92 results about "Real time tracking" patented technology

This invention discloses an intelligent advertising design and generation method, specifically including the following steps: S1, Data Collection and Preprocessing: Collecting product data, user behavior data, historical advertising data, and real-time market data, and performing cleaning, labeling, and feature extraction; S2, User Profile Modeling: Constructing a dynamically updated user interest graph based on clustering analysis and deep learning algorithms; This invention relates to the field of artificial intelligence technology. This intelligent advertising design and generation method integrates multi-dimensional data such as product functions, user behavior, and competitor dynamics to improve the accuracy of advertising content, generate targeted advertising copy, support the joint generation and style unification of text, images, and videos, and the system can simultaneously generate advertising slogans such as "Riding the Wind, Unlocking the Acceleration of Youth" and dynamic posters, track click-through rates, conversion rates, and other indicators in real time, automatically adjust content parameters, use blockchain technology to store copyright information, and protect user data through differential privacy algorithms.

The application provides a surgical robot system and control method for proximal femur osteotomy, the system comprises: a preoperative planning module for constructing a hip joint three-dimensional model and performing preoperative planning according to the hip joint three-dimensional model to generate a proximal femur osteotomy scheme, which is one of a femoral head rotation osteotomy scheme, a femoral neck rotation osteotomy scheme, an intertrochanteric rotation osteotomy scheme and a subtrochanteric rotation osteotomy scheme; a navigation positioning module for registering the entity femur in operation and the hip joint three-dimensional model before operation according to an optical positioner and an optical positioning frame to map the proximal femur osteotomy scheme, real-time tracking the pose of the surgical tool and the entity femur, and displaying and comparing the proximal femur osteotomy scheme and the real-time osteotomy process on a display screen. In the application, the preoperative planning-intraoperative optical positioning navigation can track the osteotomy condition of the surgical tool in real time during operation, and multiple medical imaging is avoided, thereby greatly improving the surgical effect.

The application discloses a kind of automatic packaging control systems of spinning production, it is related to spinning production field, comprising: acquisition module, for collecting the running time sequence of each station execution mechanism of spinning production automation packaging whole process, driven load, action displacement and response length data, complete the time sequence alignment of data according to production cycle and standardization output;Calibration module is used to receive the standardized data output by acquisition module, establish the health running parameter benchmark library of each station execution mechanism under all working conditions, complete the interval division of benchmark parameter and station matching binding;The application can accurately collect regular station operation data, build the health parameter benchmark that fits working condition, real-time track deviation, hierarchical early warning and locate station, adjust action, cycle and material conveying according to fault risk, multi-station early warning hierarchical adaptation, check and optimize benchmark parameter, reduce equipment downtime, ensure smooth connection of station, improve production stability and control accuracy.

This invention relates to the field of disaster prevention and mitigation technology for marine engineering structures, and discloses a method for plotting vulnerability curves of guide seawall structures based on random load combinations. The method includes: constructing a nonlinear finite element model of a deep-water guide seawall; introducing a two-dimensional phase coupling vector to generate random dynamic load samples containing temporal coupling characteristics of earthquakes and waves; inputting the samples into the model, tracking the structural frequency drift in real time and considering pore flow abrupt change damping, and calculating the multidimensional dynamic response of the structure; constructing a multidimensional dynamic limit state surface that shrinks with cumulative plastic damage, and determining the failure state based on the relative relationship between the dynamic response and the state surface; estimating the failure probability using extreme value statistics theory, and establishing a probabilistic demand model containing cross-coupling terms of earthquake and wave intensity; and plotting a vulnerability surface describing the change of the failure probability with bivariate strength indices based on this model. This invention can accurately assess the dynamic reliability of deep-water guide seawalls under the coupling effects of multiple disasters.

The present application relates to a kind of dynamic polarization anti-dazzle windshield systems and control methods for vehicle, its system includes composite windshield with dynamic polarization layer and electrochromic layer, light source sensing unit, driver eye point tracking unit and control unit.Control method is by real-time tracking light source and driver eye point position, it is mapped to polarization layer and forms dynamic extinction area, and calculates target polarization angle and carries out quick extinction, while with electrochromic layer and carries out transmittance compensation.The present application realizes the precision, fast anti-dazzle of fast moving light source, avoids non-glare area visual field loss, effectively improves night driving safety.

The present application relates to livestock traceability technical field, specifically for livestock meat slaughtering, cutting and packaging traceability method and system based on internet, the method comprises: collecting quarantine information of livestock individual, obtaining initial traceability data; according to initial traceability data, determine the slaughter batch code, and the initial traceability data source is bound with the slaughter batch code, and the slaughter credible data package is obtained; based on the slaughter batch code, the cutting operation process information of livestock individual is tracked and filed in real time, and the cutting link data chain is obtained; based on the cutting link data chain, the multi-dimensional quality of livestock individual is judged, and the comprehensive quality index is obtained; based on the comprehensive quality index, the intelligent matching planning of meat product is carried out, and the packaging batch planning is obtained; based on the packaging batch planning, the livestock individual is coded and identified, and the product traceability code is obtained; the present application can improve the efficiency of livestock meat slaughtering, cutting and packaging traceability based on internet.

The application discloses a kind of automatic control method and equipment for sweet potato seedling seedling pipeline operation, it utilizes differential pulse modulation to collect the excited state and background state image of vine, through space self-adaptive weighted difference modeling and non-local mean regularization enhancement technology, effectively suppress environmental light noise and retain weak biological fluorescence signal, to generate the high confidence vine node distribution map.On this basis, abandon traditional fixed-length cutting mode, construct dynamic programming model based on agronomic constraints, solve the optimal segmentation strategy of maximum output rate in the whole vine range.Finally, through the space-time fusion of visual coordinates and conveyor encoder, drive multi-axis servo system to track and accurately work the real-time virtual cutting point of dynamic movement, realize the efficient, low-loss automatic production of sweet potato seedling.

The invention discloses a multi-person picture synthesis method and device, equipment and a medium. The method comprises the following steps: splicing original images at multiple angles to obtain a panoramic image of a current target area; real-time tracking is carried out according to all face position information in the current frame, sound source information is collected synchronously, and a current spokesman in the target area is determined; and generating a multi-person synthetic picture according to the real-time motion picture of the current spokesman and the real-time motion pictures of other people. Multi-angle images are collected for feature point matching and image splicing, a high-quality panoramic image is generated, wide-area visual angle coverage is achieved, a more detailed image is obtained, all face positions are locked, corresponding sound source information is collected, a current spokesman is recognized, a multi-person synthetic picture which highlights the current spokesman and gives consideration to other people is generated, and the multi-person synthetic picture is obtained. The integrity of the panoramic information is guaranteed, meanwhile, the key content is clearly presented, the problems that the visual angle is limited and information is overloaded are solved, and the communication efficiency and watching experience of a teleconference are improved.

This invention discloses a label-free real-time blood vessel tracking method driven by dynamic blood oxygenation features, relating to the fields of medical image processing and computer vision. The method includes: acquiring dynamic blood oxygenation signals from a target tissue region; preprocessing the blood oxygen concentration change data; constructing a spatiotemporal matrix of blood oxygenation features; performing adaptive feature extraction using an improved 3D convolutional neural network; establishing a multi-scale blood vessel contour prediction model; dynamically predicting and updating the blood vessel contour using a Kalman filter algorithm; outputting the real-time trajectory of the blood vessel center and boundary contours; and introducing a dynamic feedback mechanism to achieve continuous and stable blood vessel tracking. This invention achieves highly secure blood vessel tracking, significantly improving tracking accuracy, robustness, and real-time performance under tissue movement and complex background interference by utilizing dynamic blood oxygenation features.

This invention provides a method, device, electronic device, and storage medium for reminding users to remember forgotten items, relating to the fields of smart home and Internet of Things (IoT) technology. The method includes: identifying the user's current activity context; determining the target item associated with the current activity context; acquiring the target item's status data, including location information and existence information; calculating a forgetting risk value corresponding to the current activity context based on the location and existence information; and outputting a reminder message if the forgetting risk value meets a condition. This allows for rapid location of the target item associated with the user's current activity context after identification, enabling passive, real-time tracking of the spatial location and existence information of items associated with the activity context without requiring the user to wear any tags. This reduces reliance on active tags and associated costs, while increasing the coverage of item tracking, significantly reducing the user's cognitive burden and improving convenience.

This invention relates to the field of roll call systems and discloses a roll call system for inmates, comprising: a monitoring module responsible for real-time observation of the location, status, and information of inmates; a roll call module responsible for timed roll calls of inmates; and a positioning module responsible for real-time tracking of the location of inmates. The roll call module and the positioning module are respectively communicatively connected to the monitoring module. Through the installation of facial recognition machines in warehouses, key areas, cells, workshops, outdoor areas, offline areas, fixed facial recognition machines in visiting rooms, and cargo handling areas, inmates' status is updated in real-time via the facial recognition machines in each area when they enter a designated area or enter a specific state. Simultaneously, they send their facial recognition data to the command center's web interface. This data is then displayed on a large screen in the command center, allowing command center personnel to monitor inmates in real-time, thus eliminating the need for manual roll calls.

The application provides a multi-modal data fusion evaluation and prognosis prediction method and system for septic cardiomyopathy, which comprises the following steps: obtaining target data and electronic medical records of septic cardiomyopathy patients, combining the target data with a preset first database to construct a correlation matrix; constructing a second database corresponding to the septic cardiomyopathy patients according to the electronic medical records; generating a target interaction path based on the second database; obtaining a first signal according to the causal effect intensity of each node in the target interaction path, and generating a prognosis prediction scheme in combination with a target risk threshold. The application realizes real-time tracking and closed-loop intervention of the pathological process of septic cardiomyopathy, and fundamentally solves the prognosis prediction deviation caused by the time and space disconnection of the traditional database.

The application discloses a dangerous goods road transportation remote electronic escort intelligent supervision system and method, and belongs to the technical field of Internet of Things operating systems. The system comprises a data acquisition and fusion module, which acquires multi-source data of dangerous goods transportation vehicles in real time, and generates standardized fusion data flow; a transportation risk prediction and evaluation module, which generates a predictive risk map according to the standardized fusion data flow; a path planning module, which generates a risk avoidance path set based on the predictive risk map, and outputs a recommended path scheme; and an execution module, which generates graded early warning instructions and path adjustment suggestions according to the predictive risk map and the recommended path scheme, and simultaneously tracks the actual driving track and risk changes of the dangerous goods transportation vehicles in real time. The method comprises steps T1-T4. The application fuses historical and real-time data through the transportation risk prediction and evaluation module, constructs a predictive risk map, and realizes quantitative prediction and visual early warning of future accident risks of road sections.

The application relates to a logistics transportation system with an electronic fence and a data calibration method thereof, and relates to the technical field of intelligent workshop logistics transportation calibration. The intelligent workshop logistics transportation system comprises an intelligent fence management terminal, which is used for virtually dividing a visual attention fence area according to an actual conveying line and converting the visual attention fence area into actual attention fence coordinates; a dynamic visual acquisition terminal, which is used for positioning the conveying position of an article, triggering dynamic acquisition of the article in combination with the actual attention fence coordinates, and obtaining an article video stream; a monitoring and identification execution terminal, which is used for cleaning and identifying the article video stream, obtaining an abnormal article, generating an abnormal state code, and completing abnormal removal in combination with an external execution mechanism; and a digital twin optimization terminal, which is used for creating a digital production line according to the production line layout in combination with the visual attention fence area, and simulating and optimizing the fence layout. Through real-time tracking of the position of the article and calculation of the distribution center of the article, an offset correction value is generated, and calibration data is dynamically updated, so that self-calibration and self-adaptive optimization of the electronic fence are realized.

This invention provides a method, apparatus, device, and storage medium for real-time iris tracking and localization. The method includes: performing multi-level convolution processing on a real-time input iris image to extract iris features at different scales, obtaining a feature map set; inputting the feature map set into a preset mask prediction model for mask prediction, obtaining a pupil boundary mask and an outer iris boundary mask; extracting the boundary contours of the pupil boundary mask and the outer iris boundary mask, obtaining a pupil boundary contour point set and an outer iris boundary contour point set; performing geometric fitting based on the pupil boundary contour point set and the outer iris boundary contour point set, and optimizing and correcting the fitting parameters according to the concentric constraint relationship between the iris and the pupil to obtain the iris localization result. This invention, by combining boundary enhancement feature fusion with geometric constraint optimization, can accurately locate the inner and outer boundaries of the iris in non-cooperative environments, improving the accuracy and robustness of iris localization.

The present application belongs to the field of visual tracking technology, and discloses a kind of processing existing partial occlusion flexible linear object visual tracking method, based on RGB-D camera obtains color image and depth image data, from first frame image, by mask segmentation, skeletonization processing operation generates initial state point, in each subsequent frame, object point cloud is generated by mask in conjunction with depth image;Then, the density of its surrounding current point cloud is counted, and the state point is marked as "visible" or "occlusion";By establishing the analytical model based on the spatiotemporal continuity of flexible linear object, the closed form solution of the occlusion position is derived, and the iterative optimization process of the occlusion position is eliminated, thereby reducing the computational complexity and achieving efficient real-time tracking;Meanwhile, using the inherent spatiotemporal geometric evolution law of flexible linear object, a position estimation model that can be directly analytically solved is constructed, avoiding the stability risk brought by iterative optimization, and significantly improving the reliability and tracking stability of the occlusion position estimation.

This invention discloses an artificial intelligence-based engineering resource scheduling optimization system and method, belonging to the field of engineering management technology. It establishes a resource status perception network by deploying IoT sensors and constructs a progress benchmark system based on the project plan. By comparing the actual progress with the progress benchmark system, it identifies tasks with excessive deviations that need to be scheduled. It constructs a task urgency classification model, extracts the progress dynamics, task dependencies, and resource supply characteristics of the tasks to be scheduled, generates a resource demand urgency level for each task, and generates a scheduling demand description. It matches the scheduling demand with the resource status, constructs a multi-objective optimization function considering spatial distance, workload, and type suitability, obtains a resource allocation scheme by solving the function, sends scheduling instructions according to the allocation scheme, monitors the execution status, tracks resource location and task progress in real time, and re-triggers the scheduling process when a new deviation is detected, forming a closed-loop dynamic optimization mechanism.

This application discloses a method and system for detecting abnormal output impedance of a power amplifier, relating to the field of output impedance abnormality detection technology. This application utilizes sliding window technology to track and analyze the changing trends of power amplifier operating parameters in real time, enabling timely detection of threshold range adjustment needs and generating corresponding instructions (including range expansion and range contraction instructions). This provides a foundation for realizing dynamic abnormality detection of power amplifiers. By calculating the standard deviations of load impedance, temperature, and operating frequency, and based on the results of the standard deviations, the abnormality detection threshold range can be precisely adjusted to ensure detection accuracy. Each time the sliding window slides, the system updates the abnormality range, ensuring that the abnormality detection threshold can respond in real time to dynamic changes in parameters. This adaptive mechanism is suitable for various working scenarios, especially for equipment with high dynamic performance requirements.

A method and apparatus for providing information to an electronic device are provided. The method for providing information to an electronic device includes: establishing a connection between the electronic device and a gimbal device; displaying a function icon on the display interface of the electronic device in response to the camera of the electronic device being invoked by an application of the electronic device; determining a target tracking object through a preset operation by the user based on the function icon; and enabling the gimbal device to track the target tracking object in real time based on the tracking information of the target tracking object, wherein the tracking information includes: location information and feature information.

This invention provides a method, equipment, and medium for predictive calculation of hanging basket structures based on multi-source data. It establishes a standardized parameter library by collecting hanging basket design parameters, actual processing data, and real-time on-site monitoring data. A complete structural mechanics model of the hanging basket is built, the overall structural stiffness matrix is ​​calculated, initial design loads are applied, and static equilibrium equations are solved. The structural stiffness matrix is ​​corrected using actual processing data, and the actual load vector is corrected using unloaded static data. Based on the corrected stiffness matrix and load vector, the structural mechanics equations are resolved, and deviations are calculated using construction dynamic data as constraints. If the deviation exceeds a threshold, the structural parameters are iteratively corrected, and the solution is re-solved and compared. This invention achieves high-precision simulation and real-time tracking of the hanging basket's stress state by integrating multi-source data from design, processing, and on-site data and introducing a dynamic correction mechanism, ultimately achieving precise control over structural safety and construction alignment.

This invention discloses a method for real-time 3D tracking and localization of microscale targets in a bright-field microscopic environment, relating to the fields of image recognition and reconstruction technology. The method includes inputting continuous microscopic images into a target detection model, outputting the target's 2D position, regressing the defocus height and direction from a single frame of local images using a fine-grained ROI-based defocus regression model, directly using the model output to drive a 2D motion platform and a focusing device, fusing the 2D position information of each frame with the corresponding defocus axis information, and incorporating the position information of the previous frame as a priori using a temporal correlation mechanism to achieve continuous correlation of the microscale target in the time dimension, thereby stably reconstructing the target's 3D position and outputting a smooth real-time motion trajectory. This invention achieves real-time 3D localization and stable tracking of microscale targets under single-view bright-field microscopic conditions, ensuring both positioning accuracy and system real-time performance and accuracy.

This invention discloses an intelligent e-commerce warehouse goods management system, belonging to the field of intelligent warehousing and logistics management technology. The system adopts a multi-source heterogeneous data fusion architecture, including core components such as an RFID tag module, RFID reader / writer, visual recognition module, and data fusion processing module. The data fusion processing module employs spatiotemporal alignment units, adaptive Kalman filtering algorithms, and hybrid positioning algorithms to achieve high-precision fusion of RFID data and visual data. The method includes steps such as system initialization, goods entry identification, data preprocessing, spatiotemporal alignment, data fusion, location calculation, data storage, real-time tracking, outbound verification, and report generation. Through fusion algorithms and architecture design, this invention achieves high-precision positioning, millisecond-level real-time response, and system availability, significantly outperforming existing technologies and providing a new technical solution for intelligent warehousing.

The present application relates to the technical field of deformation monitoring, in particular to a time-space self-learning early warning system for foundation settlement risk in highway construction process, which comprises an information processing module, a weight construction module, a tensor analysis module, a risk calculation module and an early warning release module. In the present application, the spatial position vector and the Gaussian kernel function are used to evaluate the distribution density and generate the coverage weight, which eliminates the local deviation caused by uneven distribution and ensures the balanced expression of regional settlement characteristics. The lag interval is deduced by using the soil consolidation theory and the deformation direction consistency is screened, the environmental noise is eliminated to lock the effective cumulative settlement caused by specific process, the prediction model with self-adaptive ability is constructed by combining the grey system theory, the dynamic growth rate of the settlement cumulative value is tracked in real time, the change from static control to dynamic trend warning is realized, and the sensitivity of capturing the precursor of foundation instability is improved, which provides a scientific basis for construction process adjustment.

The application relates to a kind of chain disaster under the safety dynamic evaluation method of track-bridge structure. The method unifies track-bridge structure and slope topology by constructing double-state heteromeric graph network containing structure node and geotechnical node;By constructing a physical information constraint double-state evolution graph network model, the temporary hidden state is updated using the structure inside and geotechnical inside message transmission module, and the bidirectional information exchange is controlled through the physical information gate crossing update module, the dynamic deterioration of slope mechanical parameters under the action of earthquake and the pathological coupling mechanism of structure response are captured;The model is trained using multi-physical field coupling simulation data to learn the above rules;Then, according to the real-time seismic monitoring data, the model is forward deduced in streaming, and multi-level safety warning indicators are constructed from the decoded structure response and geotechnical state and compared with the threshold value, to realize real-time tracking of slope deterioration process and dynamic accurate evaluation of bridge structure safety.

The present application relates to computer graphics and real-time rendering field, disclose a kind of naked-eye VR view angle continuous roaming real-time tracking system, comprising: multi-source viewpoint acquisition unit, rendering feedback prediction unit and viewport consistency arbitration unit connected with depth buffer and template buffer, the present system is through rendering feedback prediction unit, according to the object attribute purification motion vector of template buffer data hierarchical solution to deduce viewpoint, viewport consistency arbitration unit is when external sensing data deviation overrun, forcedly use deduced viewpoint to take over rendering, the present application constructs independent hot backup and abnormal takeover mechanism based on rendering pipeline data, uses picture visual residual inertia to fill in external sensor data blank, avoid rendering collapse caused by sensor signal interruption or asynchronization.