3312 results about "Reference map" patented technology

The invention relates to the technical field of industrial machine vision detection and image processing, in particular to an automobile part production mold surface smoothness detection system based on image enhancement, which comprises a data acquisition module used for acquiring an original grayscale image of the surface of an automobile part mold; performing low-pass filtering processing on the original grayscale image to eliminate imaging thermal noise; the manifold reconstruction module is used for constructing a structure tensor field; reversely deducing a pseudo-curvature field of the mold surface; the adaptive enhancement module is used for generating a corrected image; constructing a texture orthotropic diffusion model; generating a texture reconstruction reference image; the surface metering module is used for calculating the difference between the corrected image and the texture reconstruction reference image and generating a defect saliency image; calculating the surface roughness value of the mold surface; according to the method, the problem that design textures and abnormal scratches are difficult to distinguish in the prior art is effectively solved, and the technical bottleneck that micro defects are easily missed in a complex geometric structure in traditional visual detection is overcome.

The invention relates to a multi-stage filtering road spilled object detection method based on dynamic difference analysis, which is suitable for automatic identification of unstructured foreign matters in video monitoring. The method comprises the following steps: firstly, extracting a reference image road mask, eliminating vehicle and pedestrian interference by using YOLOv8 detection, and extracting a motion candidate area through a frame difference method and background modeling; and then context expansion and super-resolution reconstruction are carried out on the candidate region, the candidate region is converted into an HSV space, multi-dimensional features such as color similarity, structural similarity and shadow determination are synthesized for screening, false detection is further removed in combination with inter-frame time sequence consistency, and finally a stable detection result is output. The method provided by the invention has the advantages of strong anti-interference capability, high adaptability, high detection precision and the like, and is suitable for the intelligent recognition task of the expressway thrown objects in a complex environment.

The invention discloses a transformer substation positioning and navigation method and system integrating positioning and visual auxiliary positioning. The method comprises the following steps: establishing a background electromagnetic field distribution baseline graph associated with a three-dimensional reference map; electromagnetic field data of the transformer substation in an emergency response mode is collected through the unmanned aerial vehicle, and the abnormal field intensity of a space electromagnetic field and a fault source pointing vector pointing to a fault source are calculated; constructing a risk adaptive elliptical forbidden zone; calculating a passage cost index Cto of the unmanned aerial vehicle passing through each three-dimensional grid in the three-dimensional reference map by using the fault source pointing vector and the risk adaptive elliptical forbidden zone; and searching a path which is from the current position of the unmanned aerial vehicle to a preset target point, bypasses the risk adaptive elliptical forbidden zone, faces the fault source and has the lowest total passing cost index Cto by adopting a preset path search algorithm. According to the method, the risk self-adaptive elliptical forbidden zone is constructed and is used as the three-dimensional grid forbidden assignment processing, so that the dynamic global path avoidance of the sudden dangerous zone is realized.

Example devices, methods, and computer-readable media are disclosed. An example device includes one or more processors configured to determine a reference picture list for a current block of a current picture of the video data. The one or more processors are configured to determine that a reference picture of a collocated block is listed in the reference picture list for the current block, the collocated block being collocated with the current block in a collocated picture. The one or more processors are configured to select, in a condition where the reference picture of the collocated block is listed in the reference picture list for the current block, a reference picture for the current block to be the reference picture of the collocated block. The one or more processors are configured to and encode or decode the current block based on the reference picture for the current block.

The invention provides a three-dimensional reconstruction method based on guided filtering and Mama geometric feature fusion in the technical field of three-dimensional reconstruction, and the method comprises the steps: S1, collecting a multi-view RGB image, carrying out the calibration of a camera, obtaining a projection matrix and an internal reference matrix, and obtaining a reference image; s2, extracting image features from each RGB image; s3, sampling on the reference image to obtain a depth hypothesis plane, performing homography transformation on each image feature, and aggregating with the depth hypothesis plane to obtain a cost body; s4, sequentially performing filtering, regularization and exponential normalization on the cost body to obtain a probability body, and constructing a depth map and a confidence map based on the probability body; s5, performing frequency domain filtering and up-sampling on the depth map and the confidence map, and then performing feature fusion to obtain a visual angle depth; and S6, executing three-dimensional reconstruction operation based on the visual angle depth, the projection matrix and the internal reference matrix. The method has the advantage that the precision and robustness of three-dimensional reconstruction are greatly improved.

In an example embodiment, a method carried out by an uncrewed aerial vehicle (UAV) may involve receiving a reference map of a cluster of charging pads from a server. The cluster may include a layout of charging pads and fiducial markers distributed across the layout, the reference map representing the layout and fiducial markers. The UAV may fly to the cluster and acquire an image of charging pads and observed fiducial markers near the charging pads. The image may capture an observed constellation of fiducial markers at apparent positions and orientations relative to the charging pads. A reference constellation of fiducial markers at reference positions and orientations relative to reference charging pads may be identified in the reference map. Identities of the reference charging pads and a match of the reference constellation to the observed constellation may be used to disambiguate a particular charging pad from among the charging pads.

The invention relates to the technical field of defect detection, and particularly discloses a high-precision defect detection system based on image difference and threshold processing, which comprises a registration image acquisition module, a fixed mask conversion module, an image difference detection module, a correction difference graph generation module and a defect set output module, the method comprises the following steps: firstly, completing affine registration by shape features, changing a fixed mask into a dynamic mask, and performing edge robustness in the mask to obtain a preprocessed image; local movement difference is carried out on the preprocessed image and the multiple reference images, fusion of a reference domain and a time domain is carried out to generate a difference response image, and candidate areas are extracted in combination with a dynamic mask; estimating and correcting a displacement field in the candidate range, synchronously mapping to obtain a correction difference graph and a correction mask graph, and determining a peripheral rejection area; according to the method, false alarm and missing detection are effectively reduced, and the method is suitable for online high-precision detection.

The invention discloses a story-driven role and scene image generation method. The method comprises the steps that a natural language story text input by a user is received and preprocessed; through predefined role description structure constraints, enabling the language understanding and generation model to output a structured role description information structure under template constraints; generating a role image according to the structured role description information text, and extracting image features for consistency control; establishing a mapping table of structured role description information and image feature representation, and realizing the consistency of the appearance of roles in multiple scenes; automatically disassembling the complete story text into a plurality of scene nodes, and generating structured scene description information for each scene; and generating a complete story picture in combination with the scene description information and the role reference diagram. The invention provides a story-driven role and scene image generation method, which is used for automatically generating a story text to a role image and a scene image through semantic understanding, information description structured generation and image consistency management.

Methods and systems are described for end-to-end video coding and decoding using deep learning. Proposed fusion schemes for reference pictures and motion vector features allow single-prediction models for deep-learning video coding (DLVC) to be extended to support multi-reference prediction coding as well. Example high-level syntax to support a variety of deep learning models for bi-prediction is described as well.

The invention discloses a quadruped robot space precise positioning method and system based on deep learning. The quadruped robot space precise positioning method specifically comprises the steps that S1, a laser radar data stream and an inertial measurement unit data stream are aligned to generate a synchronous sensing data sequence in a unified mode; s2, determining a mapping pose sequence through consistency evaluation of poses output by the offline point cloud registration algorithm pool; s3, performing parallel loopback detection to generate a unified loopback constraint set; s4, the mapping pose sequence, the loopback constraint set and the pre-integration constraint are written into the factor graph model to generate a three-dimensional point cloud reference map; s5, the local point cloud frame and the three-dimensional point cloud reference map are registered, and a map matching pose is output; s6, the map matching pose and the pre-integration result are written into a factor graph model to continuously solve and output a continuous-time six-degree-of-freedom pose result; and S7, outputting a six-degree-of-freedom pose result in continuous time. According to the invention, direction constraint consistency point cloud registration and dual-channel loopback optimization are introduced, and stable and high-precision positioning of the closed space is realized.

The invention relates to the technical field of semiconductor manufacturing, photoetching alignment and feature recognition, and particularly discloses a photoetching alignment compensation system and method based on feature targeting. An exposed pattern on the surface of a wafer is used as a unique target reference, a built-in visual imaging structure coaxial with a photoetching light path is adopted, a sub-pixel-level feature extraction and dynamic reference real-time updating mechanism is combined, the dynamic deformation of the wafer is calculated, high-frequency compensation of a workpiece table is achieved, and nanoscale overlay precision is achieved. The core improvement of the invention lies in that a light path coaxial visual integrated structure is designed to solve the problem of external imaging parallax; a feature point self-adaptive weighted matching algorithm is provided, and the deformation compensation precision is improved; and constructing a reference map real-time micro-updating mechanism, and eliminating progressive deformation drift of the wafer. The system does not need to manufacture a special physical alignment mark, continuously verify a feature matching state in the whole exposure process and quickly trigger safety protection when the matching degree is abnormal, is suitable for a photoetching alignment process for manufacturing advanced process chips of 3nm and below, has an alignment error of less than or equal to 1.1 nm under a 12-inch wafer standard test condition, reduces the dependence on an ultra-precise workpiece table, and has a good application prospect. The system has the advantages of autonomous controllability, high interference resistance and controllable cost.

The invention discloses an automatic rectification method and system for an intelligent patrol point of power transformation equipment, and relates to the technical field of intelligent patrol of the power transformation equipment, and the method comprises the steps: extracting the structural features of a preset patrol point reference map of the power transformation equipment based on a power transformation equipment feature enhancement detection segmentation algorithm, and building a feature library of the patrol point reference map; the method comprises the following steps: extracting real-time visual features of a current frame image in an intelligent patrol process of power transformation equipment; matching the real-time visual features with a feature library of the inspection point location reference map by using a power transformation equipment multi-dimensional feature matching technology, and judging whether the current inspection point location deviates or not according to a matching result; if it is judged that the current patrol point position deviates, based on the visual feature corresponding relation between the reference image and the current frame image, deviation parameters for driving a camera to move are calculated; and generating a camera adjustment instruction according to the obtained offset parameter. The method avoids the hidden trouble of missing faults due to point location offset, and is suitable for large-scale inspection requirements in a complex transformer substation environment.

The invention provides a multi-view three-dimensional reconstruction method based on full-dimensional dynamic convolution and a content guidance attention mechanism. The method comprises a multi-scale feature extraction module, a cost body construction and aggregation module, a cost body regularization module and a depth map filtering fusion point cloud generation module. According to the method, feature extraction is carried out in a feature extraction network fusing full-dimensional dynamic convolution and a content-guided attention mechanism, and cross-layer feature transfer is realized by utilizing adaptive modulation convolution kernel capability of the full-dimensional dynamic convolution and content-guided attention, so that depth estimation in a weak texture region is more stable; the depth drift caused by insufficient feature information is reduced; and meanwhile, a weight map of the neighborhood map to the reference map is obtained by utilizing matching correlation, visible information enhancement is carried out on the weight map obtained by carrying out back projection on the neighborhood map in combination with the reference map, and the cost body is guided to aggregate more reliable information, so that error cost information of a shielding region or a visual angle range region is effectively inhibited when the cost body is aggregated. According to the image feature extraction method provided by the invention, the feature expression capability is enhanced, and visible information is further enhanced by using the weight map generated by bidirectional projection, so that a more accurate depth map is obtained, and finally, the accuracy and integrity of three-dimensional reconstruction are remarkably improved.

Aspects of the disclosure provide for controlling behaviors of autonomous vehicles based on evaluation of sensors of those vehicles. For instance, sensor data including distance and intensity information for a point in an environment of an autonomous vehicle may be received. An expected intensity value from a pre-stored fair weather reference map may be identified based on a location of the point. An effective detection range for the sensor may be dynamically determined based on the expected intensity and the intensity information for the point. A behavior of the autonomous vehicle may be controlled based on the effective detection range.

The invention discloses a high-precision satellite attitude correction method, system and equipment for a maximum initial positioning error, and belongs to the technical field of machine vision image matching. A proper reference region is selected to prepare a first reference image and a second reference image, and feature descriptors of the reference images are extracted offline; performing down-sampling on a remote sensing image acquired by a satellite remote sensing camera, and performing image matching on a real-time image after down-sampling and the first reference image; calculating the optimal window position of the ground calibration point of the reference area in the real-time image according to the matching result; cutting the real-time image according to the window position to obtain a high-resolution calibration point real-time image; performing image matching on the high-resolution calibration point real-time image and the second reference image; and calculating latitude and longitude coordinates of the center of the real-time image according to a matching result for satellite attitude correction. The position error of the target area is gradually reduced in a two-stage remote sensing image matching mode, the longitude and latitude coordinates of the center of the real-time image are accurately positioned, and high-precision satellite attitude correction is realized.

The invention relates to the technical field of intelligent costume design, and discloses an intelligent costume pattern generation system based on enhanced multi-modal generation, which comprises a multi-module input module, a layered attention fusion module, a self-adaptive position coding module and a hierarchical decoding module, the multi-module input module is used for receiving a clothing reference image, a version design demand text and structured data, and performing feature extraction respectively to obtain image features, semantic features and structural features; the layered attention fusion module adopts a three-layer attention mechanism to perform fusion processing on the image features, the text features and the structural features to obtain final fusion features; the self-adaptive coding module carries out self-adaptive coding on the final fusion feature and the model parameter of the clothing template, and outputs a coding result; and the hierarchical decoding module is used for decoding the coding result to generate a complete garment pattern.

The invention provides a cultivated land occupation state monitoring method, device and equipment and a medium, and the method comprises the steps: obtaining multi-temporal video image data and a cultivated land distribution reference map of a target monitoring region, and obtaining the distribution information of cultivated land; extracting a boundary line of a cultivated land area and a non-cultivated land area in the video image data of each time phase to obtain spatial position change data of the boundary line; analyzing the boundary feature set of each time phase according to the time sequence, identifying an abnormal region of boundary change, and further obtaining change data of the abnormal region; comparing and analyzing the abnormal region change data with the multi-temporal cultivated land distribution reference map to obtain a comparison result; extracting the morphological characteristics and the expansion direction of the abnormal region; simulating the future boundary change of the abnormal region, generating a prediction distribution diagram of the potential occupation range, obtaining the influence range of the abnormal region, and obtaining a monitoring result. According to the invention, the continuity and accuracy of monitoring the land occupation state can be improved.

This disclosure relates to video coding and more particularly to techniques for signaling picture information for coded video. According to an aspect of an invention, first syntax element specifying an index corresponding to a collocated picture used for temporal motion vector prediction is parsed from a picture header in a case that both (a) first flag indicating whether temporal motion vector predictor can be enabled for a picture associated with the picture header and (b) second flag indicating information associated with reference picture list are equal to 1.

The invention discloses an internet information intelligent monitoring method and system, a medium and a product, and relates to the technical field of data processing. The method comprises the following steps: firstly, acquiring internet information data containing text, image and audio contents, extracting features of the three contents respectively, and constructing a semantic map; calculating semantic similarity among different map nodes, and establishing a cross-modal mapping relation to form a mapping set; node attribute characteristics are extracted for the mapping relation to calculate consistency, and mapping lower than a threshold value is marked as a conflict relation; counting the conflict node proportion of each map to obtain a modal conflict degree, calculating the similarity with the reference map to obtain a modal matching degree, and calculating the modal credibility according to the modal matching degree; normalizing the modal credibility to obtain a weight coefficient, and performing weighted fusion on the map structure features to obtain a fusion feature vector; and finally, matching the fusion feature vector with a monitoring rule base to obtain a monitoring result. By implementing the technical scheme provided by the invention, the monitoring accuracy of Internet information can be improved.

The invention belongs to the technical field of online education, and discloses an AI digital human-computer interaction method and system applied to art design education and a medium, and the method comprises the steps that a multi-mode sensing module carries out input data collection and analysis; the digital person engine module realizes communication between virtual digital persons and students; during artistic creation of students, the generation type creation engine assists the students in creation; when a student inputs a keyword or uploads a reference picture, the creative inspiration excitation module carries out inspiration resource recommendation; the real-time cooperation module supports online synchronous editing of design works by multiple persons; the teaching evaluation system analyzes learning processes and works, constructs ability portraits, and recommends personalized learning paths and course packages. According to the invention, multiple interaction modes are supported through the multi-mode perception module, and the creative inspiration motivating module broadens the visual field of students and motivates creation inspiration through intelligent recommendation and inspiration communities; the teaching evaluation system scientifically constructs student ability portraits, recommends personalized learning paths and course packages, and meets personalized learning requirements.

A method of processing video data performed by a decoder includes: decoding a bitstream to obtain video data and coding information, the coding information comprising weighting map indication information for defining a weighting map and filter coefficients optimized for the weighting map; obtaining a picture block based on the video data; upsampling the picture block; determining the weighting map using the weighting map indication information; and obtaining an enhanced picture block by applying a signal enhancement filter using the filter coefficients, together with the weighting map, to the upsampled picture block.

A method and system for obtaining, from at least one camera associated with a vehicle traveling through a road network, a sequence of images of a road or a road environment, each image being associated with a location where that image is captured, generating a local map representation of an area of the road network using at least some images from the sequence of images and the locations associated therewith, the generating including: processing the at least some of the images to detect an object in the road or the road environment, determining at least one transformation for tracking the object between the at least some of the images and, based on the at least one transformation and the locations associated with the at least some of the images, generating a two- or three-dimensional representation of the object relative to the area of the road network, comparing the local map representation with a reference map covering the area of the road network, and determining, based on the comparison, a geographical location and an orientation of the vehicle within the road network.

The invention is suitable for the technical field of image restoration, and provides a space controllable generation guided unified image restoration method and model, and the method comprises the following steps: S1, image extraction: employing a pre-training model to extract a depth map and text description from a degraded image, the depth map being extracted through a pre-training depth map extraction model Depth-Anything-V2, and the text description being extracted through a pre-training depth map extraction model Depth-Anything-V2; the text description is extracted through a pre-training text description model CogVLM2, and the depth map is used for controlling the overall space of the reference map to be consistent with the degradation map. According to the unified image restoration method and model guided by spatial controllable generation, the spatial controllable reference generation model guided by a multi-granularity condition is introduced by improving the quality of a reference image and improving the restoration controllability, and the model can generate an intermediate reference image which is consistent in spatial structure and does not contain degradation on the basis of multi-granularity condition input; information support is provided for final restoration, degradation information can be effectively filtered out, and high-quality generation of the reference image is achieved.

The present application discloses a positioning method based on a dynamic region of a robot, comprising: step 1, upon verifying that a repositioning result fails, determining whether a matching score in the repositioning result is greater than a first preset score threshold, and if yes, proceeding to step 2; step 2, performing weighted calculation on the basis of the matching scores of point cloud points falling on a corresponding region of a target map to obtain a target matching score, and then proceeding to step 3; step 3, determining whether the target matching score is greater than a second preset score threshold, if yes, indicating that the positioning is successful, or otherwise, proceeding to step 4; step 4, setting a search distance on the basis of the relationship between a mask extracted from a reference map and a mask extracted from a depth dynamic region of the target map, and selecting a navigation target point within a preset positioning distance range on the basis of the search distance, and then executing step 5; and step 5, when a robot moves to the navigation target point, obtaining a repositioning result by means of a repositioning matching algorithm, and verifying the repositioning result to determine whether the positioning is successful.

The invention provides a circuit board defect detection method, device and equipment and a storage medium, and the method comprises the steps: generating multi-modal input data according to defect mask data of a defect image corresponding to a target circuit board and Gerber graph data of a preset circuit board design file, carrying out the linear overlapping block embedding processing, and generating coding features; performing spatial alignment on the defect image block feature of the coding feature and the reference image block feature of the Gerber image data to generate an aligned reference feature; performing style coordination on the alignment reference features and the defect image block features to generate local alignment features; carrying out feature fusion on the local alignment feature and the coding feature, and outputting a decoding feature; and mapping the decoding features to generate a repaired image. According to the method, the defects of the reference image can be repaired, so that the accurate reference image is provided for subsequent defect detection, misjudgment or missed judgment caused by the defects of the reference image is reduced, and the overall efficiency of a production line and the product quality control level are improved.

A decoder determines first symbols and second symbols available for prediction of respective first and second motion vector difference (MVD) components of a first reference picture list (RPL) and a second RPL. The decoder selects, based on the first and the second symbols available for prediction, one of the first RPL or the second RPL. The decoder selects, within each of the first MVD components of the selected RPL, a subset of most significant symbols for decoding. The decoder entropy decodes, from a bitstream for each symbol of the selected subset, an indication of whether a value of the each symbol is equal to a value of a corresponding symbol of an MVD predictor. The decoder determines, for the each symbol of the selected subset, a value of the each symbol based on the indication and a value of the corresponding symbol of the MVD predictor.

The invention relates to the technical field of parking space detection and vehicle control, and discloses a micropower geomagnetic parking space detection method and device, and the method comprises the steps: fusing the vector intensity and direction angle according to pre-obtained empty parking space geomagnetic vector data and real-time geomagnetic vector data, constructing a geomagnetic reference map, and calculating a real-time geomagnetic rotation angle; comparing and analyzing the geomagnetic reference map and the real-time geomagnetic rotation angle, generating a high-frequency sampling signal, acquiring high-frequency geomagnetic vector data of high-frequency sampling, and constructing a dynamic feature set; the adjacent vehicle interference condition is analyzed, a dynamic parking space state monitoring mechanism is configured, and the real-time state of a parking space is obtained; in response to a real-time vehicle moving task, planning and optimizing a vehicle moving path in real time to obtain an optimized path, and controlling the vehicle to move; the parking space state is adjusted in real time in combination with the adjacent vehicle interference condition, the accuracy of the parking space state detection result is improved, the optimal vehicle moving path is planned, the vehicle locating time is shortened, and the vehicle moving efficiency is improved.

The invention discloses an image hidden danger identification parameter optimization method and system based on a cascade model, and relates to the technical field of data processing. The method comprises the steps that a target image is collected, hidden danger areas are recognized, and a hidden danger candidate area set is obtained; performing fine-grained identification on each hidden danger candidate region in the hidden danger candidate region set to obtain a plurality of identification hidden danger descriptions; introducing a standard hidden danger reference image library, and carrying out feature similarity calculation on the hidden danger candidate region set to obtain a plurality of comparison hidden danger descriptions; generating a comprehensive hidden danger identification result according to the plurality of identification hidden danger descriptions and the plurality of comparison hidden danger descriptions; wherein before the hidden danger area is recognized, according to the scene of the target image, parameter optimization is carried out on the large model of fine-grained recognition and the feature similarity calculation parameters. According to the method, the image hidden danger recognition accuracy and the scene adaptability are effectively improved.

1. The name of the design product: electronic device with small program building graphical user interface. 2. The use of the design product: for electronic devices. 3. The design points of the design product: the content of the graphical user interface in the screen. 4. The picture or photo that best indicates the design points: design 1 front view. 5. The carrier of the design product is the usual design, and the rear view, left view, right view, top view and bottom view are omitted. 6. Design 1 is designated as the basic design. 7. The use of the graphical user interface: the interface is an interactive interface for building and designing small programs in the operation background; the design 1 front view and the design 2 front view are the initial interfaces, and the user can click on each function module in the interface to enter the corresponding function for program operation; the design 1 interface usage state reference diagram and the design 2 interface usage reference state diagram are the reference interfaces of the design 1 front view and the design 2 front view in the actual use process.