1129 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.

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 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.

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.

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.

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 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.

A camera system has at least a first and a second camera each with an image sensor. Active areas of the image sensors of the first and second camera are determined and define an extended image space of a real-time panoramic video. A bounding box captures a fixed position in space or an object is set. The bounding box moves through extended image space. Image data determined only by the bounding box is harvested from camera image sensors and displayed within a window on a screen in real-time. Scan-line control of images sensors based on the bounding box is updated in real-time to form an e-gimbal. Steps of the e-gimbal are performed by a machine learning inference phase on a processor.

The invention discloses a method and system for positioning a panoramic camera in a point cloud map, and the method comprises the steps: carrying out the preprocessing of a panoramic image and three-dimensional point cloud map data, and obtaining two-dimensional line segment features and three-dimensional line segment features; based on the two-dimensional and three-dimensional line segment features, calculating two-dimensional and three-dimensional line segment main directions and comparing to obtain candidate rotation estimation; designing a two-dimensional distance function and a three-dimensional distance function based on candidate rotation estimation to evaluate the rough pose, designing a two-dimensional / three-dimensional line segment loss function to score the candidate pose, and screening out # imgabs0 candidate poses meeting requirements according to scores; and carrying out two-dimensional and three-dimensional key point extraction on the # imgabs1 # candidate pose, matching the two-dimensional key points with the three-dimensional key points, and carrying out further pose estimation on the candidate pose with the maximum matching quantity by adopting a PnP-RANSAC algorithm, so as to obtain final fine pose estimation. The method overcomes the defects that in the prior art, point feature detection is unstable and depends too much on an ideal static environment.

A quadrotor is proposed than can both fly and roll. The proposed robot employs passively reconfigurable structures to enable the rolling, tightly coupling the attitude of the robot to the rolling cage. The benefits are precise rolling and turning control as well as improved rolling efficiency. The passively reconfigurable structures are enabled by pre-stretched elastic springs to generate a nonlinear restoring torque. The robot leveraged the superior maneuverability in the rolling mode to take photos of the surroundings at different tilting and panning angles to construct a panoramic image. Besides, the results of the power measurements show a significant reduction in the cost of transport brought by at low speed, equating to a 15-fold extension in the operational range.

The invention discloses an iron tower operation safety early warning system and method, and relates to the technical field related to intelligent safety early warning, and the system comprises a data obtaining unit which is used for obtaining Beidou three-dimensional coordinate data and an operation site panoramic image in real time; the operation scene model establishing unit is used for establishing a dynamic three-dimensional operation scene model; the prediction model building unit is used for tracking the motion trail of each operation target based on the coordinate data and building a prediction model fusing kinematics rules and machine learning; and the risk level judgment unit is used for carrying out risk level judgment according to the spatial position and the attribute characteristics of the intersection area and generating operation early warning information. The technical problems of insufficient safety early warning accuracy and timeliness caused by insufficient high-altitude operation target dynamic track monitoring precision and risk early warning lagging in the prior art are solved, and the purposes of accurately identifying the movement track intersection risk in real time, dynamically evaluating the safety level and improving the safety early warning efficiency are achieved. And the early warning accuracy and timeliness of the operation safety of the iron tower are improved.

The invention discloses a water area dynamic monitoring method and system based on an unmanned aerial vehicle remote sensing technology, and the method comprises the steps: adjusting the shooting angle of each camera according to the flight attitude of an unmanned aerial vehicle, and shooting a target water area photo after stabilization; performing water surface reflection compensation on the target water area picture based on the shooting angle; the compensated photos are sequenced according to the shooting time, and the photos of different shooting angles at the same shooting time are registered and spliced to obtain a panoramic image sequence; dividing the target water area into intervals, extracting an interval image sequence corresponding to each water area interval from the panoramic image sequence, extracting convolution features of each interval image in the interval image sequence, and splicing the convolution features with the shooting time of the panoramic image where the interval image is located and the central position of the corresponding water area interval to obtain a panoramic image sequence; obtaining a multi-dimensional feature vector; and constructing a water quality inversion model based on the multi-dimensional feature vector. The water quality inversion model constructed by the invention can realize dynamic monitoring of a water area and release early warning information more efficiently and accurately.

The invention discloses an automatic cattle checking method and system based on two-dimensional panoramic vision, and belongs to the technical field of computer vision and intelligent breeding, and the method comprises the following steps: reasonably arranging a plurality of fixed cameras in a cattle farm area, obtaining the internal reference and distortion coefficient of each camera through employing a camera calibration technology, and obtaining the internal reference and distortion coefficient of each camera; performing real-time distortion correction on the collected video frames; on the basis of side-by-side splicing or homography matrix perspective transformation, all paths of corrected images are fused into a complete two-dimensional panoramic image, and a view blind area of a single camera is eliminated; calling a lightweight target detection model on the panorama, and extracting bounding boxes and confidence coefficients of all cattle at one time; sorting according to the confidence from high to low, performing IOU non-maximum suppression de-duplication on the detection frame, and ensuring that the same cattle only counts once in an overlapping region; and the whole process is completed through the edge computing node. According to the invention, efficient, real-time and accurate on-site cattle checking of a large-scale cattle farm can be realized.

The invention discloses a mobile phone panoramic surround shooting device, which comprises a bottom plate, a shooting sliding module, a shooting arm, a self-adaptive mobile phone clamp, a display holder, a coupling group and a motor module, the shooting sliding module is arranged on the bottom plate, the shooting arm is connected to the shooting sliding module through a bolt, and the self-adaptive mobile phone clamp ball is connected to the shooting arm; shooting operation is carried out under the cooperative movement of the shooting sliding module and the shooting arm; the shooting sliding module and the display holder are mounted on the same axis, and the motor module is rotationally connected to an inner cavity of the display holder through the coupling group; the motor module works to drive the coupling set to rotate, and finally the display holder is driven to rotate. The device has the advantages that the precise synchronization of the linear displacement, rotation and telescopic motion of the shooting arm and the rotation of the display holder can be realized, and the omnibearing shooting of 180-degree free rotation images and videos of a part of a displayed object above the platform from a right view and a top view to a left view can be completed.

The invention belongs to the technical field of visual angle follow-up vehicle panoramic look-around, and particularly relates to a visual angle follow-up vehicle panoramic look-around system based on dynamic prediction, which is characterized in that monocular vision and laser radar time sequence data are fused, and a dense and stable dynamic target depth sequence is generated through dynamic target initial perception, cross-modal time sequence alignment and inter-frame depth correlation modeling; through environment interaction modeling and target behavior intention prediction double-branch parallel processing, a dynamic self-adaptive accurate track is output in combination with a weighted fusion strategy, and the prediction weight dynamic adjustment requirement of a complex motion scene is adapted; after a virtual view angle image is preliminarily synthesized based on the predicted trajectory, deviation detection and coordinate dynamic correction are realized through inter-frame target consistency verification, and artifact area positioning and pixel-level restoration are synchronously completed; multi-modal preprocessing and algorithm tasks are deployed according to hardware, and a model lightweight optimization and inter-frame prediction result multiplexing strategy is combined, so that low-delay operation of the system in a high-resolution panoramic image output scene is ensured.

The invention discloses a road culvert inner wall damage image detection and traffic capacity evaluation method and system, and relates to the technical field of road engineering detection and computer vision, and the method comprises the steps: collecting multi-source data through an annular camera, a laser section scanner and a mileage encoder carried by a detection robot, and carrying out the panoramic expansion and time-space registration; using a multi-scale attention panoramic segmentation network to identify damages such as lining cracks, joint slab staggering, damage and chipping, steel bar exposure and water leakage; calculating the clearance size and the deposition thickness of the culvert by adopting an ellipse fitting method; according to the method, the culvert detection speed reaches 50 m / h, and the damage detection accuracy reaches 89% or above.

The invention discloses an oral cavity panorama image data enhancement method and system. The method comprises the steps that an oral cavity panorama image is acquired and preprocessed; constructing and training an oral cavity panorama image data enhancement model, and inputting the preprocessed oral cavity panorama image into the trained auto-encoder to generate an enhanced image; according to the method, interference of a non-concerned area is effectively inhibited, the alveolar bone area is focused, the alveolar bone area is extracted more accurately, excessive segmentation and wrong classification are avoided, learning of key features is effectively enhanced, response of a key area is enhanced, artifact influences are effectively eliminated, the reconstruction effect is optimized, and the method is suitable for being popularized and applied. Therefore, non-physiological tooth arrangement after model reconstruction is avoided, the structural property and the layering sense of the image are further enhanced, overfitting is avoided, and meanwhile the regularization intensity in the training process is optimized.

The invention relates to a four-dimensional occupied grid panoramic sensing method and device based on visual information. The method comprises the following steps: after acquiring a multi-view image, inputting the multi-view image into a pre-constructed four-dimensional panorama perception model based on visual information, and outputting a four-dimensional panorama occupation grid prediction result; wherein the visual information-based four-dimensional panoramic perception model comprises an encoder module, a decoder module and a query vector propagation module, the encoder module is used for extracting three-dimensional volume features, the query vector propagation module is used for updating four-dimensional query vectors, and the decoder module is used for realizing interaction between the three-dimensional volume features and the four-dimensional query vectors. Compared with the prior art, the method has the advantages that the final four-dimensional panoramic occupied grid prediction result is generated in an end-to-end and streaming mode, and a large amount of post-processing requirements can be eliminated.

A quadrotor is proposed than can both fly and roll. The proposed robot employs passively reconfigurable structures to enable the rolling, tightly coupling the attitude of the robot to the rolling cage. The benefits are precise rolling and turning control as well as improved rolling efficiency. The passively reconfigurable structures are enabled by pre-stretched elastic springs to generate a nonlinear restoring torque. The robot leveraged the superior maneuverability in the rolling mode to take photos of the surroundings at different tilting and panning angles to construct a panoramic image. Besides, the results of the power measurements show a significant reduction in the cost of transport brought by at low speed, equating to a 15-fold extension in the operational range.