35 results about "Spatial distortion" patented technology

The invention provides an image correction method and system based on a nonlinear distortion distribution elliptical fisheye lens, and a medium. The method comprises the following steps: establishing a nonlinear mixed distortion imaging model based on a mapping relation between image coordinates and a spherical direction; defining a distortion vector, and performing fitting processing on the distortion vector based on a two-dimensional B-spline function to obtain a distortion function; the method comprises the following steps: acquiring images in a five-surface three-dimensional angle calibration space based on an elliptical fisheye lens, analyzing lens imaging parameters, and generating parameter values of a distortion function; analyzing parameter values of the distortion function based on a nonlinear mixed distortion imaging model to generate calibration parameters, and remapping pixel points in the distorted image based on the calibration parameters; performing image reconstruction on the remapped distorted image to obtain a corrected image; improving the sampling density of a target area by constructing a nonlinear mixed distortion imaging model; the system adapts to complex monitoring environments such as galleries and entrances and exits; and spatial distortion is flexibly expressed through a B spline, so that the modeling capability is improved.

The invention provides a cast-in-place pile quality online monitoring method and system based on an ultrasonic array, and the method comprises the steps: transmitting and receiving ultrasonic waves through the ultrasonic array arranged in a cast-in-place pile, and obtaining a multi-channel sound wave signal; performing generalized S transformation processing on the multichannel sound wave signals to obtain a time-frequency matrix, and calculating a cross correlation coefficient between each channel signal and the defect-free reference signal; an amplitude matrix and an instantaneous phase gradient matrix are calculated based on the time-frequency matrix, neighborhood amplitude energy and a phase consistency factor are fused in a time-frequency domain, and a defect energy indication diagram of the pile body section is generated; calculating the energy entropy of the defect energy indication diagram in a full frequency band; and extracting an actually measured energy arrival time sequence, comparing the actually measured energy arrival time sequence with a theoretical arrival time sequence to construct a space distortion vector, and setting a threshold value by combining energy entropy to judge defects.

The invention belongs to the technical field of artificial intelligence and environment monitoring, and particularly relates to an air pollutant concentration prediction method based on an ICLU-CWGAN model. The method comprises the following steps: acquiring and preprocessing data such as atmospheric pollutant concentration and weather, fusing an Inception multi-scale convolution thought with a ConvLSTM network, and constructing a multi-scale ConvLSTM network; the method comprises the following steps: under a Wasserstein generative adversarial network framework with a gradient penalty condition, taking a multi-scale ConvLSTM as a generator, taking an improved U-Net as a discriminator, and constructing an ICLU-CWGAN model; and completing model training by using the preprocessed training grid data, and predicting the atmospheric pollutant concentration. According to the method, the problems of weak long-time-sequence complex space-time correlation modeling capability, spatial distortion and unstable training in the prior art can be solved, so that the precision and the stability of atmospheric pollutant concentration space-time distribution prediction are improved.

The invention discloses a dynamic environment multi-line radar calibration method and system, and relates to the technical field of road radars, and the system comprises a dynamic reference field generation unit which is disposed on the ground of a radar coverage area, is composed of a reflection target array with known space coordinates, and is adjustable in target distance, and a multi-line laser radar unit which is provided with a horizontal field angle of not less than 120 degrees, and is provided with a multi-line laser radar unit. The number of lines in the vertical direction is larger than or equal to 128 lines per frame, the radar body is installed on the portal frame and connected with the control device, the environmental parameter sensing unit collects the temperature, three-dimensional acceleration and power supply voltage data of the radar body in real time, and the distortion compensation module constructs a space distortion field model based on real-time point cloud feedback and environmental parameters of a dynamic reference field, outputs a calibration matrix and outputs the calibration matrix. And the multi-radar collaborative calibration module is used for synchronizing space-time reference through a PTP protocol. Through a real-time compensation mechanism driven by environmental parameters, vibration acceleration and temperature change data are converted into space coordinate correction, and high-precision stable measurement in a dynamic environment is achieved.

This application provides an isolation structure and its manufacturing method. The isolation structure includes a substrate, an isolation trench, a flexible dielectric layer, and a filling layer located within the substrate. The flexible dielectric layer is made of hydroxyl-para-xylene. The filling layer covers the surface of the flexible dielectric layer and fills the isolation trench. This flexible dielectric layer can reduce cracks caused by excessive stress in subsequent thermal processes and can adapt to spatial distortion caused by the expansion of residual gas in the isolation trench through deformation under thermal conditions, reducing damage to the substrate, enhancing the electron coupling ability of the HiK material, improving the yield of devices on the substrate, and reducing dark current in devices and white spots in display images from the source. In addition, this flexible dielectric layer does not contain metal, so it will not cause metal ion contamination to the substrate. It eliminates the need for an additional isolation layer, improving the performance of devices on the substrate while simplifying device structure and processes and reducing manufacturing costs.

The location of the mobile device is estimated using angle-based positioning measurements. These measurements are generated using transmit (Tx) or receive (Rx) beams from one or more base stations generating beams over an ultra-wide bandwidth that introduces frequency and spatial distortion and attenuation in the array gain response. Variations in the array gain distribution as a function of angle and frequency for the set of beam weights used in beamforming are transmitted to indicate frequency and spatial distortion. The array gain distribution variation for a subband that serves as a portion of the allocated bandwidth for the base station can be provided to the mobile device in auxiliary data, or an aggregation of array gain distribution variations for multiple subbands of the allocated bandwidth can be provided to the mobile device to reduce the burden on signaling.

The present application belongs to the field of artificial intelligence and environmental monitoring technology, and particularly relates to an atmospheric pollutant concentration prediction method based on an ICLU-CWGAN model. By obtaining and preprocessing atmospheric pollutant concentration, meteorological and other data, the Inception multi-scale convolution idea is fused with the ConvLSTM network to construct a multi-scale ConvLSTM network; under the condition of the gradient-penalized Wassertein generative adversarial network framework, the multi-scale ConvLSTM is taken as a generator, and the improved U-Net is taken as a discriminator to construct an ICLU-CWGAN model; the model training is completed by using the pretreated training grid data to predict the atmospheric pollutant concentration. The present application can solve the problems of weak modeling capability for long-time sequence complex space-time correlation, spatial distortion and unstable training in the prior art, thereby improving the accuracy and stability of the atmospheric pollutant concentration space-time distribution prediction.

This invention relates to the field of mobile track geometry state detection technology, and discloses a real-time track state detection method based on multi-sensor fusion and dynamic compensation. It collects multi-source synchronous data from a global navigation satellite system receiver, inertial measurement unit, and laser profilometer mounted on the vehicle body, as well as accelerometers mounted on the bogie, and performs time synchronization and coordinate system unification. Through dynamic error correction and extended Kalman filtering fusion, it achieves high-precision estimation of vehicle attitude, velocity, and position. First-level point cloud motion compensation eliminates spatial distortion caused by the rigid body motion of the vehicle itself on the point cloud collected by the laser profilometer. Second-level point cloud motion compensation eliminates residual geometric errors caused by high-frequency vibration of the bogie. Finally, track geometric parameters are extracted and smoothness analysis is performed. This invention achieves high-precision reconstruction of track point clouds, providing technical support for real-time, high-precision track state monitoring on operating trains.

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.

This invention relates to the field of mobile device camera testing technology, and discloses an Android dynamic adaptive screen camera testing system, including a light sensing module, an algorithm module, a parametric template system, a distortion compensation engine, and a differential rendering module. The light sensing module collects ambient absolute illuminance data; the algorithm module calculates the ambient illuminance gradient and controls the system state flow; the parametric template system reconstructs basic texture parameters based on the gradient to generate a two-dimensional texture of the test pattern; the distortion compensation engine constructs a non-uniform three-dimensional geometric mesh model based on the screen curvature radius and performs spatial distortion calculations on the vertices of the two-dimensional texture; the differential rendering module obtains a feature mask image, performs shading resource reallocation calculations, and sends a timing synchronization trigger command to the camera under test after rendering is completed. This invention can reduce the impact of sudden changes in external ambient light on the pattern display quality and compensate for the geometric deformation at the edges of curved screens.

The invention provides a laser auxiliary positioning system and method based on intelligent control. The method comprises the steps of collecting a polarization image reflected by the surface of a target positioning area; generating a multi-dimensional feature description matrix in a laser projection process according to polarization state distribution and spatial distortion features of each polarization sub-image in the polarization image; constructing a polarization fingerprint spectrum of the target positioning area according to the relevance between the laser projection features under different polarization channels identified by the multi-dimensional feature description matrix and the target spatial position; reconstructing the projected laser pattern into an optimized image matched with a preset positioning template on the surface of the target positioning area based on a pose adjustment instruction generated by the polarization fingerprint spectrum; and determining a positioning completion state of the target positioning area based on the optimized image. According to the technical scheme provided by the invention, the laser pattern emitted by the laser can be accurately mapped under the interference of the nonlinear change of the surface optical characteristic.

The present application belongs to the technical field of computer vision, and discloses a reference relationship construction and consistency control method in visual asset generation, which is executed by an embedded visual processor: geometric features, texture features and illumination features of dynamic visual assets are collected and normalized pretreatment is completed to obtain standardized time sequence feature data; a time sequence deviation quantization factor is calculated in combination with a single frame time sequence interval; a cross-domain mapping distortion coefficient is calculated by fusing a time sequence deviation, a time sequence interval and a double-domain feature component; a consistency control total weight is calculated by linking a time sequence parameter, a distortion coefficient and a cross-scale feature total amount; and a visual asset reference relationship is reconstructed based on the total weight and rendering output is completed. The present application introduces a physical time sequence dimension to quantify interframe deviation, realizes linkage correction of time sequence error and spatial distortion, solves the technical problem that traditional static feature matching cannot adapt to dynamic rendering scenes, and effectively guarantees dynamic visual asset feature consistency and rendering stability.

The application belongs to the technical field of image fusion, and particularly relates to a remote sensing image fusion method and system based on local variance image mutual information. The method comprises the following steps: firstly, using a multivariate linear regression component replacement fusion method to perform fusion to obtain an initial fusion image; then, on the basis of the initial fusion image, similarity between an intensity component of a high-resolution multispectral image and an intensity component of the initial fusion image is calculated with the aim of obtaining an optimal Gaussian filter; finally, the original high-resolution panchromatic image is filtered by using the estimated optimal Gaussian filter to obtain a low-resolution panchromatic image, and image fusion is performed on the basis of the low-resolution panchromatic image. The application makes the fused image more conducive to the preservation of spectral characteristics and reduces spatial distortion in the spatial scale.

The invention provides a long-time viewport prediction method based on a space deformation attention network, and belongs to the technical field of 360-degree panoramic video viewport prediction. The method comprises the following steps: firstly, modeling a historical head movement track of a user by using a convolutional long-short-term memory network, and extracting basic spatio-temporal characteristics; then introducing a spatial deformation attention network, dynamically adjusting a convolution sampling position through a biased field prediction module, and adaptively compensating spatial distortion generated by isometric columnar projection through deformable sampling; meanwhile, in combination with a space and channel dual attention gating mechanism, performing multi-dimensional significance enhancement on the deformed feature map; and finally, generating a probability distribution diagram of a future viewport through feature fusion and edge enhancement output network. Experimental results show that the average prediction accuracy of the method exceeds 97% within the range of 1s to 5s, the limitation that a traditional fixed convolution kernel is difficult to adapt to the non-uniform distortion of the panoramic image is effectively broken through, and the perception ability of the model to the change of the space structure and the stability of long-term prediction are remarkably improved.

The invention provides a game picture optimization method and game equipment, and relates to the technical field of image processing.The method comprises the steps that a current frame game image and basic parameters of the game equipment are obtained; segmenting the current frame of game image into a plurality of image blocks, and setting an initial coloring rate of each image block; extracting a texture signal of each image block; judging whether the basic parameters of the game equipment meet preset conditions or not; if yes, determining the quality score of each image block by using a predefined quality score calculation formula according to the initial coloring rate; otherwise, determining the spatial distortion value and the time distortion value of each image block according to the initial coloring rate and the texture signal; performing weighted summation on the spatial distortion value and the time distortion value, and determining a negative number of a weighted summation result as a quality score of each image block; determining the optimal refresh rate of the display screen according to the quality score of each image block; according to the optimal refresh rate of the display screen, the optimal coloring rate of each image block is determined, and optimization of the game picture is completed.

The utility model discloses a double-ring type bow and arrow aiming device, and relates to the technical field of bow and arrow aiming. The first aiming ring and the second aiming ring form a three-dimensional channel which is sequentially reduced from near to far, the first aiming ring and the second aiming ring assist in different colors and strengthen the three-dimensional channel, and when aiming is inclined, a user can see spatial distortion of the three-dimensional channel, so that adjustment is facilitated, and aiming is further assisted; the height position of the sighting needle in the connecting seat can be changed by changing the position of the adjusting column in the connecting seat, so that the use requirements under different conditions can be met, and the mounting positions of the fixing frame, the fastening column and the mounting frame can be changed by changing the position of the positioning column in the positioning frame. And by changing the position of the fastening column in the fixing frame, the use position of the mounting frame can be changed, so that the purpose of mounting at different positions can be achieved, and the practicability and the applicability are further improved.

The tunnel floor heave state recognition method and device are disclosed, the over-limit section is determined in the target section, the high-low irregularity waveform, the track irregularity waveform, the horizontal irregularity waveform, the triangular pit irregularity waveform, the track slab separation thickness and / or the center ditch shape and the like track parameters of the over-limit section are obtained, the spatial distortion form of the track slab is determined according to the track parameters, the tunnel floor heave state of the over-limit section is determined according to the spatial distortion form, and thus, the deformation state of the track slab and the floor heave state of the tunnel can be determined by analyzing the track detection data, and technical support is provided for identifying the tunnel disease range, analyzing the tunnel disease causes and proposing the tunnel disease solution scheme.

The embodiment of the invention discloses a tunnel floor heave state identification method and device, and the method comprises the steps: determining an over-limit section, of which the uneven value exceeds an over-limit threshold value, in a target section; the method comprises the following steps: acquiring track parameters such as unevenness waveform, rail direction unevenness waveform, horizontal unevenness waveform, triangular pit unevenness waveform, track plate gap thickness and / or central ditch shape of an overrun section, determining a spatial distortion form of a track plate according to the track parameters, and determining a tunnel floor heave state of the overrun section according to the spatial distortion form. According to the embodiment of the invention, the deformation state of the track plate and the heaving floor state of the tunnel can be determined by analyzing the track detection data, so that technical support is provided for identifying the tunnel disease range, analyzing the tunnel disease cause and proposing a tunnel disease solution.

This invention relates to the technical field of ecological product value accounting, and in particular to an ecological product value accounting mapping system and method based on grid conservation allocation. The system includes a data source access module, a basic data management subsystem, a value accounting management subsystem, a spatialization and consistency engine, and a result output module. The system solves the problem of mismatch between multi-source heterogeneous data through online verification and consistency preprocessing. Utilizing the spatialization and consistency engine, it introduces vegetation net primary productivity weighting in material product allocation and suitability weighting in cultural service allocation, and employs a normalized conservation allocation algorithm. This invention can reveal spatial heterogeneity within a county and strictly ensures the conservation constraint between grid summary values ​​and statistical totals, realizing a closed-loop operation from raw data management to result mapping, improving the authenticity and consistency of accounting results, and solving the problems of spatial distortion, inconsistent definitions, and cumbersome operation in existing technologies.

The application provides a panoramic image quality evaluation method and system fusing multi-level distortion perception, and the method comprises the following steps: obtaining a stage distortion perception refined feature map based on a processed panoramic image; obtaining a distortion perception feature map processed by a deformable adaptive distortion perception module based on the stage distortion perception refined feature map after local branch and global branch processing; obtaining a feature attention fusion feature map based on the distortion perception feature map processed by the deformable adaptive distortion perception module; and obtaining a predicted quality score of the panoramic image based on the feature attention fusion feature map. Through the feature attention fusion module, the bilinear interpolation up-sampling deep layer feature map is added to the shallow layer feature map, and then the spatial distortion perception attention module is used to adaptively highlight the area related to distortion, so that the perception ability of the model to complex distortion is enhanced, and the final fusion feature is obtained.

The invention provides an automatic evaluation system and method for a vehicle-mounted sound reinforcement system. Efficient and objective whole vehicle acoustic performance evaluation is realized through binaural microphone multi-dimensional acquisition, pulse response analysis and a dynamic weighted scoring model. According to the system, a binaural microphone is fixed by a multi-dimensional bracket with a height and distance adjusting mechanism, and the head posture of a passenger is accurately simulated; a 20Hz-20kHz sweep frequency signal and an 18-24kHz near ultrasonic signal are driven in a time-sharing manner through a loudspeaker controller, and crosstalk is suppressed in combination with a time division multiplexing technology; six indexes such as frequency response flatness, reverberation time, total harmonic distortion and a speech transmission index are extracted based on an impulse response file, a centesimal system score is generated by adopting reverse normalization and dynamic weight adjustment, and the problems of spatial distortion, high-frequency detection blind areas, subjective and objective disjunction and the like of traditional single-point measurement are effectively solved.

This invention relates to the field of online detection technology for surface defects of counterweights, specifically disclosing a machine vision-based online detection method and system for surface defects of counterweights. This invention constructs a phase synchronization triggering mechanism based on physical displacement to ensure sub-pixel synchronization between camera line scanning and conveyor belt displacement, eliminating motion blur. It utilizes a high-speed linear scan camera to acquire multiple rows of one-dimensional image data, generating a continuous row pixel sequence carrying absolute spatial position. By extracting physical contour features and calculating instantaneous spatial attitude parameters, spatial distortion correction is performed on the image. Furthermore, by integrating the corrected row pixel data, a virtual global static image with eliminated motion distortion is reconstructed, and a defect recognition algorithm is applied to detect microscopic defects on the counterweight surface, outputting a quality judgment result. This invention effectively solves the problem of microscopic defect detection in high-speed non-uniform motion scenarios, improving the reliability and repeatability of detection.

The invention discloses an underground mine electronic fence monitoring system and method based on the Internet of Things, and the system comprises an establishment module which is used for establishing an underground mine three-dimensional basic model based on the Internet of Things technology; the generation module is used for generating a mine electronic fence based on a geographic information system according to the underground mine three-dimensional basic model; the acquisition module is used for acquiring personnel position data; and the monitoring module is used for monitoring according to the mine electronic fence and the personnel position data to obtain a monitoring result. Real-time data are obtained based on the Internet of Things technology, the three-dimensional foundation model of the underground mine is convenient to update, and synchronous adjustment of the mine structure and the electronic fence is achieved. The dynamic electronic fence is generated based on the three-dimensional model, and spatial distortion of a traditional two-dimensional fence is avoided. Monitoring is carried out according to the mine electronic fence and the personnel position data, the three-dimensional model and the environment parameters are fused, whether the personnel cross the boundary or not is accurately monitored, potential safety hazards can be eliminated conveniently, and construction safety is improved.

The present invention provides a transformer-based panoramic image feature representation learning method, comprising: dividing a first panoramic image into a number of squares, extracting features from each square using a multi-layer deep convolutional neural network to obtain a first eigenvector for each square; dividing the squares into a number of first windows, performing a self-attention operation on all squares within each first window, and obtaining a second eigenvector for each square; subjecting all squares in the entire first panoramic image to a sliding transformation and a self-attention operation to obtain a third eigenvector for each square; rotating the copied first panoramic image by 90° to obtain a second panoramic image, performing a cross-attention operation, and obtaining a fourth eigenvector for each square; and, based on the obtained eigenvectors, merging the features of every four adjacent squares as a group to obtain processed features of the first panoramic image. This invention overcomes the spatial distortion and boundary discontinuity problems of panoramic images.

This invention belongs to the technical field of image data processing and relates to an image processing method and system for adaptive optimization detection of a float position. The method includes the following steps: generating a spatial kinematic tensor based on basic geometric center data; generating a hydrodynamic spatial distortion phase array by modifying the preset standard point matrix distribution coordinates using addressing scaling factors; superimposing and merging the hydrodynamic spatial distortion phase array with the default center reference base address to generate a deformation address offset read / write pointer; merging the distortion spatial feature data to generate a target adaptive filtering pixel matrix; calculating the anti-interference centroid target position based on the entity's vertical contour boundary; generating a defect pointer and triggering a hardware abnormal interrupt level to reset the visual acquisition parameters. This invention solves the problem of limited target detection accuracy and insufficient tracking stability caused by using a fixed image sampling and processing model under dynamic fluid disturbance environments.

The invention discloses a flexible target and a calibration method. The flexible target comprises a plurality of target parts, and the target parts are movably connected in the mode that the shape and the relative position relation can be changed. Mark point patterns are arranged on the plurality of target parts; the spatial position relations of the mark point patterns on the multiple target parts can be mutually mapped according to shape and relative position relation change parameters when the shapes and the relative position relations of the multiple target parts are changed. According to the calibration method, the flexible target is adopted for calibration. When the target part of the flexible target is formed into a required form in a manner of changing the shape and the relative position relationship, the cameras in different directions can acquire required target images. The calibration method combines the structural characteristics of the flexible target and the spatial distortion coupling model, not only optimizes the geometrical relationship between the camera and the target, but also can dynamically correct the distortion along with the spatial position, thereby still keeping high precision in a multi-camera and multi-angle scene.

The application discloses a wheel image acquisition device based on a heterogeneous composite structure light and a wheel multi-parameter calculation method, relates to the technical field of wheelset parameter measurement, and comprises multiple light measurement units, a photoelectric triggering component and a controller. The multiple light measurement units are installed within the safety limit outside the same steel rail and are arranged in a straight line at equal intervals along the longitudinal direction of the steel rail. The light measurement unit is used for simultaneously generating a spatial laser plane of three common projection optical centers and a single-line laser plane in an excited state, and forming a three-line+single-line heterogeneous composite structure light on a wheel. The light measurement unit is also used for acquiring a local structure light image of the wheel. When the wheel travels, the wheel blocks the photoelectric triggering component, and a switching value signal is generated. The controller is used for generating a triggering pulse according to the switching value signal and controlling the light measurement unit to be in the excited state. The application shortens the wheelset measurement baseline, reduces the dynamic spatial distortion of the image, and improves the image quality of the structure light image.

The application discloses a sandstorm identification method based on stationary satellite remote sensing data and ground-based cloud images, and relates to the technical field of meteorological monitoring. The method comprises the following steps: step S10, spatial distortion correction is performed on a stationary satellite cloud image, multi-channel remote sensing data of a specified area is acquired, and standardization processing is performed; step S20, the cloud coverage area and the sandstorm area are identified by using the processed multi-channel satellite remote sensing data; and step S30, according to the identification results of the cloud coverage area and the sandstorm area, the satellite cloud image row and column numbers of the cloud coverage area are acquired, and the sandstorm area under the cloud condition is identified by using the all-sky ground-based cloud image. The application identifies the sandstorm weather of the sandstorm and the sandstorm under the cloud based on the deep learning method, and by fusing the channel data features and the time sequence features, the correlation between the fused features and the sandstorm weather is mined, so that the sandstorm identification precision of the cloud layer and the sand-dust layer boundary area based on the multi-channel satellite remote sensing data is improved.

The invention discloses a method for repairing spatial distortion welding deformation of a large structural member. The method comprises the following steps: measuring welding deformation data; carrying out data processing and modeling; model comparison and analysis; making a repair scheme; directional repair welding and machining are carried out according to the size; and rechecking and confirming the size. According to the method for repairing the spatial distortion welding deformation of the large structural part, through comparative analysis of a portable three-coordinate instrument and a CREO model, complex spatial deformation is converted into visual deviation data, and the limitation of traditional artificial experience repairing is broken through; the repair welding area is accurately positioned based on the model analysis result, the repair welding amount is determined, the problems of workpiece hinge point hole machining decentration and insufficient end face machining allowance caused by inconsistent deformation of an open structure are effectively solved, and the method can be popularized and applied to deformation repair scenes of other complex welding structural parts.