267 results about "Tracking data" patented technology

The application discloses a vehicle false track identification method, device and equipment and a storage medium. The method comprises the following steps: determining the parking data and the mileage data of a vehicle according to the track data of the vehicle; calculating the abnormal parking data of the vehicle according to the parking data and the mileage data; determining the abnormal track segment of the vehicle according to the abnormal parking data; obtaining the contrast track segment of the abnormal track segment, calculating the similarity between the abnormal track segment and the contrast track segment, determining the track anomaly of the vehicle according to the similarity, and obtaining the number of days of the track anomaly of the vehicle; and when the number of days of the track anomaly is greater than a preset day threshold, determining that the vehicle reports a false track. According to the vehicle false track identification method provided in the application, the vehicle false track can be effectively identified, and the normal operation of the freight vehicle can be effectively supervised by the freight platform and the service provider.

The application provides a guided tooth repair method, system and storage medium, which realizes the conversion and unification of the coordinate systems among multiple systems through technical steps such as CBCT data acquisition, CT three-dimensional model creation, robot calibration, matrix conversion relationship analysis, and the like, and then, after a tooth repair scheme is formulated based on the CT three-dimensional model, the matrix conversion relationship among the coordinate systems of the oral cavity reference plate, the CT and the optical positioner is obtained, the cutting tool and the repair tool on the robot are guided through the optical positioner, the real-time pose of the patient is judged in the assistance of the optical positioner by combining the running track data of the cutting tool and the running track data of the repair tool, the cutting and repair are guided in real time, human errors are avoided, the operation precision is improved, and the tooth repair effect is ensured.

The application discloses a road centerline determination method and system based on a deep neural network satellite map, and relates to the technical field of satellite image processing; the method comprises the following steps: preprocessing time-phase satellite images of a collected to-be-processed region, vehicle GPS track data and street view image sequences to obtain a dynamic region in the to-be-processed region, a track density map and a street view feature mapping table; inputting the time-phase satellite images into a pre-trained road segmentation model to obtain multiple road probability maps; based on the multiple road probability maps, performing dynamic region weighted fusion, non-dynamic region logical or operation and threshold determination to obtain an initial road mask; vectorizing the initial road mask into a centerline network and extracting cross nodes to obtain an initial road network topology; and the application has the advantages of improving the accuracy of the road network topology and guaranteeing the rationality of path planning.

The application discloses a vehicle instrument information priority sequencing method and device based on eye movement track, comprising: acquiring vehicle state data, external environment data and eye movement track data of a target driver of a target vehicle; determining a safety requirement level of each to-be-displayed instrument information according to the vehicle state data, determining a scene requirement level of each to-be-displayed instrument information according to the external environment data, and determining an intention requirement level of each to-be-displayed instrument information according to the eye movement track data; determining an information display priority of each to-be-displayed instrument information according to the safety requirement level, the scene requirement level and the intention requirement level; and dividing the to-be-displayed instrument information into core layer information, auxiliary layer information and redundant layer information according to the information display priority, and performing hierarchical display. The application realizes priority display of instrument information with high importance and high requirement, improves the efficiency and timeliness of information acquisition of a driver, and can be widely applied to the technical field of intelligent cockpits.

This application relates to a register monitoring method, apparatus, system, chip, and chip module. Applied to a register monitor located on a transmission port of an on-chip bus, the method includes: obtaining multiple access events of at least one target master device accessing a register from a cache queue of the on-chip bus; packaging the multiple access events according to a preset trace data structure to obtain a trace data stream; the trace data stream is used to monitor the register access behavior. This method enables register monitoring.

This application provides a multimedia resource display method, apparatus, and related equipment based on eye-tracking interaction. It offers an interaction scheme for displaying multimedia resources that accurately determines the user's selection intent through gaze behavior. By analyzing eye-tracking data generated during the user's viewing of media resources, the application determines the user's gaze behavior, identifies the selected interactive element based on the gaze behavior, and further displays media resources pre-associated with the interactive element. The interaction method proposed in this application does not require the user to execute preset fixed action commands, highly conforming to natural visual observation habits. Furthermore, because the user's gaze behavior accurately reflects their interests, it ensures that the selected content is what the user is most interested in. The entire interaction process is intuitive, smooth, and seamless, enhancing the user's immersion and acceptance.

A head-mountable device renders a graphical user interface and causes user-interface changes responsive to facial expressions of a user. The device receives sensor data from user-facing sensor assemblies, including imaging of left and right eye regions, and eye-tracking data indicative of eye movement. The device derives eye-openness data for each eye from the sensor data, including measurements based on eyelid geometry. In response to a facial expression, the device causes a user-interface change that is conditional, at least in part, on the eye-tracking data and the eye-openness data. Facial expressions may include winking, blinking, and squinting. In some embodiments, the device determines an amplitude and / or duration of the facial expression and varies a magnitude or speed of the user-interface change based on the determined parameter(s), enabling text entry, selection, navigation, and manipulation of displayed objects and applications.

This application relates to the field of interface gateway management technology, and discloses an open application programming interface (API) gateway management system and method. The method includes: responding to a received API call request, extracting the caller's identity information and request context parameters, performing dynamic authentication on the call request, and obtaining the authentication result; obtaining the corresponding rate limiting rules, performing dynamic mixed-mode traffic control on the call request, and obtaining the traffic control result; forwarding the call request to the corresponding backend service, and monitoring the backend service's operating status data in real time during the forwarding process, performing circuit breaker analysis based on the operating status data and preset business semantic rules, and obtaining the circuit breaker control signal; executing the corresponding request processing action according to the circuit breaker control signal, and collecting full-link observable data such as call chain tracing data and network performance data in real time to manage interface calls; this application can effectively intercept replay attacks, abnormal logins from different locations, etc., and improve gateway throughput.

This invention relates to eye-tracking methods, specifically to an occlusion-resistant eye-tracking method. It addresses the problems of insufficient tracking accuracy, lack of robustness, and difficulty in maintaining stable tracking under interference such as continuous blinking in existing eye-tracking methods. This invention first reconstructs low frame rates into kilohertz-level high-frequency sequences using an event-driven frame interpolation network, overcoming the frame rate limitations of traditional sensors. Subsequently, through multi-scale feature fusion and a temporal matching mechanism based on adaptive templates, it effectively utilizes historical clear frame features to compensate for occlusion areas. Furthermore, it dynamically selects three processing strategies based on an occlusion rate perception strategy, thereby maintaining high accuracy and continuous tracking even under occlusion conditions. This significantly improves robustness and practicality under interference such as blinking, providing a reliable technical foundation for applications requiring high-frequency, interference-resistant eye-tracking data, such as VR / AR interaction and clinical eye-tracking analysis.

This invention discloses a neurophysiological behavior-driven multimodal intelligent learning guidance system and method. The system achieves closed-loop control by constructing a cognitive-emotional-task adaptive adjustment space: 1) In the cognitive dimension, it integrates EEG neural oscillations and frontoparietal network connections, fNIRS cerebral oxygen metabolism indicators, and eye-tracking data to construct a multimodal cognitive load assessment model; 2) In the emotional dimension, it combines the nonlinear characteristics of skin conductance signals with facial expression recognition to quantify learners' motivation levels and emotional valence in real time; 3) In the task dimension, it parameterizes task difficulty and interaction form as moderating variables. During system operation, the system locates the learner's position on the cognitive-emotional state plane in real time and dynamically adjusts task dimension parameters through a nonlinear mapping strategy. This invention effectively utilizes the decoupling ability of multimodal signals and the interaction of intention to achieve precise adaptive delivery of teaching content.

The application discloses a park navigation method and device, electronic equipment and storage medium, belongs to the navigation technical field, and is used for improving the accuracy and navigation efficiency of park navigation. The method comprises the following steps: in response to a navigation request for a target park, determining navigation starting point information and navigation ending point information, and a carrier type of an execution carrier; based on preset space boundary information of each traffic area in the target park, matching a starting traffic area for the navigation starting point information and matching an ending traffic area for the navigation ending point information; based on a traffic cost parameter corresponding to the carrier type, searching for a navigation path from the starting traffic area to the ending traffic area from a pre-constructed floor connection relationship of the target park, and outputting traffic track data matched with the navigation path; wherein the floor connection relationship of the target park is constructed by taking each traffic area in the target park as a regional node and a connection relationship between the regional nodes through entrances and exits as edges.

The application discloses a data management method and system suitable for IMR, wherein when a bottom track is updated, data of an effective top track is actively migrated to other free tracks; in the MFML data update strategy, a zigzag four-stage data management scheme is adopted, in the first stage, data of the bottom track is updated; in the second stage, the MFML strategy is adopted to update data of the bottom track; in the third stage and the fourth stage, data distribution and bottom track data update are continuously performed according to the mode of the second stage, and data management is realized. The application can make the MFML update strategy better play the performance in the four-stage data management scheme, and can also relieve the performance decline problem caused by the too high top track occupation amount of the multi-stage distribution scheme.

Embodiments of the present application provide a road network updating method, device, equipment, storage medium and program product. The method comprises: obtaining driving track data, and performing track preprocessing on the driving track data to obtain target track data; performing matching processing on the target track data and an initial road network to obtain sub-track data matched with each business road section; determining heat map data corresponding to each business road section according to the track density of the sub-track data matched with each business road section; determining a drivable road surface corresponding to each business road section according to the heat map data, and determining road network updating intelligence according to the spatial matching relationship between the drivable road surface and the initial road network; wherein the road network updating intelligence is used to update the topology road section of the initial road network. The method can reduce the road network updating cost and improve the real-time performance, efficiency and accuracy of road network updating.

This document describes techniques, systems, and methods for multi-scan sensor fusion for object tracking. Sensor fusion systems can acquire radar and visual tracking data generated for a vehicle's environment. The system maintains a set of hypotheses about the association between visual and radar tracking based on multiple scans of radar and visual data. This set of hypotheses includes quality values ​​for the associations. The system determines a probability value for each hypothesis. Based on these probability values, a match is determined between radar and visual tracking. The system then outputs the match to a semi-autonomous or autonomous driving system to control the vehicle's operation. In this way, the described techniques, systems, and methods can provide high-precision object tracking with quantifiable uncertainty.

This disclosure provides a system and method for receiving, at a processor associated with a vehicle and via one or more image sensors associated with the vehicle, image data associated with the environment surrounding the vehicle and corresponding to a first image captured at a first time, and supplementary image data associated with the environment surrounding the vehicle and corresponding to a second image captured at a second time. The provided system and method can determine, based on the received supplementary image data and a machine learning model, that a tracked object not detected in the second image but identified in the first image, and can determine, based on vehicle data and tracking data of the tracked object, that the tracked object should be present in the second image and perform remedial actions on the supplementary image data to identify the tracked object in the second image.

The application relates to the technical field of target identification, and discloses a kind of fusion track and image collaborative target identification method and system, the method comprises: synchronously obtaining track data and image data, and track data and image data are time-space registered, and collaborative data is obtained;Based on collaborative data, track data is time-series correlation fitting, and target track is obtained;Based on collaborative data, image data is multi-scale feature fusion, and image fusion atlas is obtained;Target track and image fusion atlas are bidirectional intercommunication correlation, and track atlas pair is obtained;The behavior semantics of track atlas pair is interpreted, and behavior intention is obtained, and the situation representation between behavior intention is evaluated, and situation representation is obtained;Based on situation representation, track atlas pair is structured analysis, and target identification result is obtained;The application can improve the accuracy of collaborative target identification.

This invention relates to the field of AI-based data quality assessment technology, specifically to an AI-based method and system for assessing data quality throughout its entire lifecycle. The method includes: acquiring multi-stage data samples throughout the data lifecycle; decoupling data content and metadata structure; separating the core content field from the process trajectory field; automatically constructing a multi-dimensional quality feature space in the core content field; extracting native feature points and mapping them into the space; tracking data transfer events in the process trajectory field to generate dynamic transfer trajectories; injecting the process information carried by the trajectory back into the feature space; applying process constraint offsets to the native feature points to form quality state points; and finally generating a data quality assessment value. This solution achieves dynamic quality representation throughout the data lifecycle through field decoupling and process constraint perturbation, making the assessment results more closely reflect the actual data flow state.

A method for deriving a wear state of a soil interaction component of a soil processing implement of a construction vehicle. The method comprises steps of 1.) providing a geometry model regarding an assumed shape of the soil interaction component, 2.) engaging the soil by using the soil interaction component and tracking a motion for deriving tracking data of the soil interaction component, 3.) using the tracking data and the geometry model to derive an expected 3D surface model, 4.) providing visual 3D perception data of a soil area affected by the engaging, such that the visual 3D perception data and the expected 3D surface model can be referenced to one another, and 5.) comparing the visual 3D perception data with the expected 3D surface model and, based thereof, determining a deviation of an effective shape of the soil interaction component from the assumed shape.

Systems and methods are described for generating a customized care plan for a patient, tracking data and progress of the patient across a service line history over time, generating at least one analytics dashboard, and causing display of the at least one analytics dashboard, wherein the patient information in the at least one analytics dashboard is encrypted and accessible for view according to predefined patient permissions.

Parallel processing computer systems and methods for real-time multimodal behavioral classification and dynamic content adaptation are provided. A parallel processing pipeline implements concurrent execution of sensor data ingestion, neural network inference, content adaptation, and rendering stages across specialized processor resources including graphics processing units and tensor processing units. The parallel processing pipeline achieves end-to-end latency of less than 200 milliseconds from sensor data capture to rendered content output, representing a reduction of at least 60% compared to conventional sequential architectures exhibiting latencies exceeding 500 milliseconds. A trained neural network model comprising feature extraction modules with parallel convolutional branches, a bidirectional Long Short-Term Memory temporal processing module, and a classification module processes multimodal sensor data including video frame data, audio waveform data, motion tracking data, and physiological sensor data to classify behavioral states and calculate engagement levels. A dynamic adjustment algorithm modifies content parameters including difficulty level, environmental complexity, and reinforcement schedule based on real-time performance metrics to maintain user performance within target ranges.

This application belongs to the field of radar data processing technology, specifically relating to a radar data association and detection capability analysis method. The method includes: classifying and parsing received radar detection result data of a batch to be analyzed according to data source; acquiring the spatiotemporal position data of the platform to be analyzed, the target track data output by the platform's radar detection, and the spatiotemporal position data of the test target; identifying the time period where the above three types of data coexist; using the detection time of the radar detection track as a reference, converting the spatiotemporal position data of the platform to be analyzed and the spatiotemporal position data of the test target to the reference time through interpolation; for the selected platform to be analyzed, associating the track corresponding to the test target from the radar detection track; calculating the error of each radar detection index relative to the given actual value of the test target, and graphically displaying the radar detection value, actual value, and error value of the index. This application significantly improves data processing efficiency and evaluation accuracy.

The application discloses a front-end interface self-repairing method and device based on user operation track. The method can realize real-time sensing and analysis of the user operation process by listening to the interactive operation of the user on the front-end interface. The interface state of the front-end interface can be self-repaired based on the target behavior judgment result, and the interface self-adaptive repair is realized without invading the business logic. In addition, the target behavior judgment result is accurately and efficiently generated by feature extraction and analysis of the operation track data, so that the interface state of the front-end interface can be accurately and correctly self-repaired based on the target behavior judgment result, and the user can see the interface state after self-repairing in real time.

The utility model relates to agricultural machinery, concretely relates to a land wheel device for seeding and fertilizing, including four joint profiling mechanism, land wheel frame, land wheel and rotary encoder, four joint profiling mechanism includes upper connecting piece, lower connecting piece, front connecting seat and rear connecting seat form four joint frame structure and elastic connecting piece, is provided with the vehicle body connecting portion on the front connecting seat, is provided with the land wheel frame on the rear connecting seat, the land wheel frame is installed with land wheel and is used for measuring the rotary encoder of land wheel rotating speed, because four joint profiling mechanism, land wheel can adjust height according to actual operation terrain, makes land wheel always can be pasted to ground in the operation process, avoids idling, skidding, rotary encoder adopts the component that can access big dipper system, in addition to direct measurement land wheel rotating speed, still can combine big dipper system to the speed, track data of operation vehicle, judges the advancing speed of operation vehicle comprehensively, improves the precision of seeding / fertilizing.

The application discloses a content-tracing-based enterprise culture hot word analysis method, and relates to the technical field of enterprise culture analysis.The method comprises the following steps: collecting culture-related original data from three dimensions, and constructing an enterprise-specific culture term library through preprocessing, density peak clustering, de-redundancy and matching with top-level culture elements; classifying enterprise internal texts to be analyzed according to departments and text types, automatically matching terms of corresponding categories in the enterprise-specific culture term library, and performing directional word segmentation based on preset rules; calculating the scene coverage of terms according to department scenarios and text type scenarios, calculating the culture correlation degree by using Jaccard similarity, and screening core hot words by combining the Apriori algorithm; locking target hot word origin texts based on the core hot words, counting the track data of the origin text transmission channels, identifying the transmission nodes and constructing the transmission track; and the method improves the accuracy of hot word analysis and provides support for targeted promotion of enterprise culture.

The disclosure provides an eye tracking-based data generation method, a model training method and related equipment. The data generation method comprises: acquiring a plurality of first eye images and a plurality of first masks corresponding to the plurality of first eye images; training an initial model based on the plurality of first eye images and the plurality of first masks to obtain a target model; generating a plurality of gaze information and a plurality of second masks corresponding to the plurality of gaze information based on an eye model; inputting the plurality of second masks into the target model to obtain a plurality of second eye images; and generating a plurality of eye tracking data based on the plurality of second eye images and the plurality of gaze information.

The application relates to a method for generating a track of a ground transportation tool, a computer device, a readable storage medium and a program product. The first historical track data is determined based on the original historical track data and historical event data of the transportation tool in the ground. The second historical track data is determined based on the available path data and historical event data corresponding to the ground. The corrected historical track data corresponding to the historical time period of the transportation tool is generated according to the matching result of the first historical track data and each second historical track data. Compared with the traditional track generation by using the latitude and longitude data, the original historical track data, the historical event data of the transportation tool and the available path data of the ground are combined to correct the track of the transportation tool from multiple angles, so that the accuracy of the track generation of the ground transportation tool is improved.

This invention discloses a multi-dimensional data-driven quantitative assessment method and system for team situational awareness, relating to the fields of aviation safety and human factors engineering. The technical problem it addresses is that existing multi-dimensional data suffers from inconsistent dimensions and a lack of quantitative team collaboration, making it difficult to directly assess team situational awareness. This invention collects evaluation data and eye-tracking data from team members during task execution. Based on subjective data, it calculates individual situational awareness scores and constructs a team collaboration coefficient. Using the weighted average of individual situational awareness scores as a benchmark, it applies the team collaboration coefficient nonlinearly to obtain a comprehensive team situational awareness score. This score is then standardized and correlated with the eye-tracking data to obtain the analytical results. This invention achieves a quantitative assessment of team situational awareness by fusing subjective and objective data, providing a reference for evaluating team cognitive status.

The application relates to the technical field of agricultural intelligence, and discloses a working area accurate calculation method and device based on classification-clustering bidirectional feedback, which comprises the following steps: determining target track data generated by a farm machine during working; performing working state classification processing on the target track data by using a target classification model to determine a target working data set of the farm machine; wherein the target classification model is determined by iteratively training an initial classification model by using suspicious track data in the target track data; and performing area calculation on effective plot units in the target working data set to obtain a target working area of the farm machine. By iteratively training the initial classification model, the target classification model can continuously learn and correct classification errors, compared with a single classification model, the target classification model can effectively reduce misjudgment and missed judgment, significantly improves the accuracy of the final working area calculation result, and can meet high-standard application requirements.

This invention discloses an adaptive wavelet denoising method for noise characteristic verification of PEPT trajectory data. The method first performs statistical analysis on the PEPT trajectory data under static conditions to obtain its noise characteristics. Then, it uses an adaptive wavelet denoising method to obtain the denoised PEPT trajectory and noise data. It then verifies whether the statistical characteristics of the filtered noise data conform to the noise characteristics under static conditions. Based on the verification results, the denoising parameters are dynamically adjusted for iterative feedback until the verification conditions for noise characteristics are met, at which point the method stops. This method uses "filtered components conforming to noise characteristics" as the convergence criterion, providing an objective statistical verification basis for denoising quality. It can effectively filter out as much noise data as possible from the PEPT trajectory without excessively smoothing out the real high-frequency motion. Moreover, it does not rely on the prior motion model of the tracer particles, thus having stronger universality.

The present disclosure is related to a peripheral containing an eye tracking device, a controller, and a battery. The peripheral may be able to receive a user device. When the user device is connected to the peripheral, the eye tracking device may transmit eye tracking data to the user device, and the controller may dynamically charge the user device, as well as power the eye tracking device.