deduced according to a cylindrical or spherical projection method; a cooperative calibration method based on plane constraint is adopted, initial values of rotation and translation vectors between a checkerboard plane and a distance are solved by utilizing a constraint relation between the normal vector and the distance of the checkerboard plane in a laser and camera coordinate system, and finally a global optimal solution is obtained by iteratively optimizing a target equation. The method is simpler to operate and does not need too much manual intervention. And the matching precision is high, the speed is high, and the robustness is good.

The invention discloses a shielding complementing method based on a continuous streetscape panoramic image, and aims to solve the problem of information loss caused by shielding of dynamic objects (such as vehicles and pedestrians) in the existing streetscape image, and the method comprises the following steps: S1, recognizing and positioning a dynamic shielding object area in a continuous streetscape panoramic image sequence; s2, providing a continuous panoramic image-oriented feature extraction and matching algorithm (FDMPano), realizing robust feature retrieval and matching in a cross-view angle, and accurately positioning a reference image region which can be complemented; and S3, carrying out feature alignment and content mapping on the sheltered area based on a matching result, and generating an unsheltered panoramic image with consistent vision. According to the method, the internal relevance of continuous streetscape data is fully utilized, the occlusion area can be automatically completed with high quality, the integrity and availability of streetscape images are remarkably improved, and the method has wide application value in the fields of automatic driving, digital cities, virtual reality and the like.

The invention discloses a waterlogging panorama construction method based on panorama stitching and spatial projection, and the method comprises the steps: image collection and feature extraction: obtaining a multi-view waterlogging image from a monitoring video, and extracting and matching key points to establish a spatial feature relation; panoramic stitching and projection transformation are carried out, a point cloud model is constructed, a projection matrix is generated, multi-view images are stitched into a hexahedral panoramic image, and the calculation efficiency is optimized; spherical mapping and visualization: mapping the panoramic image to the inner wall of the sphere to realize immersive display; target detection and positioning are carried out, a waterlogging area is identified through deep learning, the ponding range is calculated in combination with camera parameters, and accurate monitoring is achieved; and panoramic browsing and dynamic updating are carried out, an interactive panoramic system is constructed, the ponding range and the change trend are displayed in real time, and the emergency response capability is improved. Through fusion of computer vision and space projection technologies, multi-view panoramic stitching and three-dimensional display are realized, and the coverage range, the real-time performance and the visualization capability of waterlogging monitoring are improved.

The present disclosure provides computer-implemented methods and systems to generate high dynamic range (HDR) panoramas to render virtual objects. A low dynamic range (LDR) panorama from a prompt describing a desired aspect of a panorama. The LDR panorama is then converted to an HDR panorama. The process can include generating a backplate image using a first machine learning model, projecting the image onto a sphere and inpainting it using a second machine learning model to generate an LDR panorama, and converting the LDR panorama to an HDR panorama using a third machine learning model. Each of the 10 first, second and third machine learning models can be diffusion models. Alternatively, the third machine learning model can be a convolutional neural network model. A physics-based rendering engine can then be used to render a virtual object in the HDR panorama.

The invention relates to the technical field of anomaly positioning, and provides an anomaly positioning method and system based on panoramic video fusion. The method comprises the following steps: carrying out discrete video stream acquisition and return on a management and control area, and determining multiple paths of video streams; converting and clustering the multiple paths of video streams, and determining a preprocessed video stream; constructing a three-dimensional panorama fusion module, performing fusion splicing modeling on the preprocessed video stream, and determining a fusion panorama; carrying out abnormal event positioning and visual angle refinement based on the fused panorama, and determining abnormal positioning data; determining a spatial distribution field, performing spatial field calculation for the abnormal positioning data, and determining a target camera holder; and controlling the target camera holder, carrying out refined monitoring, and determining an abnormal positioning single column. According to the method, the technical problems of limited monitoring range and low positioning precision in a traditional anomaly positioning method are solved, full-coverage and high-precision monitoring and positioning of the control area through panoramic video fusion are realized, and the effect of improving the abnormal event reverse checking efficiency is achieved.

The invention discloses a full-appearance detection method and system for welding flux of an internal wire of an automobile brake hose joint. The method comprises a multi-angle collaborative imaging step, a geometric defect detection step, a texture defect detection step, a dynamic fusion decision-making step and a fault-tolerant adjustment step. Images are collected through the cameras which are asymmetrically arranged in a surrounding mode and synthesized into a panoramic image, and detection blind areas are eliminated. The welding flux area can be fully covered, the defect detection precision and efficiency are improved, the adaptability to supplied material deviation is enhanced, and the method is suitable for full-appearance quality detection of the automobile brake hose connector internal wire welding flux.

An environmental capture system (ECS) captures image data and depth information in a 360-degree scene. The captured image data and depth information can be used to generate a 360-degree scene. The ECS comprises a frame, a drive train mounted to the frame, and an image capture device coupled to the drive train to capture, while pointed in a first direction, a plurality of images at different exposures in a first field of view (FOV) of the 360-degree scene. The ECS further comprises a depth information capture device coupled to the drive train. The depth information capture device and the image capture device are rotated by the drive train about a first, substantially vertical, axis from the first direction to a second direction. The depth information capture device, while being rotated from the first direction to the second direction, captures depth information for a first portion of the 360-degree scene. The image capture device captures, while pointed in the second direction, a plurality of images at different exposures in a second FOV that overlaps the first FOV of the 360-degree scene. The depth information capture device and the image capture device are rotated by the drive train about the first axis from the second direction to a third direction. The depth information capture device, while being rotated from the second direction to the third direction, captures depth information for a second portion of the 360-degree scene. The image capture device, while pointed in the third direction, captures a plurality of images at different exposures in a third FOV that overlaps the second FOV of the 360-degree scene.