2754 results about "Sight line" patented technology

The invention is suitable for the technical field of earth surface monitoring, and provides an earth surface deformation monitoring method and system based on a time sequence InSAR, and the method comprises the following steps: carrying out the SAR image screening and interferogram generation, and collecting corresponding meteorological data and thermal infrared data; performing space-time adaptive atmospheric phase correction, taking the air pressure vertical gradient and the temperature anomaly as driving factors of atmospheric delay, and separating an atmospheric phase through a space-time weighted model; dynamic deformation modeling is carried out, and deformation is decomposed into linear deformation and nonlinear deformation; the method comprises the following steps: taking a mining area road network as a geometric constraint, unwrapping a coherent region by adopting a minimum cost flow algorithm, converting an unwrapping phase into sight-line-direction deformation, and calculating horizontal and vertical deformation components in combination with InSAR sight-line-direction deformation and a digital elevation model. The method adapts to a complex deformation mechanism of a mining area by capturing linear and nonlinear deformation. Through sight line deformation and DEM geometric projection, vertical and horizontal deformation separation is realized, and the deformation direction is determined.

A WTRU may be configured to receive first configuration information associated with a channel state information reference signal (CSI-RS) resource set, a set of transmission configuration index (TCI) states, a set of probability thresholds, and / or a set of time durations. The WTRU may be configured to estimate a line of sight (LOS) probability of the WTRU based on one or more CSI-RS measurements. The WTRU may be configured to determine whether the estimated LOS probability is greater than or equal to a probability threshold from the set of probability thresholds. In response to determining that the estimated LOS probability is greater than or equal to the probability threshold, the WTRU may be configured to determine a time duration from the set of time durations based on the estimated LOS probability. The WTRU may be configured to predict a future TCI state applicable to an associated time instance.

The invention discloses a dynamic unmanned aerial vehicle cluster electromagnetic characteristic modeling method and system based on a digital array radar, and the method specifically comprises the steps: setting radar system parameters, building a time-varying motion model of an unmanned aerial vehicle cluster, and obtaining the formation pose distribution of the unmanned aerial vehicle cluster under a global coordinate system; component decomposition is carried out on an unmanned aerial vehicle CAD model, shielding analysis is carried out under the radar sight line constraint condition, time-varying scattering center parameter extraction is carried out according to the dynamic electromagnetic effect between targets, scattering center space distribution of an unmanned aerial vehicle cluster is updated in a time sequence recursion mode, and construction of a time-varying scattering center model is completed; a radar system signal model is constructed according to digital array radar DAR parameters, multi-dimensional dynamic feature extraction and parameter mapping are carried out, digital array radar multichannel signal modulation and unmanned aerial vehicle cluster target radar echo construction are completed, and radar scattering electromagnetic characteristic modeling of a dynamic unmanned aerial vehicle cluster is realized. According to the method, the model description accuracy is improved, and the calculation process is more efficient.

The invention provides a driving behavior intelligent identification method and system based on video analysis, and the method comprises the steps: obtaining a driver face video stream and a road environment video stream collected by a vehicle-mounted camera, and reading the driving information recorded by a whole vehicle communication network; recognizing an eyelid closing state, a sight line direction and a head posture in the driver face video stream based on a posture recognition model, and performing fatigue distraction analysis to obtain driver state information; performing motion trail analysis on the road environment video stream and the driving information, and performing driving risk assessment in combination with the driver state information to obtain driving assessment information; and performing early warning construction according to the driving evaluation information, generating early warning prompt information, and synchronously writing the early warning prompt information, the driving evaluation information and the driver state information into a safety data protection memory. The fatigue and distraction states of the driver can be recognized more accurately, and the accuracy of state judgment is improved.

Various aspects of the present disclosure relate to a use equipment (UE) configured with multiple artificial intelligence (AI) models each of which has been configured (e.g., trained) based on training data sets corresponding to one or more of different conditions, such as location of the UE, orientation of the UE, whether the UE is indoors or outdoors, whether the UE is line-of-sight or non-line-of-sight with a base station, and so forth. A network entity (e.g., a gNB) configures the UE with a set of reference signals for measurement of at least one quantity. The UE generates the measurement report based at least in part on the set of reference signals and one of the multiple AI models, and transmits the measurement report to the network entity (e.g., gNB).

Extended Reality (XR) applications may require high throughput and very low latency. New Radio (NR) Wireless receiver / transmitter units (WTRUs) running XR applications (XR-WTRUs) may be confronted with link failures when these applications are used in dense urban or indoor environments because of these devices operating in the millimeter band. Methods and devices are provided therefore for performing cell selection and beam management proactively to avoid link failure due to objects being in line of sight between the XR-WTRU and a network node with which it has established a connection. XR-WTRUs may therefore perform visual sensing that may enable visualizing current and future radio environment and using this information to prevent link failures by handing the XR-WTRU over to an alternative network node in line of sight of the XR-WTRU before the XR-WTRU is no longer in line of sight of the network node with which it has established a connection.

The invention provides a high-dynamic deformation measurement system and method based on laser section contour differential scanning. The measurement system is composed of a section contour measurement unit, a calibration unit, an error compensation unit and a data processing unit, wherein the section contour measurement unit comprises a multi-sight-line structured light sensor module, a speed sensing module and a distance measurement module; the calibration unit comprises a synchronous control module, an adjustment module and a common tooth-shaped calibration target; the error compensation unit comprises a vibration detection module, a posture detection module and a temperature detection module; the data processing unit is a device with programming and computing functions. The measuring method comprises the following steps: (1) calibrating a laser plane and an image plane; (2) unifying a global coordinate system; (3) obtaining point cloud data; (4) error compensation; (5) constructing a deformation time-history model; and (6) carrying out maximum deformation global optimization. According to the measurement system and method, accurate expression and maximum value global optimization of a pavement micro-deformation three-dimensional space under the load effect can be realized.

The invention relates to the technical field of vehicles, in particular to an intelligent cabin man-machine cooperative control method and device, a vehicle, a medium and a product. Performing fusion processing on the voice signal data, the visual signal data and the tactile signal data of the current driver by using a preset dynamic weight distribution model to obtain a multi-modal fusion control instruction; and under the condition that the multi-mode fusion control instruction meets a preset sight-voice dual-mode condition, synchronously issuing the multi-mode fusion control instruction to a plurality of target execution devices in the intelligent cabin so as to drive each target execution device to perform cooperative control. Therefore, by constructing a cooperative control mechanism of multi-mode sensing and dynamic weight distribution, the problems that the false wake-up rate is high, the voice and graphical interface cooperative efficiency is low and the interaction mode cannot adapt to a complex driving environment due to a single or separated interaction mode in the related technology are effectively solved.

The embodiment of the invention discloses a visual field tracking method and device, and the method achieves the differential weight fusion of an image through a first infrared image set, greatly reduces the influence of a tear film, a lens scratch, a cosmetic contact lens line and other interference factors, improves the recognition accuracy of a cornea reflection point, and improves the sight tracking precision. The combined methods of FFT confidence analysis, RANSAC algorithm verification, Kalman filtering, median filtering and the like are adopted, interference of pseudo spots and dynamic noise is effectively reduced, and the stability and reliability of cornea reflection point detection are remarkably improved. The self-adaptive enhancement technology and the ROI accurate extraction method are adopted, so that the method can better adapt to eye feature differences of different users and various complex actual environments and illumination conditions, and the universality of the visual field tracking device is enhanced. Differential fusion, feature recognition, confidence verification and filtering processing are automatically carried out in the whole process, and manual intervention is not needed.

The invention discloses a high-altitude falling simulation system based on VR equipment, and relates to the technical field of virtual reality simulation, and the system comprises a data collection module which collects the pupil distance and initial sight line data of a user; the visual disturbance module is used for dynamically adjusting local visual disturbance of a corresponding area in the high-altitude virtual scene based on the gaze data to form a visual disturbance effect; the psychological index calculation module is used for calculating an anxiety index and a focus drift speed by adopting a time sequence convolutional neural network according to the visual disturbance effect and the eye movement behavior of the user to obtain an anxiety index and a focus drift speed index; and the disturbance adjustment module adaptively adjusts the frequency and amplitude of the visual disturbance effect by adopting a method of combining fuzzy logic control and adaptive gain adjustment to obtain disturbance rhythm parameters. According to the method, the personalized matching ability and training effectiveness in psychological behavior intervention and virtual high-altitude adaptation training are improved.

This invention discloses a 2D gaze point estimation method based on the pupil-corneal reflection vector method. It utilizes the star ray method for pupil center localization and adds a classification pupil detection mechanism for error correction. Corneal feature extraction is performed to obtain the center coordinates of the corneal reflected light spot. Step 4: Establish a gaze mapping model, and assign the detected pupil-corneal reflection vector V(V) to each frame of the image. x V y The gaze coordinates G(G) mapped onto the screen x G y This invention enables 2D gaze point estimation based on the pupil-corneal reflection vector method. Compared with existing technologies, this invention can improve the accuracy of 2D gaze point estimation.

A method by which a device operates in a wireless communication system, according to at least one of the embodiments disclosed in the present specification, comprises: obtaining line of sight (LoS)-related information for at least one reference signal for positioning on the basis of an artificial intelligence / machine learning (AI / ML) model; and transmitting a signal including the LOS related information, wherein the LoS related information may include information about the reliability of determination by the AI / ML model regarding whether each reference signal is provided through the LoS or non-line of sight (NLoS).

The invention provides a three-dimensional flow velocity field inversion method and system based on coherence-assisted SAR adaptive offset tracking, and a storage medium, so as to improve the problem of decoherence caused by time heterogeneity in a synthetic aperture radar interferometry (InSAR) technology, and relates to the technical field of electric power engineering geological disaster monitoring. The method comprises the following steps: establishing a space-time baseline network between SAR images; obtaining coherence data after geocoding; selecting a pair of SAR images from the space-time baseline network as a reference unit, calculating an offset result through a pixel offset tracking technology for the reference unit, and determining an optimal matching window parameter of the reference unit; establishing a mapping function between coherence and optimal matching window parameters; according to the established mapping function, calculating an optimal matching window parameter of each remaining SAR image pair; and in combination with the line-of-sight average deformation rate fields of the ascending and descending rails, inverting a surface three-dimensional flow velocity deformation field of the target area through a geometric vector decomposition model.

The invention relates to the technical field of automobile electronic control, discloses a control system of a three-dimensional interactive automobile atmosphere lamp, and aims at solving the problems that an existing atmosphere lamp is single in function, insufficient in space sense, poor in adaptability and poor in user experience. The system comprises a multi-mode sensing unit which collects environment, operation, passenger behavior and interaction instruction data in real time; the data fusion and situation analysis unit is used for preprocessing the fused data, identifying a prediction situation and generating a situation representation vector; the interaction intention recognition unit is used for analyzing gesture, voice and sight line information of the passenger and recognizing an interaction intention; the three-dimensional light field generation engine is used for dynamically generating a three-dimensional light effect scheme based on the situation representation and the interaction intention; and the distributed light-operated execution network drives the light units to realize a lighting effect scheme. According to the scheme, intelligent dynamic and humanized control over the light environment is achieved, and system intelligence, interaction experience and driving and riding comfort and safety are remarkably improved.

The invention relates to an earth surface deformation detection and classification method and system fusing CNN and SBAS-InSAR technologies, and the method comprises the steps: obtaining high-precision deformation data through a small baseline subset and an interference synthesis radar technology (SBAS-InSAR), constructing a CNN classification frame through combining PCA-enhanced optical satellite images, elevation, soil physical parameters, geological landform maps and other multi-source geographic information, and carrying out the detection and classification of the earth surface deformation through the CNN classification frame and the SBAS-InSAR technology. And identification of deformation types such as landslide, settlement and lifting is realized. The process comprises multi-source satellite data acquisition and preprocessing (including InSAR sight velocity decomposition and optical / topographic feature extraction), generation of a preliminary deformation label based on a classification algorithm of a gradient and a deformation velocity threshold, and recognition of a deformation type through a multilayer CNN model. According to the method, the deformation mode is automatically clustered and analyzed in a large-range area, the accuracy and detail performance of deformation type recognition are remarkably improved, the accuracy rate reaches 93%, the method is superior to a traditional method, a stable and extensible tool platform is provided for geological disaster monitoring, and positive risk management of landslide or land subsidence prone areas is assisted.

The invention relates to a radar synthetic wind speed resolving method, device and equipment and a storage medium, and is applied to the field of radar speed measurement, the radar synthetic wind speed resolving method comprises the steps that radar sight wind speed and the rotation angle of a radar are acquired, and the rotation angle is the angle of a radar roll angle; performing radar beam azimuth calculation according to the rotation angle to obtain a radar beam vector; and performing synthetic wind speed calculation according to the radar sight wind speed and the radar beam vector, and generating scalar wind speed and wind direction. The method has the technical effect that the calculation accuracy of the synthetic wind speed is improved.

The invention discloses a high arch dam global deformation analysis method and system fusing InSAR and measuring point data, particularly relates to the technical field of radar interference deformation monitoring, and is used for solving the problem of inaccurate shielding failure compensation. According to the method, data stability is guaranteed by obtaining InSAR image data and extracting sight line direction displacement in combination with coherence indexes, a key measuring point deformation sequence is collected, an InSAR result is calibrated based on stable reference points, data consistency is improved, a projection correction coefficient is constructed by using a dam body three-dimensional structure model, the sight line displacement is inversely solved into structural normal displacement, and the accuracy of the dam body three-dimensional structure model is improved. Obtaining an initial deformation value of the real structure meaning; according to the method, a spatial coupling map of measuring points and InSAR pixels is constructed for a shielding failure area, deformation compensation of the failure area is completed based on an edge weight, finally the deformation compensation result is remapped to a three-dimensional structure model, measuring point data restoration is performed on a high arch dam, and structural plane-level deformation visualization and trend analysis are realized more quickly and more accurately.

The invention discloses an eye movement tracking method and system based on multi-modal fusion, and particularly relates to the technical field of eye movement tracking, and the method comprises the steps: collecting a face image, an eye image and a head movement parameter of a user through an RGB camera, an infrared camera and an IMU which are synchronously arranged; the signals are processed in parallel, sight line direction vectors based on the face and the eyes and reliability measurement of the sight line direction vectors are extracted respectively, and the head space posture is calculated; dynamically selecting high-confidence cooperation, master-slave compensation or conflict arbitration strategies according to reliability measurement, and fusing to generate an initial sight direction; and mapping the direction to a display plane to obtain an initial fixation coordinate, performing optimization calibration in combination with visual saliency analysis of screen content, and outputting a final fixation point coordinate. The system comprises a signal acquisition and processing module, a parallel computing module, a multi-strategy fusion decision-making module and an output optimization module. According to the invention, through multi-modal information fusion and dynamic strategy selection, the precision and robustness of eye movement tracking are significantly improved.

The invention relates to the technical field of virtual reality and indoor and outdoor design, in particular to a VR indoor and outdoor design virtual material selection system based on eye movement tracking. Comprising a VR display and eye movement tracking module used for presenting a virtual design space to a user and capturing eye movement data of the user in real time; the fixation point recognition and target object judgment module is used for calculating real-time fixation point coordinates of the user based on the eye movement data; the dynamic material menu management module is used for outputting the target object information according to the judgment module; the sight line interaction and material rendering module is used for receiving a selection instruction of a user on a specific material in the dynamic material menu through a sight line; and the central processing module is used for coordinating and controlling data streams and execution logics of the modules. By integrating the eye movement tracking technology and the dynamic material menu management, the intelligent material selection interaction driven by the fixation point is realized.

The invention provides an on-line examination anti-cheating method and system based on AI fusion sight tracking, and relates to the technical field of on-line education safety, and the method comprises the steps: extracting a head motion feature sequence of an examinee, calculating the coordinates and duration of a sight fixation point, analyzing the fixation behavior of a functional region, and recognizing a periodic jump mode in a fixation migration feature map. The gazing mode mutation point is identified by combining autoregression spectrum analysis and wavelet analysis, so that the cheating behavior is accurately identified, the safety and fairness of the online examination are effectively improved, and the misjudgment rate is reduced.

The invention discloses a single-satellite target sight atmospheric refraction correction method and system based on multi-spectral range finding, and relates to the field of atmospheric refraction processing, and the method comprises the steps: determining a target radiation intensity ratio based on two radiation intensities on different wavebands at the same moment; obtaining observation sight lines of the satellite on the measured target on different wave bands at the same moment, and carrying out light trace tracking to obtain a light ray tracking trajectory; determining a target grid through which each ray tracing trajectory passes from the atmosphere gridding model, determining an extinction coefficient of each target grid, and constructing a target function of a radiation intensity ratio with respect to the height of the target from the ground in combination with a radiation intensity calculation formula; determining a target height from the measured target to the ground based on a target function and a target radiation intensity ratio, determining the position of the measured target according to a track point matched with the target height in each light ray tracing track, and determining a sight line vector after atmospheric refraction correction by combining the position of a satellite, therefore, high-precision atmospheric refraction correction under a single-star observation condition is realized.

The invention provides a signal processing method and system for a long-distance follow-up laser seeker, and belongs to the technical field of signal processing. Target surface center coordinates, a light spot image sequence and a synchronous echo pulse waveform sequence of the seeker are obtained; the speckle energy entropy and the centroid drift distance are obtained by calculating the information entropy and the centroid displacement of the target light spot image, and the pulse width parameter is extracted from the echo waveform. And constructing the three parameters into a laser feature vector, and inputting the laser feature vector into a pre-trained reflecting surface classification model so as to identify the surface material type of a laser irradiation point in real time. And determining a group of optimal follow-up control gain sets from the material gain mapping relation according to the surface material type, and dynamically reconstructing a follow-up control loop by using the optimal follow-up control gain sets. And the sight angle error of the light spot mass center and the target center is calculated, and the adjusted control loop is used for calculating the error to generate an accurate driving instruction signal, so that the tracking stability and the tracking precision of the target are improved.

The invention discloses a dynamic rendering method and system for virtual reality, a storage medium and electronic equipment, and relates to the technical field of virtual reality, augmented reality and computer graphics. Therefore, the frequency and time sequence change of the sight focus of the user hitting the surface of the virtual object in the virtual scene are analyzed, so that the relative motion trend and observation intention of the user and the object are pre-judged, predictive and adaptive scheduling of rendering resources is realized, and optical feedback conforming to the physical law, namely, dynamic material, is triggered at the sight focus, so that the real-time performance of the user is improved. Therefore, the interaction fineness in the process of interaction between the user and the VR system is improved.

The invention discloses a virtual-real fusion dynamic calibration method based on binocular eye movement tracking. The method comprises the following steps: step 1, constructing a virtual-real fusion dynamic calibration system based on binocular eye movement tracking; step 2, establishing a calibration coordinate system; 3, solving a conversion relation between the coordinate system of the eye movement tracking camera and the coordinate system of the AR equipment through offline joint calibration; 4, collecting eye movement tracking parameters and modeling user characteristics; 5, constructing a virtual display camera model, and solving an internal parameter matrix and external parameter transformation of a virtual display camera, so that the virtual display camera is geometrically consistent with the real watching behavior of the user; step 6, constructing a conversion relation between an external tracking sensor coordinate system and a virtual display coordinate system, so as to convert the position of the marker to a virtual display camera coordinate system; and step 7, evaluating a system registration error, carrying out on-line fine tuning on key external parameters, carrying out sight line prediction compensation, and adaptively adjusting the pose of a virtual object in a virtual display camera coordinate system.

The embodiment of the invention discloses a classroom attention monitoring method and device, equipment and a storage medium. In a teaching mode, a first video shot by a first camera capable of shooting a human face and a second video shot by a second camera capable of shooting a full view of a classroom are utilized to obtain a moving path of a head of a teacher and a sight path of sight of each student; the classroom attention is monitored through the similarity between the moving path and the sight line path, whether the sight line of the student follows the movement of the teacher in the teaching mode can be effectively monitored, the attention of the student on the teaching content is reflected by following the movement of the teacher, and the attention monitoring accuracy is effectively improved.

The invention provides a space intelligent non-planar reflection generation method based on surface normal guidance. Extracting multi-layer visual representation from an original RGB image containing a non-planar reflection medium scene, and identifying a non-planar reflection area by combining brightness distribution of the original RGB image and a spatial symmetry relation; analyzing non-linear deformation features of textures in the non-planar reflection area, and predicting pixel-level three-dimensional surface normal vectors and confidence distribution in combination with multi-layer visual representation to construct a surface normal graph; determining a line-of-sight vector based on a camera imaging model, and executing geometrical optical mapping operation on the line-of-sight vector, the surface normal graph and the confidence distribution to construct a reflection offset field; extracting an intermediate semantic feature representation corresponding to the non-planar reflection region, and generating a pre-distortion reflection feature representation according to the reflection offset field and the intermediate semantic feature representation; and injecting the pre-distortion reflection feature representation, the multi-layer visual representation and the initial reflection area mask into a generative model for image reconstruction, and generating a non-planar reflection image.

The present invention relates to a system and method for audio, video and data communication using the human body or any other medium as a channel using techniques which benefits from the presence of the human body or the medium. The system comprises a transmitter and a receiver that communicate with each other by utilizing the properties of the human body to enhance signal strength and data rate. The frequencies used for communication may range from 0.1-200 MHz and may employ a variety of modulation schemes, including pulse-based, spread-spectrum, time-domain, and amplitude, phase, and frequency modulation. The communication may be digital or analog and may use single or multi-bit / symbol modulation. The system provides for efficient, secure, and reliable communication that does not require line-of-sight transmission or the use of traditional communication channels. The system finds applications in various fields, including, but not limited to healthcare, military, and entertainment industries.

The invention relates to the technical field of elevators, in particular to an elevator traction machine vibration reconstruction method and system based on a millimeter wave radar. The method comprises the steps that in the elevator running process, echo signals of a millimeter wave radar are collected; firstly, a continuous phase sequence is obtained through echo signals; generating a rough vibration signal in a radar sight line direction according to a phase-displacement mapping relation, calculating a physical confidence coefficient, constructing a dual-channel physical prior tensor, synthesizing a three-axis reconstruction vibration signal tensor by using a PGGN physical gating generation network, and finally performing physical rationality evaluation on the three-axis reconstruction vibration signal tensor. And adjusting the gating parameters of the anisotropic physical gating unit according to the evaluation result. On the premise that a contact sensor does not need to be installed on the surface of the traction machine for a long time, physical consistency reconstruction of the three-axis vibration signals of the elevator traction machine is achieved.

The invention discloses a VR panoramic glasses data synchronization and transmission method based on multi-sensor fusion, and relates to the technical field of computer network and multimedia real-time transmission. Time alignment and unified modeling are carried out on various sensor data such as eye movement, inertia measurement, gestures and environment through extended Kalman filtering; a user head position, a posture, a sight line direction and a gesture action are coded into a single user behavior vector, so that a subsequent system does not face original sensor streams with different formats any more, but makes a decision based on a behavior space with a clear structure, thereby remarkably reducing posture jitter and sight line deviation accumulative errors; a long short-term memory network is introduced to carry out time sequence modeling on behavior vectors and environment contexts, interactive hotspot areas in a virtual scene are predicted, and hotspot distribution is mapped into priority weights of different data streams, so that sensor streams related to fast actions in areas near a sight line can still obtain a relatively high service level when the bandwidth is insufficient.

A method of operating a distance sensor includes emitting pulses of light from an emitter on the distance sensor at one or more designated wavelengths in a non-visible spectrum and receiving a set of reflected pulses of light with a receiver on the distance sensor that correspond to the pulses of light reflected off a surface of an object within a line-of-sight of the receiver. A point cloud is generated of an area including the surface of the object based on the set of reflected pulses of light. A pattern is identified on a surface of the object based on at least one of an area of increased or decreased reflectivity for the one or more designated wavelengths in the non-visible spectrum identified in the point cloud. Embedded data is decoded from the pattern on the surface of the object.