99 results about "Visual flow" patented technology

The invention provides an end-to-end automatic driving track generation method and system, computer equipment and a medium, and belongs to the field of path intelligent planning, and the method comprises the steps: obtaining traffic environment three-dimensional perception information and a natural language instruction; converting the traffic environment three-dimensional perception information to obtain a structured semantic mark, and adjusting the weight of the structured semantic mark through a natural language instruction; based on the weight of the structured semantic mark, visual flow features are extracted from the structured semantic mark, and language flow features are extracted from the natural language instruction; based on a cross-modal attention mechanism, the visual flow features and the language flow features are fused, fusion features are obtained, and a simulation track is generated; real-time collision time is calculated, when the real-time collision time is larger than a collision time threshold value, the simulation track is corrected based on physical constraints and a traffic regulation library, and a corrected driving track is obtained. The automatic driving simulation track constructed by the method conforms to the intention of a user, and the system reliability and the man-machine cooperation efficiency are improved.

The invention relates to an unmanned aerial vehicle self-adaptive wind-resistant flight control method and system based on multi-mode environment perception. The method comprises the steps that a miniature wind speed and direction sensor array obtains real-time wind speed and wind direction information of the surrounding environment of an unmanned aerial vehicle; the inertial measurement unit obtains real-time attitude angle, angular velocity and acceleration information of the unmanned aerial vehicle; the visual flow sensor obtains real-time image data of the surrounding environment of the unmanned aerial vehicle; the data fusion and wind field estimation module receives multi-source data collected by the miniature wind speed and direction sensor array, the inertial measurement unit and the visual flow sensor, carries out fusion processing on the multi-source data based on an extended Kalman filtering algorithm, and predicts to obtain predicted wind field information in a future short time window; the flight control core module adopts an adaptive sliding mode control algorithm to calculate a compensation control quantity for counteracting wind disturbance, and performs real-time control on the unmanned aerial vehicle based on the compensation control quantity; and the wind resistance and the operation reliability of the unmanned aerial vehicle in a complex dynamic environment are improved.

The invention provides a service robot cross-modal user intention analysis method and system. The method comprises the following steps: firstly, acquiring and analyzing a voice instruction sequence and a visual flow containing a gesture, fusing a task target object and a gesture pointing direction to generate an intention hypothesis, and then projecting the intention hypothesis to a knowledge graph of an environment with a body; the method comprises the following steps: acquiring an intent hypothesis of a user, querying a candidate object set simultaneously matched with spatial constraints and semantic constraints of the intent hypothesis, when ambiguity exists in the candidate object set, generating an inquiry instruction for eliminating the ambiguity according to a relation path in a knowledge graph of the body environment, and finally analyzing and confirming a final user intent according to the response of the user to the inquiry instruction; according to the technical scheme provided by the invention, the ability of the robot to cope with uncertainties such as unknown reference and environment shielding in a real scene is enhanced, the interactive experience closer to the human cognitive level is realized, and the interactive efficiency and satisfaction of the user in a complex environment are also improved.

The invention relates to the field of image processing, in particular to an industrial feeding anomaly recognition method based on visual flow detection, and the method comprises the steps: obtaining an image sequence for optical flow calculation through the collection and preprocessing of an image sequence of an industrial feeding port; performing nonlinear fusion on the pixel brightness value and the time brightness change rate to obtain a highlight suppression factor; carrying out distribution analysis on the local gradient structure tensor characteristic value to obtain a gradient structure confidence factor; performing joint weighting on the highlight suppression factor and the gradient structure confidence factor to obtain a dynamic space-time confidence weight; weighted optical flow calculation and variance threshold judgment are carried out on the dynamic space-time confidence coefficient weight, a feeding abnormal state recognition result is obtained, and therefore the problems of optical flow calculation distortion and abnormal misinformation caused by mirror surface highlight in the SMT micro component feeding process are solved.

The invention discloses a finance and taxation field agent workflow arrangement method and system based on a natural language, and the method comprises the steps: S1, widely collecting workflow arrangement cases of a finance and taxation field typical business scene, carrying out the detailed analysis of each case, and extracting a key business process and node information, S2, taking all structured workflow data as nodes, and carrying out the calculation of the workflow arrangement cases, constructing a finance and tax workflow knowledge graph by taking the semantic similarity, the function multiplexing relationship and the business process dependency relationship among all the structured workflow data as edges; s3, based on structured data and natural language description corpora constructed by the finance and tax workflow knowledge graph, performing training optimization on the base large language model by adopting a domain self-adaption and task specific fine tuning technology; s4, a user inputs a natural language demand through the interactive interface, and the natural language demand is processed by using the demand analysis agent, the retrieval agent and the arrangement agent; and S5, displaying the generated draft workflow in a visual flow chart form.

The invention provides a fire prevention and control method and system using computer vision, and relates to the technical field of computer vision, and the method comprises the steps: firstly obtaining a monitoring scene visual flow containing visible light and infrared thermal imaging images, and carrying out the visual flow segment correlation modeling of the monitoring scene visual flow to obtain a correlation chain cluster; a fire evolution feature set is obtained through feature linkage evolution analysis, a fire prevention and control response instruction containing prevention and control operation guidance information is generated based on the fire evolution feature set, the fire prevention and control response instruction is sent to an execution terminal, feedback is received, and comprehensive monitoring and effective prevention and control of the fire are achieved. Fire prevention and control efficiency and reliability are improved, and fire loss is reduced.

The invention relates to the technical field of computers and simulation analysis, in particular to a flow field simulation analysis method in the starting process of a water turbine, which comprises the following steps of: performing geometric pretreatment and grid pretreatment on a movable guide vane of the water turbine, and constructing a simulation environment; constructing a basic flow simulation model of the movable guide vane of the water turbine, adding a turbulence equation to model a turbulence phenomenon in the operation process of the water turbine, and inputting the turbulence phenomenon into the simulation environment for flow field simulation; a water turbine and a steady-state solver are initialized, and transient simulation results of flow velocity and pressure in the starting process of the water turbine in the simulation environment are solved in combination with analysis of the starting transition process of the water turbine until calculation convergence is achieved; and post-processing the calculation result, and outputting a visual flow field result. The variable speed transient simulation process of the water turbine starting process can be achieved, and high-precision transient numerical simulation of flow field changes in the water turbine starting process is achieved.

The invention discloses a naked-eye 3D augmented reality interactive display system, and relates to the technical field of naked-eye 3D display and reality interaction. According to the invention, the multi-source depth data acquisition module acquires and fuses a user limb depth image, the parallax physical depth mapping module completes depth and parallax mapping and visual angle correction, the occlusion relation determination module divides regions to determine the occlusion type, and the adaptive mask layer generation module generates a dynamic smooth mask layer. The shielding effect fusion display module is used for overlapping and synthesizing the shielding layer and the multi-view virtual image and then displaying the overlapped and synthesized shielding layer and the multi-view virtual image; the problems that in naked eye 3D interaction, the occlusion relation between the limbs of the user and the virtual object is not accurate, and the vision is abrupt are effectively solved, the space consistency and the vision fluency of interaction are remarkably improved, and the real and natural naked eye 3D augmented reality interaction experience is achieved.

The invention belongs to the technical field of relay protection practical training and evaluation of a power system, and particularly relates to a relay protection operation coach and evaluation system and method based on AR glasses, and the system comprises an AR intelligent glasses terminal which is worn by an operator and is used for collecting the depth visual flow data of a field environment in real time; an edge computing server which is in communication connection with the AR intelligent glasses terminal and is used for obtaining the visual flow information collected by the AR intelligent glasses terminal, constructing a state sensing model based on a power equipment topological relation and realizing direct semantic level identification of screen cabinet elements; meanwhile, generating a three-dimensional visual operation indicator, a dynamic safety early warning signal and real-time evaluation feedback information, and superposing the three-dimensional visual operation indicator, the dynamic safety early warning signal and the real-time evaluation feedback information in the visual field of the AR intelligent glasses terminal; the cloud management platform is in communication connection with the edge computing server and is used for performing user management, storage and updating of an operation instruction knowledge graph, storage and analysis of historical evaluation data and unified allocation of system resources; the defects of a traditional training and evaluation system are overcome.

The invention relates to the technical field of multi-scene dynamic orchestration, in particular to a multi-scene-based orchestrable unified preprocessing rule method and system, and the method comprises the steps: carrying out the dynamic matching of a rule according to scene information, employing a visual rule orchestration engine, and employing a micro-service architecture design; the method has the beneficial effects that different service scenes can be covered through the modular rule base and the dynamic configuration capability, repeated development of a traditional single scene preprocessing system is avoided, and the technology reuse rate is improved. Visual flow arrangement is adopted, a user is allowed to customize a rule execution sequence, conditional branches and combinatorial logic, complex business demand changes are flexibly dealt with, and the technology coupling degree is reduced.

The invention discloses a space-time image texture angle detection and discrimination method and system, and belongs to the field of visual flow measurement instruments. According to the design, a Zynq series processor with an ARM + FPGA architecture is used as a core, and a system module comprises a PS host control end, a PL end texture enhancement module, a two-dimensional Fourier transform module, a frequency spectrum logarithm transform module, a Gaussian filter module and an image segmentation and texture angle detection and judgment module. Wherein the texture enhancement module inhibits noise interference and enhances the continuity of effective textures; the two-dimensional Fourier transform module converts the information of the spatial domain image to a frequency domain; the frequency spectrum logarithmic transformation module is used for carrying out logarithmic magnitude spectrum calculation on the transformed spectrogram so as to improve the visibility of a low-amplitude component; and the image segmentation and texture angle detection and discrimination module carries out angle detection and discrimination after effective and invalid signals are separated, and finally outputs an angle detection result. The method can be applied to a river surface flow velocity measurement system based on a space-time image velocity measurement method, and the adaptability and efficiency of flow measurement in complex scenes can be improved.

The invention is suitable for the technical field of hydrographic survey, and provides a millimeter wave radar speed measurement calibration method based on visual flow measurement, which comprises the following steps: acquiring data, constructing a database and preprocessing an image, performing target detection on the preprocessed image based on YOLO v8, performing region segmentation on a water surface region after target extraction is completed, and obtaining a millimeter wave radar speed measurement calibration result. Visual flow measurement calculation is carried out based on an optical flow method, when optical flow calculation is carried out, calculation should be carried out in each area, space-time synchronization is carried out on a visual flow measurement result and a flow velocity measured by a millimeter wave radar, credible areas are screened, abnormal data are processed, and linear coefficients are fitted for each credible area k through a least square method; according to the method, under the condition that millimeter wave radar speed measurement single-point measurement is limited, area speed measurement information is provided through visual flow measurement, and the problem that the millimeter wave measurement range is insufficient is solved.

The invention relates to the field of computer vision and artificial intelligence, in particular to a multi-modal fusion document image classification method based on multi-branch deep convolution and hierarchical semantic modeling. According to the method, visual and text information of a document is co-processed through a double-flow architecture; a visual semantic feature of a document image is efficiently extracted from a visual flow by adopting a lightweight convolution operation and multi-scale feature fusion mechanism; an original text is obtained from a text stream through an optical character recognition technology, text error correction and word embedding extraction are carried out through a fine tuning language model, word-level and sentence-level context modeling is realized by inputting a hierarchical semantic coding network, and document-level features are generated. And high-precision document image classification is realized by fusing the double-flow feature vectors and combining a full-connection layer. Experimental results show that the method has an excellent multi-modal feature fusion effect, relatively high classification precision and strong robustness to complex document scenes in a document image classification task, and is suitable for application scenes of various document image classification.

This invention relates to the field of construction safety monitoring and intelligent visual analysis technology, specifically a wiring-free construction safety monitoring system based on visual algorithm analysis. The system includes: an independent power supply module, a visual perception module, a scene risk topology assessment module, a computing-risk coupling scheduling module, a multi-level wake-up execution module, and a context-related early warning output module. It collects initial visual flow data, remaining power, and predicted charging power of the target monitoring area; divides the topology regions into different risk levels through semantic segmentation and assigns risk weights; dynamically generates computing power scheduling instructions containing the target sampling frame rate and target model complexity; outputs the target violation event identification results; and generates the final early warning result by combining the spatial inclusion relationship between the occurrence location and the topology region boundary. This achieves priority protection for high-risk spatiotemporal nodes and reduces ineffective energy consumption and invalid alarms in low-risk scenarios.

Generating and running computer vision pipelines for processing images and / or video. A user may select blocks for the computer vision pipeline, including image transformation blocks that transform images and / or video, and prediction blocks that detect objects or classes of objects in images and / or video. The user may specify an input source for the images and / or video and an output destination for the computer vision pipeline. Upon activation, the computer vision pipeline receives input images and / or video. The input images and / or video are transformed using the image transformation block to produce transformed images and / or video. Objects or classes of objects in the transformed images and / or video are detected using the prediction block to produce detected objects or classes of objects. The detected objects or classes of objects are transmitted to the output destination.

The invention aims to provide a gas turbine blade unstable flow visualization testing method, and belongs to the technical field of gas turbine experimental testing. Comprising the following steps: inputting boundary conditions and geometric conditions of a calculation model; numerical simulation flow field data under the condition are obtained through CFD calculation; if yes, the next step is carried out, and if not, a higher-quality grid is generated and returned to the encrypted grid, and CFD numerical simulation calculation is carried out again; selecting a proper resolution ratio based on an actual demand; generating a data source quantity and obtaining CFD calculation data according to the data source quantity; and outputting the three-dimensional transient visual flow field at the moment obtained by the checked high-precision CFD numerical simulation. The actual working condition of the gas turbine blade can be simulated, the test error of an actual instrument under the severe working condition is avoided, and the test difficulty is reduced. The precision of CFD numerical simulation is optimized, and the error is reduced, so that the credibility of the three-dimensional visualization cloud picture is improved.

The utility model discloses a visual flow adjusting device for feeding nitrogen during glue making, which comprises a glue making tank gas inlet pipe, a transparent pipe outer supporting pipe, a lower connecting flange pipe, a gas inlet valve and a notch groove formed in one side of the transparent pipe outer supporting pipe which are sequentially and hermetically connected from top to bottom, the transparent inner pipe is embedded in the transparent pipe outer supporting pipe and arranged at the position where the notch groove is located, the upper net plate is arranged between the glue making tank air inlet pipe and the transparent pipe outer supporting pipe, the lower net plate is arranged between the transparent pipe outer supporting pipe and the lower connecting flange pipe, and the flow ball is arranged in the transparent inner pipe and arranged between the upper net plate and the lower net plate. A plurality of mesh holes are formed in the upper mesh plate and the lower mesh plate; the air inlet valve is externally connected with nitrogen; the transparent inner tube is connected with the transparent tube outer supporting tube in a sealed mode. According to the scheme, the device has the advantages of simple structure, intuition, reliability and the like, and has very high practical value and popularization value in the technical field of glue making.

The invention discloses a logging instrument drilling fluid outlet flow monitoring system and method based on machine vision, and belongs to the technical field of drilling fluid detection. Collecting data; carrying out image convolution processing; extracting features; calculating a visual modal visibility probability; calculating a flow modal probability; calculating a pressure modal probability; determining a comprehensive cutoff probability based on multi-modal probability fusion; and determining a risk level and a hierarchical response mechanism based on the comprehensive cutoff probability. According to the method, three heterogeneous modes of vision, flow and pressure are fused, so that the problem that the reliability in the prior art is still difficult to meet the real-time decision-making requirement under the complex working condition is solved, the system reliability under the severe working condition is improved, and the technical effect of reducing the false alarm rate and the missing report rate is achieved.

The invention relates to the technical field of computers, provides an AI collaborative code generation method based on flow arrangement, and innovatively realizes full-flow automation from demand acquisition to complete code engineering through a visual flow arrangement of a low-code platform and a multi-role collaborative mechanism of a large language model. And demand iteration is supported through a dynamic optimization technology. The core objective of the invention is to significantly improve the development efficiency, reduce the technical threshold, and ensure the consistency and expandability in a complex development scene.

The invention provides a multi-mode document processing method, system and equipment, and the method comprises the steps: obtaining a multi-source heterogeneous file, and converting the multi-source heterogeneous file into a standard document; performing layout element analysis on the standard document, and determining a section set; according to each document semantic block in the section set, analyzing the spatial relationship, visual flow and semantic association between the document semantic blocks so as to generate a global content sequence conforming to a reading sequence; constructing an optimal analysis pipeline according to the type of each document semantic block in the global content sequence, analyzing each document semantic block based on the optimal analysis pipeline, and determining an analysis result; and generating the analysis result into structured data, and outputting the structured data. According to the method, the reading sequence is corrected, sequence logic coherence is ensured, and the semantic disjunction problem caused by only relying on the spatial position is solved; according to the method, scattered recognition results are associated and integrated and converted into structured data, so that the problem that information is scattered and difficult to reuse is solved.

Methods, systems, and devices for wireless communications are described. A computer vision pipeline may be implemented that enables segmentation of 3D models. For example, multiple two-dimensional (2D) images may be generated from a three-dimensional (3D) model, and multiple image segmentation masks may be generated based on segmentation operations performed on each 2D image. Backprojection operations may be performed for each image segmentation mask, where a correspondence between respective pixels of each image segmentation mask and respective objects of the 3D model is identified in accordance with the backprojection operations. Further, sets of labels from each image segmentation mask may be merged based on the correspondence, and the respective objects may be associated with a label in accordance with the merging. A segmented 3D model may be generated that corresponds to the original three-dimensional model, where the segmented three-dimensional model includes the respective objects having an associated label.

The invention discloses a visual compiling system for cloud intelligent screen operation chain tracking, and relates to the technical field of intelligent office systems.The system comprises an operation chain logic modeling module, a visual interaction configuration module, a compiling deployment execution module, an abnormity intelligent diagnosis module and a repairing scheme closed-loop module. A structured logic graph is generated and converted into a visual flow chart, runnable codes are automatically generated and deployed, abnormity is accurately diagnosed, an adaptive repair scheme is generated, and whole-process closed-loop management is formed; according to the method, full-process automation from operation collection to code generation is realized by integrating an automatic process module, a structured graph is constructed by relying on a logic dependency algorithm, a configuration threshold is reduced by combining a visual interface, differentiation and offline deployment are supported, the development period is shortened, the maintainability is improved, and meanwhile, the development efficiency is improved. And an anomaly diagnosis and repair closed-loop mechanism accurately locates an anomaly root, a reliable repair scheme is generated, the manual troubleshooting cost is reduced, and the fault response efficiency is improved.

Systems and methods are provided to power video conferencing and remote collaboration with subsymbolic and symbolic artificial intelligence. The autonomous video conferencing systems of this disclosure include one main smart camera and multiple peripheral smart cameras, optionally coupled with one or more smart sensors. Each smart camera is equipped with a vision pipeline supported by machine learning to detect objects and their interactions as well as related changes in gesture and posture, and a virtual director adapted to apply a predetermined rule set consistent with television studio production principles. The main camera is adapted to select and update a focus video stream in real time under the direction of its virtual director and stream the updated focus stream to a user computer. Methods for creating an automated television studio production for a variety of conferencing spaces and special-purpose scenarios with virtual director assistance are provided.

The application provides an IVR flow arrangement method, device and equipment and a storage medium. The method pre-establishes a node database, and a user can generate a node path from a first node to an end node of a flow by using the node database. The coordinates of each node on the node path are calculated by using a coordinate algorithm, the nodes containing the coordinate information are encapsulated, an interactive voice response (IVR) flowchart is generated and displayed, a complete set of IVR flows related to the first node is automatically generated based on the node database and the IVR flowchart, and the efficiency of IVR flow configuration is effectively improved. A visual flow customization environment is provided for the user, operations of the user on the IVR flowchart in the visual flow customization environment are received and processed, IVR flow arrangement data is obtained, and the efficiency and data accuracy of flow arrangement can be greatly improved.

Approaches are disclosed for enhancing frame rate and visual smoothness in real-time video streams through multi-frame interpolation. A classification neural network analyzes two sequential frames, outputting confidence scores that indicate the reliability of motion data for each pixel. These scores determine whether a pixel's motion is accurately described by motion vectors or should be treated as static. The classification results are reused to generate intermediate frames by warping the original frames based on the motion characteristics. Blending weights are calculated by combining warped motion vector confidence values with static values, and a second neural network refines the alignment and blending of candidate frames. This second network predicts intermediate flows and generates new blending weights, which are used to warp and blend the candidate frames, ultimately producing a final interpolated frame that enhances visual smoothness and consistency in the video stream.

The invention provides a time backflow type digital memory presentation method, and relates to the technical field of mobile internet, and the method comprises the steps: obtaining a starting time point and an ending time point which represent a to-be-presented memory time range; calculating to obtain a total time difference through the starting time point and the ending time point; based on the total time difference, setting a total step number required for realizing the reverse animation and an execution interval of each step, and obtaining an animation progress parameter according to the total step number and the execution interval; the animation progress parameter is initialized, so that the animation progress parameter is linearly changed from an initial value to a final value in an animation execution process; when each step of the animation is executed, obtaining a current value of an animation progress parameter as input; and applying the input current value to a preset slow motion function for calculation so as to obtain a nonlinear progress parameter with an S-shaped change curve. According to the invention, immersion, emotional resonance and visual fluency of memory presentation are improved.

Various implementations include methods for processing images from a device camera to identify potential malicious attacks on the camera. These implementations may include using multiple different trained image processing models or vision pipelines to process images received from the device's camera to obtain multiple different image processing outputs, and performing multiple consistency checks on the multiple different image processing outputs. Such consistency checks compare two or more selected outputs from the multiple different outputs to detect inconsistencies that may be associated with or caused by an attack on the camera. Indications of an attack on the camera may be reported to and considered by the device's autonomous driving system, or otherwise addressed in one or more mitigation actions.

The present application relates to the technical field of low-permeability oil and gas reservoir development, and is a visual flow experiment device and experiment method for simulating conventional rod pumping dynamic, comprising a constant-pressure water supply device, a micro displacement device, a measuring cylinder and a vacuum suction device, the constant-pressure water supply device outlet is communicated with the measuring cylinder bottom inlet through a first water supply pipeline, the vacuum suction device top inlet is fixedly communicated with a vacuum hose, the vacuum hose inlet end extends into the measuring cylinder, and the influence of the change amplitude of the bottom hole pressure on the percolation is controlled by simulating different pumping unit stroke and frequency conditions.The present application has simple structure, convenient operation, easy measurement and calculation of various pressures, and the experiment phenomenon is easy to observe, record and analyze, the conventional rod pumping system can be simulated, the dynamic change of different drainage systems and the influence of the bottom hole pressure disturbance on the reservoir percolation are studied, the best production system parameters under different reservoir conditions are optimized, thereby reducing the production cost and improving the reservoir recovery.

The invention relates to the technical field of hydrological monitoring and computer vision, and discloses a visual flow measurement method, device and equipment based on a large-scale particle image flow measurement algorithm and a medium, and the method comprises the steps: obtaining the monitoring video data of a to-be-measured river and camera calibration parameters; image frames in the video data are preprocessed; performing pixel displacement calculation on the preprocessed continuous image frames through a large-scale particle image velocity measurement algorithm to generate a surface velocity vector field, and converting the surface velocity vector field into an actual velocity; performing multi-criterion chained filtering on the surface flow velocity vector field to obtain an optimized flow velocity field; mapping the optimized flow velocity field to a river section grid, and performing integral calculation based on section water depth data to obtain a section flow time sequence; and generating a transparent vector layer based on the optimized flow velocity field, fusing the transparent vector layer with the original video frame by frame, and outputting a flow field visualization video. According to the invention, efficient, accurate and stable non-contact river flow measurement is realized, and the processing efficiency and the result reliability are improved.

The application provides an image acquisition method, device and storage medium, and relates to the technical field of communication. The image acquisition method is applied to a master device, and the master device is in communication connection with a plurality of controlled devices which are respectively located at corresponding preset positions. The method comprises the following steps: performing time synchronization with the plurality of controlled devices according to a preset reference time; controlling the plurality of controlled devices to shoot a to-be-shot object according to the preset reference time, and obtaining a plurality of to-be-processed images which are matched with the preset positions; and generating a target image by using the plurality of to-be-processed images. The shooting time of the plurality of controlled devices is kept consistent with the shooting time of the master device through time synchronization, and time delay error is reduced. The plurality of controlled devices are controlled to shoot the to-be-shot object according to the preset reference time, and multi-dimensional to-be-processed images are obtained. The plurality of to-be-processed images are processed according to preset extraction conditions, and the visual fluency of the obtained target image is better.