61 results about "Shape matching" patented technology

The invention provides an intelligent boxing method and system. The intelligent boxing method comprises the steps of obtaining boxing task information and generating a boxing scheme. The boxing task information comprises the size, the weight, the stacking limitation, the number and the priority of each cargo, and the size, the bearing capacity and the occupation state of each loading unit. And under the condition that the size, bearing and stacking constraint conditions are met, a plurality of candidate boxing combinations are generated, the loading utilization rate, the residual space distribution and the shape matching degree are evaluated based on a preset optimization target, and an optimal scheme is selected. The system comprises an input terminal, a task information receiving module, a data storage module, a task and scheme storage module, an operation processing module and a final boxing scheme generation module. According to the method, multi-dimensional constraint matching and weight balance are considered, and space waste and transportation risks are avoided; the maximum greedy algorithm and the adaptive large neighborhood search optimization are combined to realize the combination of automation and experience. The method can be expanded to batch task scheduling and grouping sequencing, so that the calculation complexity is reduced, and the overall boxing and transportation efficiency is improved.

The invention discloses a whole-process vascular interventional operation training method and system based on a virtual reality technology, and the method comprises the steps: firstly, developing a vascular interventional mechanics and collision simulation module, and achieving the deformation simulation of a blood vessel and a guide wire through the combination of position dynamics, a region shape matching technology and a Cosseerat elastic rod model, the collision between the blood vessel and the guide wire is treated by adopting a wide-to-narrow three-layer progressive collision detection method; secondly, constructing an immersive virtual operation scene through model construction and rendering optimization; visual angle roaming, instrument operation and interface interaction are fused, and multi-mode interaction control driving intervention training is achieved; finally, based on a'module-event 'dual-drive framework, operation tasks such as anesthesia, puncture, radiography, intervention, stent release and hemostasis are sequentially connected in series through a unified state machine, and whole-process training is achieved. The accuracy and stability of blood vessel and guide wire simulation are improved, the training immersion sense is enhanced, interventional operation whole-process training is achieved, and high teaching and practical value is achieved.

The invention discloses a power transmission line mountain fire smoke detection method and system, and the method comprises the steps: segmenting a mountain fire smoke candidate region in a to-be-detected power transmission channel picture through a pre-trained semantic segmentation model, and calculating a semantic segmentation confidence score; for each mountain fire smoke candidate area, calculating a shape similarity score through a shape matching method, calculating a position confidence score through a position function, and calculating a color confidence score through color distribution comparison; and carrying out weighted summation on the semantic segmentation confidence score, the shape similarity score, the position confidence score and the color confidence score to obtain a final smoke confidence score, and comparing the final smoke confidence score with a preset threshold to judge whether the corresponding mountain fire smoke candidate region is mountain fire smoke. According to the technical scheme provided by the invention, the forest fire smoke condition in the power transmission line channel picture can be effectively identified, the misidentification conditions of pond smoke, chimney smoke, cloud and mist and the like are obviously reduced, and the method has a wide application scene.

The invention relates to the technical field of digital people, and provides a method and equipment for generating a digital people video, which can be applied to a digital marketing scene. According to the method, the generation of the digital human video is divided into an audio generation process and a video generation process, when the audio is generated, a target text, an emotion parameter and a reference audio are taken as input, and the target audio of the target text is broadcasted by the sound of a reference person in the reference video and a set emotion, so that sound cloning is realized, the degree of violation of the generated digital human video is reduced, and the user experience is improved. And the text features are extracted from two dimensions of characters and pronunciation, so that the pronunciation accuracy during sound cloning is ensured. When the video is generated, the cloned target audio and the cloned reference video are used as input, and the fidelity of the digital human video is improved through expression and mouth shape matching, so that a reference person can quickly and efficiently generate vivid digital human videos with different broadcast contents only by shooting one reference video without shooting one by one, thereby reducing the manufacturing cost of the digital human video, and improving the user experience. And the video production efficiency is improved.

The invention belongs to the technical field of overhead line butt joint detection, and particularly discloses and provides a method for detecting overhead conductor steel strands after butt joint, and the method comprises the steps: building and correcting a digital twinborn model of a to-be-detected wire clamp based on a CAD drawing and three-dimensional scanning data of the to-be-detected wire clamp; extracting interface geometric parameters and identifying actual shapes of the interface geometric parameters; generating an initial gridding detection path based on a shape matching grid node distribution strategy; collecting a first ultrasonic data set according to the detection path and identifying an abnormal region; dynamically adjusting the grid density according to the abnormal index of the abnormal region, generating an updated detection path, and collecting a second ultrasonic data set; the first and second ultrasound data sets are combined to form a final detection data set. Through model correction and adaptive path planning, the defect of a fixed point distribution mode is overcome, the transformation from wide screening to accurate focusing is realized, and the defect identification accuracy and the evaluation reliability are remarkably improved.

The invention discloses a robot path recognition method and system, and belongs to the technical field of robots, and the system comprises an acquisition module, a recognition module, a coffee cup shape recognition result acquisition module, a coffee cup position recognition result acquisition module, a determination module, a position posture acquisition module and a path recognition module. The method comprises the following steps: acquiring an environment image including a coffee making area, and performing multi-stage identification and processing on the image, including determining candidate block images of suspected coffee cups, obtaining coffee cup structure standard parameters for shape matching, and identifying a coffee making area range for position judgment. And finally, fusing the shape and position identification results to determine a target coffee cup so as to confirm the moving path of the coffee cup. The method can effectively solve the problem that in the prior art, due to the fact that coffee powder is attached to a camera lens, an image is blurred, coffee cup recognition is inaccurate, and path planning deviation is caused.

The invention provides a three-dimensional effect rendering method and device and electronic equipment, and the method comprises the steps: carrying out the zooming processing of a target surface patch according to the model size of a target three-dimensional model and the camera orientation of a virtual camera, obtaining a zoomed target surface patch of which the size is matched with the model size, and keeping the zoomed target surface patch facing the virtual camera; stretching the scaled target surface patch according to the model shape of the target three-dimensional model to obtain a stretched target surface patch of which the shape is matched with the model shape; and moving the stretched target patch to the position of the target three-dimensional model in the virtual scene, deleting the target three-dimensional model in the virtual scene and rendering the stretched target patch to obtain a rendered target patch so as to simulate the three-dimensional effect of the target three-dimensional model through the rendered target patch. According to the method, the target surface patch is stretched in the camera space according to the visual angle, so that the surface patch fitting three-dimensional effect is realized, and a better three-dimensional effect is realized with extremely low rendering performance consumption.

The application belongs to the field of intelligent human-computer interaction, and relates to a kind of intelligent writing and correcting method and system, comprising: utilizing flexible pressure sensor matrix and coordinate positioning system, the multidimensional data of sensing input pen writing, and constructing four-dimensional writing characteristic space;Adopt three-level correcting system, the logical reasoning verification of answer is carried out through depth semantic understanding model;The three-level correcting system successively includes OCR character shape matching, semantic rectification based on large language model and intelligent correction based on process reward model;Cognitive diagnosis model is introduced, and the degree of hesitation of answering is judged by analyzing answering index;Fusion question solving information, the knowledge point of question is identified using large model, and according to the question answering condition, the weak point of knowledge mastery is inferred;With the intelligent writing capture technology based on multi-modal sensor fusion, the writing information is accurately collected, and the intelligent correcting integrated method is constructed combined with cognitive diagnosis model, the efficient identification and accurate correction of writing content are realized.

The application discloses a power transmission line mountain fire smoke detection method and system, comprising the following steps: for the power transmission channel picture to be detected, a pre-trained semantic segmentation model is used to segment out the mountain fire smoke candidate area in the picture and calculate the semantic segmentation confidence score; for each mountain fire smoke candidate area, the shape similarity score is calculated through a shape matching method, the position confidence score is calculated through a position function, and the color confidence score is calculated through color distribution comparison; the semantic segmentation confidence score, the shape similarity score, the position confidence score and the color confidence score are weighted and summed to obtain the final smoke confidence score, which is compared with a preset threshold to determine whether the corresponding mountain fire smoke candidate area is mountain fire smoke. The technical scheme provided by the application can effectively identify the mountain fire smoke condition in the power transmission line channel picture, and significantly reduce the misidentification conditions such as pond smoke, chimney smoke and cloud and mist, and has a wide application scenario.

The invention relates to a precise infinitesimal displacement photoelectric measurement system and a precise infinitesimal displacement photoelectric measurement method, and belongs to the technical field of photoelectric measurement, and the precise infinitesimal displacement photoelectric measurement system comprises a curvature flow contour extraction module, a geodesic constraint positioning module, a Riemann optimization module and a displacement calculation module. Then parameterized representation and optimization are carried out on the light spot contour by using a curvature flow theory to generate high-quality contour description data; constructing a geodesic distance field based on a differential geometry principle, identifying a local maximum point as a candidate circle center, and evaluating the shape matching degree of each candidate circle center to determine an optimal candidate circle center; converting a sub-pixel positioning problem into an optimization problem on a Riemannian manifold, and determining a target coordinate of sub-pixel precision through gradient descent of a parameter space; finally, target displacement change between adjacent image frames is calculated, a micro displacement measurement result is output, and the displacement measurement precision is improved to 0.01 pixel and is improved by 5-10 times compared with a traditional method.

The application discloses a polygon decomposition method, an electronic device and a computer readable storage medium. The polygon decomposition method comprises the following steps: obtaining a to-be-decomposed polygon of an integrated circuit layout; obtaining a plurality of candidate polygon templates from a template library; performing shape matching processing and polygon update iteration processing on the to-be-decomposed polygon and the candidate polygon templates to obtain a shape matching result; and performing polygon decomposition processing on the to-be-decomposed polygon according to the shape matching result to obtain a trapezoidal set for manufacturing a mask after decomposition. According to the scheme of the embodiment of the application, the polygon in the integrated circuit layout can be efficiently decomposed, thereby reducing the decomposition time consumption and improving the universal applicability.

The invention discloses an electrical secondary drawing small target detection method, system and device based on an improved Faster R-CNN, and a medium, and belongs to the technical field of drawing small target detection. On the basis of optimization technologies such as a lightweight conditional generative adversarial network, multi-modal feature extraction and fusion, an adaptive Anchor mechanism and shape matching loss function, a dynamic receptive field and the like, the electrical secondary drawing small target detection task is completed with high precision and high efficiency.

The invention discloses a workpiece contour detection method and a related device. The method comprises the following steps: acquiring a pre-dispensing image and a post-dispensing image of a target workpiece; performing shape matching on the image before dispensing according to the contour feature point distribution template to obtain matching data before dispensing; acquiring a grid matching range according to the matching data before dispensing; performing segmentation processing on the dispensed image to obtain a current contour area and a current glue path area; and according to the grid feature point distribution template, performing shape matching on the current contour area and the current glue path area in a grid matching range, and obtaining current contour data of the target workpiece in the image after glue dispensing. According to the method, the image of the target workpiece before glue dispensing and the image of the target workpiece after glue dispensing are respectively collected, the target workpiece is primarily positioned according to the image before glue dispensing, the image after glue dispensing is secondarily positioned according to the result of the primary positioning, and the positioning error caused by tiny offset in the glue dispensing process is made up by secondarily positioning the target workpiece.

The invention provides an automatic drawing auditing method based on deep learning semantic segmentation and shape matching, and the method comprises the steps: converting a to-be-recognized drawing from a vector format to a bitmap format, obtaining an image corresponding to the to-be-recognized drawing, inputting a pre-constructed target recognition model for recognition, and obtaining a first target object of the to-be-recognized drawing, performing morphological optimization to obtain the contour shape and geometric attribute information of the first target object; selecting a target contour shape from a pre-constructed standard shape library, and calculating an intersection-to-union ratio of the contour shape to the target contour shape; if the intersection-union ratio is larger than the intersection-union ratio threshold value of the first target object, compliance auditing is conducted on the first target object, a compliance auditing result is obtained, and a structured auditing report is generated, so that the target objects in the drawings of various formats are rapidly and accurately recognized, the target objects are verified based on a shape matching method, and the verification efficiency is improved. And the efficiency, flexibility and accuracy of engineering drawing auditing are improved.

The application belongs to the technical field of overhead line butt joint detection, and specifically discloses an overhead conductor steel strand butt joint detection method, which comprises the following steps: constructing and correcting a digital twin model of a to-be-detected clamp based on CAD drawings and three-dimensional scanning data of the to-be-detected clamp; extracting interface geometric parameters and identifying the actual shape thereof; generating an initial grid detection path based on a shape matching grid node distribution strategy; collecting a first ultrasonic data set according to the detection path and identifying an abnormal area; dynamically adjusting the grid density according to the abnormal index of the abnormal area, generating an updated detection path, and collecting a second ultrasonic data set; and merging the first and second ultrasonic data sets to form a final detection data set. Through model correction and adaptive path planning, the application overcomes the shortcomings of a fixed point distribution mode, realizes a transition from extensive screening to accurate focusing, and significantly improves the defect identification accuracy and evaluation reliability.

The application provides a trackless navigation texture information redundancy analysis method, comprising: processing original image data of a current wear area by using an edge detection algorithm to obtain wear boundary contour coordinates and gray distribution data; extracting boundary coordinate point sets from a reliable anchor point area and determining an optimized update frequency value according to the position and shape matching degree of the boundary coordinate point sets and historical path map data; incrementally updating the path map by using the optimized update frequency value, integrating the gray distribution data of the reliable anchor point area and the texture detail loss degree value, and generating an enhanced positioning reference data set; updating the enhanced positioning reference data set according to supplementary data and performing periodic matching degree evaluation according to the optimized update frequency value to maintain long-term positioning consistency.

This invention discloses a traffic sign detection method based on spatial completion and multi-scale focusing, comprising: performing category balancing enhancement on the traffic sign dataset to construct a balanced dataset; embedding a feature complementarity mapping module in the Q4 layer of the YOLOv12 backbone network, fusing color and spatial information through channel segmentation and bidirectional attention mechanism to complete the features of small targets; embedding multi-scale convolutional attention modules in the P3, P4 and P5 layers of the detection head respectively, using differentiated strip convolution kernels and color attention mechanism to achieve feature focusing of traffic signs at multiple scales; using a composite loss function combining SIoU loss and shape matching loss for network training optimization; performing color enhancement, multi-scale feature extraction and non-maximum suppression algorithm post-processing in the inference stage to output the traffic sign category, bounding box and confidence score; this invention significantly improves the accuracy of small target detection and multi-scale adaptability, meeting the real-time detection needs in complex traffic scenarios.

A workpiece detection system capable of detecting a workpiece accurately and rapidly comprises: a three-dimensional sensor that measures a three-dimensional shape of an object in a field of view; and an information processing device that uses a visually recognizable shape in each point of view of a three-dimensional model as a search target shape, and, when a matching partial shape that matches the search target shape is found from the three-dimensional shape measured by the three-dimensional sensor, outputs the matching partial shape as a search result. The information processing device excludes a part of the search target shape or a part of the search result on the basis of a preset condition.

A vehicle control system incorporates a variety of neural networks used to compute multiple wheel slip estimates for multiple wheels based on wheel speed measurements for each wheel and outputs from other vehicle sensors, such as an IMU or GNSS receiver. Separate neural networks estimate the wheel slip for each wheel. These wheel slip estimates can be used to select wheel speed measurements to update a Kalman filter. The Kalman filter further updates its state based on GNSS measurements that were not rejected according to a rejection algorithm that includes shape-matching with respect to a trajectory estimated by the Kalman filter.

The present application provides a kind of personnel identification and counting method and system based on single vision, comprising: using latitude correction algorithm to carry out equidistant cylindrical development to wide-angle image of single vision, eliminate edge human distortion;Personnel detection model is trained through data set, and the feature response of occluded target is adaptively enhanced;The virtual trajectory of the occluded target is maintained by establishing a "parent-child association" state machine;Trajectory matching algorithm is used to perform time sequence shape matching on the trajectories inside and outside the door, accurately retrieve the lost exit target due to occlusion and perform counting compensation.The present application realizes high-precision counting of complex occlusion behaviors such as side by side and close contact under the premise of using only single vision and without depth sensor, with a counting error rate of less than 2%, significantly reducing the deployment cost of the system.

The invention discloses a bracket-free invisible orthodontic appliance based on direct 3D printing and a digital design and manufacturing method of the bracket-free invisible orthodontic appliance. According to the method, a digital closed-loop process is constructed; firstly, a correction target is set through intraoral scanning and digital tooth arrangement; constructing a smooth envelope space of the appliance by utilizing a contraction wrapping algorithm; accurately segmenting the dental crown by adopting an AI technology based on PointNet + + so as to define a force boundary; generating an appliance digital model with an accurate form and stable mechanics through a thickness control and edge optimization algorithm; finally, based on the DLP technology, the orthodontic appliance is directly printed with biocompatible resin, and the performance and safety of the orthodontic appliance are ensured through strict post-treatment such as secondary curing. According to the method, a traditional film pressing process is omitted, accumulative errors are eliminated fundamentally, personalized gradient design of mechanical properties of the appliance can be realized through process control, and an invisible correction technology is marked to step from shape matching to function matching.

The application provides a trackless navigation texture information redundancy analysis method, comprising: processing original image data of a current wear area by using an edge detection algorithm to obtain wear boundary contour coordinates and gray distribution data; extracting boundary coordinate point sets from a reliable anchor point area and determining an optimized update frequency value according to the position and shape matching degree of the boundary coordinate point sets and historical path map data; incrementally updating the path map by using the optimized update frequency value, integrating the gray distribution data of the reliable anchor point area and the texture detail loss degree value, and generating an enhanced positioning reference data set; updating the enhanced positioning reference data set according to supplementary data and performing periodic matching degree evaluation according to the optimized update frequency value to maintain long-term positioning consistency.

The invention relates to the technical field of positioning methods, in particular to a carbon fiber plate automatic positioning method and system based on visual inspection, and the method comprises the steps: obtaining an initial image of a carbon fiber plate, and extracting edge points in the initial image to form a candidate edge point set; constructing a corresponding analysis window for each edge point in the candidate edge point set to obtain a gradient coherence index about the edge points; constructing an edge section related to the edge points, and calculating to obtain a texture consistency index of the edge points based on the variance of the gradient coherence indexes of all the edge points on the edge section; carrying out weighted fusion on the gradient amplitude and the texture consistency index of the edge point to obtain a significance weight of the edge point; and in a shape matching algorithm, taking the significance weight of the edge point as a weighting coefficient of a matching score, and obtaining a positioning result of the carbon fiber plate. According to the invention, the carbon fiber plate can be accurately positioned in a complex industrial scene.

The present application relates to a precise micro-displacement photoelectric measurement system and method thereof, belonging to the technical field of photoelectric measurement, comprising a curvature flow profile extraction module, a geodesic line constraint positioning module, a Riemann optimization module and a displacement calculation module. The system first collects light spot images and performs pretreatment, then uses the curvature flow theory to parameterize and optimize the light spot profile, generating high-quality profile description data; then, based on the principle of differential geometry, a geodesic distance field is constructed, local maximum points are identified as candidate circle centers, and the shape matching degree of each candidate circle center is evaluated to determine the best candidate circle center; then, the sub-pixel positioning problem is converted into an optimization problem on the Riemann manifold, and the target coordinates of sub-pixel accuracy are determined through gradient descent in the parameter space; finally, the target displacement change between adjacent image frames is calculated, and the micro-displacement measurement result is output. The present application improves the displacement measurement accuracy to 0.01 pixels, which is 5-10 times higher than the traditional method.

The invention discloses a method and device for determining the hierarchy of tubular tissue, a surgical robot and electronic equipment. The method includes acquiring a first three-dimensional image, the first three-dimensional image including a first tubular tissue. Based on the first three-dimensional image, a first linear diagram of the first tubular tissue is obtained, the first linear diagram comprises a first linear structure, the shape of the first linear structure is matched with that of the first tubular tissue, and a point in the first linear structure is the center of the cross section of the first tubular tissue. And obtaining at least two first branches of the first tubular tissue based on the first linear structure. Based on the first three-dimensional image, obtaining at least two pieces of first level information of the at least two first branches, the first level information being in one-to-one correspondence with the first branches, and the first level information indicating radiuses of the first branches; according to the method, at least two pieces of first level information of at least two first branches of the first tubular tissue can be obtained, so that the information of the tubular tissue can be enriched.

The application discloses a multi-target perception fusion method in a multi-unmanned aerial vehicle search process. First, an unmanned aerial vehicle A uses a camera to search and track a target, obtains a target image position and number, and calculates a three-dimensional position of each target. If no new target appears, target information in a fusion target pool is updated; otherwise, the information component of unmanned aerial vehicle A is deleted from the fusion target pool, a target pool subset to be matched is obtained, an adjacent relationship bipartite graph is constructed, the bipartite graph is simplified, and matching is performed by taking the maximum matching number and the minimum shape gap as a correlation measure. Finally, an updated multi-target fusion result is calculated from each target information in the fusion target pool. The application can realize multi-target perception and fusion in a multi-unmanned aerial vehicle search process, retains shape features of original calculation results, uses an adjacent judgment and a shape matching strategy, and solves the problem of a high correlation matching error rate of a traditional matching fusion algorithm when a target is low-speed, gathered, and the like.

Embodiments relate to a system for determining when an object should be an object-of-interest. An input module receives an image scene captured by an image capture device. A processor performs a shape analysis technique, wherein a first processing module scans the image scene to identify an object, a second processing module identifies a shape of interest of the object, a third processing module compares the shape of interest to a reference shape, and a fourth processing module classifies the object as having a target characteristic when the shape of interest matches the reference shape. The processor compares an interior area of an image curve of the classified object to an interior area of an image curve of the reference shape to generate a scale factor, and designates the classified object as an object-of-interest based on the scale factor.

A method for three-dimensional (3D) registration of three-dimensional virtual models, performed by a computing device, according to one embodiment of the present disclosure, comprises the steps of: generating a 3D interior digital model of an indoor space using a plurality of datasets collected in the indoor space; generating a 3D exterior digital model of an outdoor space using a plurality of image sets collected in the outdoor space; generating outline-based 3D volumetric models for the 3D interior digital model and the 3D exterior digital model; and performing registration between the 3D interior digital model and the 3D exterior digital model on the basis of external shape matching between a 3D interior volumetric model and a 3D exterior volumetric model.

The invention discloses a partial fingerprint identification method based on multistage feature fusion, and relates to the field of image processing and mode identification, and the method comprises the steps: carrying out the preprocessing of an input fingerprint image, and obtaining a preprocessed fingerprint image; based on the preprocessed fingerprint image, first-level curvature features, second-level minutia features and third-level ridge line shape features are extracted; retrieving and classifying the fingerprint template library through the first-level curvature features to obtain a candidate fingerprint set; on the basis of the candidate fingerprint set, performing minutia point matching and ridge line shape matching through the second-level minutia point features and the third-level ridge line shape features to obtain minutia point matching scores and ridge line shape matching scores; and calculating a final matching score in combination with adaptive weight fusion to obtain a fingerprint matching judgment result. According to the method, the efficiency and precision of partial fingerprint identification and the adaptability to images with different qualities are improved by fusing multi-level features such as curvature, minutiae and ridge line shapes and adopting an adaptive weighting strategy.

The application discloses a kind of 3D character visual detection defect device and method based on double laser camera, the method includes: step S1, laser profile picture of the workpiece to be detected irradiated by laser is respectively collected using first laser camera and second laser camera, obtain first point cloud and second point cloud, the first laser camera and second laser camera use positive and negative opposite installation mode;Step S2, first point cloud and second point cloud are spliced, and a point cloud with higher precision and more complete information is synthesized;Step S3, character content is recognized using OCR technology to the spliced point cloud, and the position of character is further confirmed and obtained using shape matching, whether the position of character is within the allowable tolerance range is tested, and after obtaining the content and position of character, difference comparison is carried out between actual character and standard character, to detect whether actual character exists defect.