4714 results about "Virtual reality" patented technology

The invention provides an intelligent rehabilitation training method and system based on artificial intelligence and virtual reality, a user wears an intelligent wearable device to collect multi-modal data such as electroencephalogram, myoelectricity, physiological features and motion signals, the multi-modal data is preprocessed and then input into an artificial intelligence training model, and key features are extracted and fused by using a graph convolutional network and an attention mechanism algorithm. And constructing a digital twinborn model by using the fusion features, performing real-time dynamic mapping and predictive simulation, and generating a customized training scheme by means of a reinforcement learning algorithm in combination with a rehabilitation target and a physical state of the user. A user is trained in the virtual reality interaction model, the system monitors actions and physiological states in real time, the digital twin model synchronously acts, and the scene is dynamically adjusted. After training, the rehabilitation effect is evaluated according to the physiological indexes, the motion data and the twinning optimization analysis result, and an optimization training scheme and a digital twinning model are fed back. Precision, individuation and intelligentization of rehabilitation training are achieved, and the training effect and quality are improved.

The invention discloses an intelligent system and method for early screening of depression based on electroencephalogram-eye movement multi-modal data fusion. According to the system, in a virtual reality situation, emotion and cognitive response of a subject are stimulated through an elaborately-designed cognitive task, and brain electrical activity and sight behavior data are synchronously collected by adopting a wearable EEG device and a high-precision eye tracker. After signal preprocessing and feature extraction, deep fusion of multi-modal data is realized by using a weighted fusion formula or a graph neural network, the weight of each modal is automatically adjusted, interaction features between electroencephalogram and eye movement are extracted, and then the depression risk of a subject is accurately judged through a classifier. Experiments show that the method can effectively capture weak physiological abnormalities of mild depression patients, has the advantages of high sensitivity, high accuracy and real-time online screening, and meets the requirements of non-invasive, portable and intelligent clinical application.

A real-time system for the multimodal generation of virtual reality scenes based on artificial intelligence for the creation of immersive three-dimensional environments from natural language narratives, consisting of: a speech capture module configured to continuously record a user's spoken narrative via one or more directional microphones, preprocesses the captured signal by noise reduction and temporal alignment, and outputs a digital speech stream; A speech-to-text processing unit that is operationally coupled to the speech capture module and configured for real-time speech recognition using a continuous neural transformer model. The unit is trained to transcribe natural language utterances into structured text data while maintaining contextual continuity throughout the evolving narrative. a semantic interpretation processing unit that is communicatively linked to the speech recognition unit and configured to perform natural language understanding techniques to extract contextual entities, spatial references, temporal relationships, and object attributes from the transcribed narrative; the engine includes a large language model that is fine-tuned for spatial reasoning tasks; a scene graph generation module configured to transform the interpreted semantic data into a structured, hierarchical representation that defines nodes for identified entities and edges for corresponding relationships, with each node associated with metadata describing geometry, position, orientation, texture, and linking attributes between objects; a multimodal image-language model processor coupled with the scene graph generation module, wherein the processor is configured to retrieve, adapt, or synthesize appropriate three-dimensional elements from a pre-trained visual-lexical embedding space and align these elements with their semantic and spatial definitions derived from the scene graph; a scene assembly and rendering controller configured to create a cohesive virtual scene from the aligned assets, perform real-time rendering using a GPU-accelerated ray tracing pipeline, and produce a stereoscopic visual output that corresponds to the evolving narrative; A head-mounted virtual reality visualization device connected to the rendering engine and configured to display the generated immersive environment to the user in real time. The device features motion sensors and inside-out tracking cameras to detect head and body movements, dynamically updating viewing angles and perspective within the rendered scene; and a bidirectional feedback module integrated into the head-mounted device and connected to the semantic interpretation processing unit; the module is configured to interpret corrective commands, gestures, or supplementary comments from the user to refine or modify specific scene elements without interrupting the real-time visualization; The system continuously updates the virtual scene as the narrative develops, ensuring temporal synchronization between speech input and rendered output below a defined latency threshold, thus enabling a natural, dialogic construction of complex three-dimensional virtual environments.

The invention discloses an intelligent inspection method for fusion of Internet of Things and virtual reality based on an AI large model, particularly relates to the technical field of industrial intelligent inspection, and is used for solving the problem of end-to-end response lag caused by multi-modal data fusion delay and resource competition under an existing layered architecture. The method comprises the following steps: synchronously acquiring heterogeneous data of target equipment through a multi-source sensor and visual equipment, and generating time-space synchronous data through cross-modal feature extraction and time-space alignment; computing resources are dynamically allocated to an AI model or a rendering pipeline in combination with cross-modal correlation analysis and environmental interference assessment, and key tasks are preferentially guaranteed to be executed; performing deep correlation reasoning on the multi-modal data by using an AI large model, and generating equipment state features and an abnormal region mask; and finally, superposing the abnormal features and the three-dimensional scene through a virtual-real fusion rendering technology to form a visual interaction interface. Efficient fusion and real-time interaction of multi-modal data are realized, and the accuracy of anomaly detection and the decision response efficiency of an operator are remarkably improved.

The invention provides an augmented reality cooperation system for a cloud desktop, and the system comprises a cloud service module which generates a virtual desktop image, and carries out the resource monitoring and data storage; the AR equipment is used for collecting data and interacting with virtual reality; the collaborative rendering module is used for fusing AR rendering and virtual reality; the interaction module is used for a multi-modal interaction mode and personalized recommendation; the intelligent scheduling module is used for dynamic resource allocation, resource prediction and optimal management; the network optimization module is used for designing a layered edge architecture and introducing a QUIC protocol to carry out optimized transmission of data streams; the security module is used for carrying out encryption transmission and verifying the identity and access of the user; and the compatible module is used for defining standardized interfaces and protocols and realizing multi-platform support. Functions and resources can be deeply fused, the problems of network dependence, interaction precision, resource allocation and the like are solved, optimal AR presentation and experience effects are provided, and various application scenes are supported.

A system for dynamic latent space adaptation using spatiotemporal kernel context for multiscale rendering with hierarchical and Lorentzian autoencoders. The Spatiotemporal Kernel Estimator (SKE) analyzes media through motion field, temporal recurrence, frequency band, and scene semantics analyzers to generate adaptive kernel parameters encoding content-specific importance distributions. The system dynamically adapts latent manifold geometry by modifying metric tensor properties according to kernel context, enabling content-aware compression that allocates representational capacity based on visual significance. A multiscale cache implements kernel-adaptive retention policies prioritizing important regions. An adaptive renderer provides intelligent level-of-detail selection based on zoom level and kernel-estimated importance, optimizing processing allocation. The self-optimizing architecture continuously refines kernel context and geometric adaptation based on user interaction and performance feedback, achieving superior compression ratios and perceptual quality. Applications include bandwidth-efficient video streaming, virtual reality, scientific visualization, and cognitive video analytics requiring intelligent context-aware visual processing.

The invention relates to the field of virtual reality positioning, and discloses a VR large-space positioning interaction system based on multi-modal perception, and the system comprises the steps: deploying a multi-modal sensor to obtain sensing data, carrying out the visual feature extraction and preprocessing, building a sparse point cloud map in a matching manner, carrying out the scale calibration, and constructing an environment model; pre-judging a UWB signal path based on an environment model, performing error optimization compensation on an NLOS state, and performing observation updating and fusion through degradation detection to obtain a predicted state change; constructing an interactive perception network, and tracking the hands and the whole body; tactile feedback is realized by using a layered tactile system, and a tactile effect is generated by using vibration frequency mapping; the transmission efficiency is improved by using a beam forming technology, an edge cloud server cluster renders a virtual scene, and the scene is pre-rendered in advance to offset network and rendering delay; an online calibration mechanism is designed, and system errors are corrected through visual loopback detection, UWB beacon dynamic correction and IMU drift compensation.

Provided are a processing system for a three-dimensional model, a method for obtaining a physical model on the basis of three-dimensional printing of a three-dimensional processing system, a system for generating a three-dimensional model from a virtual reality / augmented reality three-dimensional sketch, a diffusion model training method, and a method for editing a three-dimensional model on the basis of a virtual reality / augmented reality three-dimensional sketch. The method for obtaining a physical model on the basis of three-dimensional printing of a three-dimensional processing system comprises: step one, at an input apparatus, a user using a hand or a handle to draw three-dimensional sketch content in the air, wherein a three-dimensional sketch is stored in the form of a three-dimensional point cloud, and when the user draws a trajectory, a corresponding point cloud is generated in the drawn trajectory and is displayed in a three-dimensional virtual space in a highlighted manner, and displacement and deletion operations of the user for the three-dimensional sketch are overall displacement and deletion operations for points in a region corresponding to the point cloud of the three-dimensional sketch; step two, a computing apparatus converting the three-dimensional sketch content into a three-dimensional model; step three, converting the three-dimensional model into a readable file for an execution apparatus, wherein the conversion is implemented by using a slicing algorithm; and step four, a three-dimensional printer executing the readable file to perform a printing operation, so as to obtain a physical model.

The invention discloses a cognitive impairment assessment system and method based on general artificial intelligence, and the method comprises the following steps: S1, collecting multi-modal data through a wearable device, a mobile application and an online tool; s2, carrying out preprocessing on the multi-modal data; s3, comprehensively analyzing the preprocessed data, evaluating cognitive competence, and identifying a cognitive impaired field; s4, a rehabilitation training plan is generated through a neural evolution algorithm, and the training content, sequence, difficulty and type are dynamically adjusted; s5, providing cognitive training and adjusting tasks in real time through virtual reality and augmented reality technologies; s6, predicting cognitive load and psychological state, and dynamically adjusting the intervention plan; and S7, protecting data privacy by using a block chain technology, monitoring a training effect, and generating a progress report. According to the method, the intervention plan and the privacy protection technology are dynamically adjusted through multi-modal data analysis based on general artificial intelligence, and a personalized and real-time cognitive impairment assessment and intervention scheme is provided.

A high-fidelity three-dimensional reconstruction method for a specular reflection plane comprises the steps of decomposing pixel colors into diffuse reflection and specular reflection components based on a 3D Gaussian sphere, introducing a dynamic reflection ratio parameter and a spherical harmonic function coefficient to respectively represent two reflection characteristics, and simulating light multi-reflection behaviors through weight fusion of cumulative projection and a reflection ratio map. Secondly, in combination with monocular inverse depth calibration, depth smoothing constraint of color gradient weighting and edge mutual exclusion loss, geometric consistency is enhanced, and artifacts are suppressed; a progressive multi-resolution training strategy is further adopted, low resolution is gradually optimized to complete resolution, reflection parameters are activated in stages, 3D Gaussian sphere overgrowth and floating artifacts are inhibited, and efficiency and precision are balanced. According to the method, the reconstruction fidelity of the specular reflection scene is remarkably improved while the real-time rendering advantage of the 3DGS is reserved, and the method is suitable for the high-precision modeling fields of virtual reality, augmented reality and the like.

The invention provides a game cartoon character display method based on a virtual reality technology. The method comprises the following steps: acquiring three-dimensional model data of a game cartoon character in a target display area through a user interaction terminal; the virtual reality content management platform determines a dynamic rendering precision level according to the model data, and generates a real-time rendering strategy including a model patch reduction coefficient, a texture compression rate and a skeleton animation updating frequency in combination with terminal performance parameters; the strategy is sent to a virtual reality supervision platform and a user interaction terminal, and a virtual reality rendering engine platform is instructed to execute real-time rendering; and the virtual reality supervision platform monitors the frame rate fluctuation data of the head-mounted display device, calculates the scene rendering stability, sends a rendering optimization instruction if the scene rendering stability is lower than a threshold value, and adjusts the model data acquisition frequency and the video memory cleaning period to optimize the performance. The rendering efficiency and the system stability can be improved, and the hardware load and the frame rate fluctuation are reduced.

The invention provides a cardio-pulmonary resuscitation training system based on multi-modal artificial intelligence in combination with a virtual reality technology, and relates to the technical field of virtual reality, and the system comprises a multi-modal sensing module which is used for collecting posture data, mechanical data and environment data; the multi-source data collaboration module is used for generating an operation quality evaluation parameter set and establishing a mapping relation between the operation posture and the pressing efficiency; the virtual scene construction module is used for generating a virtual first-aid environment according to a preset first-aid scene template and the operation quality evaluation parameter set; the decision module is used for generating a feedback control signal; and the interactive closed-loop execution module is used for inputting the feedback control signal into the virtual first-aid environment and updating the operation quality evaluation parameter set according to the operation data after feedback response. According to the invention, standardized, intelligent and scene-diversified cardiopulmonary resuscitation skill training can be realized, and the technical problems of inaccurate posture evaluation, non-personalized feedback, single scene, high resource dependence and the like in traditional training are solved.

A computer-implemented system and method for pupil-directed retinal projection in near-eye displays are disclosed. The computer-implemented system provides smart glasses with directed physical pixels that project light beams / signals directly onto a user's retina based on pupil position and size. The glasses comprise a frame, lenses with directed pixel layers, and sensors for tracking pupil movement. Each directed pixel may generate multiple virtual pixels by rapidly changing its emission angle. The glasses function as prescription lenses, virtual reality displays, and augmented reality devices without traditional optical systems. Additional features include depth sensors, cameras, and connectivity to peripheral devices. The glasses enable a seamless blend of virtual and real-world experiences, creating an immersive “Mixverse” environment. Various input methods, including gesture recognition and brain-computer interfaces, allow for intuitive control and interaction.

The invention discloses a virtual reality scene three-dimensional reconstruction method and system based on multi-source data fusion, and relates to the technical field of underground commercial and traffic integrated space scene three-dimensional reconstruction. The system constructs a multi-dimensional data set through synchronous acquisition of point cloud, images, poses, positioning and semantic text information; a three-dimensional convolutional neural network is adopted to establish an AI reconstruction fusion model, and a three-dimensional model is generated; the system calculates a structural integrity evaluation coefficient JGPG, a fusion consistency evaluation coefficient RHPG and a VR interaction adaptability evaluation coefficient VRJH, compares the coefficients with corresponding thresholds, triggers an optimization strategy, and finally completes model adaptability optimization and packaging output, thereby improving the reduction degree and interaction performance of a virtual reality scene.

The embodiment of the invention provides a filling production line control method and system based on a virtual reality technology. According to the embodiment of the invention, the method comprises the steps: synchronously collecting a real-time dynamic parameter set of a fluid medium, constructing a dynamic coupling factor, generating a dynamic response coefficient matrix through a fluid coupling identification model, generating a nonlinear control parameter combination according to the dynamic response coefficient matrix, and inputting the nonlinear control parameter combination into a motion trail planner. Generating an optimized motion track instruction, driving an execution mechanism to execute filling operation according to the optimized motion track instruction through a servo controller, monitoring the deviation degree in real time, reconstructing the fluid coupling identification model when the deviation degree exceeds a preset threshold value, and updating a dynamic coupling factor; the nonlinear control parameter combination is corrected through the updated dynamic coupling factor, a closed-loop interlocking control mechanism is generated, and the technical scheme provided by the embodiment of the invention not only improves the intelligent level of a filling production line, but also improves the precision and stability in the filling process.

The invention discloses a video stream processing method for dynamic Gaussian compression and adaptive code rate regulation, which is suitable for scenes such as virtual reality, augmented reality and three-dimensional video, and comprises the following steps: S1, Gaussian attribute modeling and initialization; s2, constructing a binary hash grid; s3, constructing a deformation prediction network; s4, designing a mask pruning mechanism; s5, entropy modeling and arithmetic coding and decoding module design; s6, model training; and S7, video stream transmission under multiple code rates. According to the method, a unified scheme combining Gaussian volume cloud coding and adaptive video transmission is proposed for the first time, the video data storage and transmission cost is remarkably reduced, and the comprehensive performance superior to that of an existing method is obtained on multiple real and synthetic data sets.

The invention discloses a 500kV standardized switching operation method based on a VR virtual reality technology, and aims to solve the problems of unreal environment, incomplete evaluation and low efficiency in the switching operation training of an existing 500kV transformer substation. The method comprises the following steps: constructing a full-immersive virtual reality scene, collecting actual environment data of a transformer substation, and constructing and optimizing a high-precision model; designing multi-modal interaction of the standardized switching operation process, wherein the multi-modal interaction comprises visual guidance, a multi-modal interaction interface and an intelligent sensing function; dynamic action scoring and intelligent behavior evaluation are realized, actions are captured in real time by using high-precision action capture equipment, an instant score is generated by comparing with a standard, and dynamic feedback is provided; and real-time optimization and learning migration of the virtual character model are realized, user operation habits are captured, virtual character actions are optimized, and multi-scene migration and adaptation are realized. The method is suitable for VR-based 500kV standardized switching operation work, and the training authenticity and efficiency are improved.

The invention relates to an immersive VR psychological detection system and method based on multi-modal AI. The system comprises a data acquisition and processing module which is used for acquiring a multi-modal data set of a user in a virtual reality scene based on unified clock synchronization, performing time-space alignment and noise reduction standardization processing on the multi-modal data set, and extracting key biological characteristics. And the correlation model construction module performs space-time correlation mapping through a spatial transformation network, constructs a three-dimensional space attention model, and generates a real-time fluctuation curve after inputting the key biological characteristics into the trained model. And the state report generation module identifies a real-time fluctuation curve by using a time sequence analysis model, performs backtracking analysis in combination with the psychological state conversion node and a multi-modal cross validation result, and finally generates a three-dimensional interactive report. By adopting the method, multi-modal data fusion can be realized, the dynamic change of the psychological state of the user can be effectively captured, the psychological state of the user can be comprehensively and deeply analyzed, and a scientific basis is provided for psychological health assessment and intervention.

The invention provides a PICC puncture virtual simulation training system and method constructed based on XR. A nursing skill simulation training platform and an intelligent training room based on augmented reality (XR) combine a simulation medical technology, an artificial intelligence large model, XR intelligent hardware, intelligent agent application, space calculation, computer vision and a mainstream technology of Internet of Things in scheme planning and design. According to the PICC puncture virtual simulation training platform, the ground practice, standardization, high virtual simulation and adaptive application of PICC puncture virtual simulation training are realized, and the intelligent development process and teaching concept of PICC puncture teaching are improved. According to the PICC puncture teaching system, intelligent virtual tutors, puncture teaching holographic three-dimensional sharing, virtual reality fusion technologies and the like are provided, an interactive teaching mode can be brought to PICC puncture teaching, the interest of students in teaching and clear operation guidance are improved, the theory and practice are fused, and the clinical cooperation ability is improved.

Head-mounted displays with waveguides comprising superimposed diffractive gratings and methods for fabricating said waveguides are described herein. In an embodiment, a head-mounted display comprises an optical element and an image source that provides an image beam to an optical element. The optical element comprises two gratings superimposed over each other, at least one of which comprising a buried diffractive grating. The buried diffractive grating comprises a high-refractive index material interspersed with a low-refractive index material or non-solid pockets, such as gas, air or vacuum. Light diffracted by a first of the two gratings is further diffracted by a second of the two gratings without interacting with a surface of the optical element between diffractions.

The invention provides a motion fear intervention device based on virtual reality. The motion fear intervention device comprises a VR scene generation module; the subjective evaluation module presents the TSK scale to the user to obtain a TSK scale score of the user, and obtains a TSK grade corresponding to the TSK scale score according to the TSK scale score; the biological signal acquisition module is used for acquiring biological feedback of a user and calculating a comprehensive exercise fear grade according to the following formula: the comprehensive exercise fear grade = alpha * TSK grade + beta * HRV score + gamma * GSR score + delta * pupil change score + belonging to * EMG score; the dynamic intervention module is used for generating scene parameters in real time according to the comprehensive exercise fear level and inputting the scene parameters into the VR scene generation module to generate a corresponding scene; the dynamic intervention module is also used for providing forward excitation. According to the method and the device, the currently displayed VR hierarchical scene is adjusted through biological feedback, and closed-loop feedback adjustment of motion scene stimulation is realized.

The invention discloses a scene building method and system based on three-dimensional reconstruction. The method comprises the following steps: collecting a multi-view two-dimensional image of an environment; preprocessing the obtained two-dimensional image, and automatically identifying and labeling different objects and areas in the image by applying a semantic segmentation technology to understand semantic information in the image; according to the marked two-dimensional image data, reconstructing a three-dimensional model from the two-dimensional image by using a multi-view geometric three-dimensional reconstruction algorithm based on bundle adjustment, and storing the reconstructed three-dimensional model as a sub-scene model; according to the method, the three-dimensional model is accurately reconstructed by collecting the multi-view two-dimensional image and applying the semantic segmentation and bundle adjustment technology, the technical bottleneck of real-time rendering of a complex scene is solved, and the scene building efficiency and precision are improved; and in combination with the generative adversarial network and the variational auto-encoder optimization model, authenticity, detail expressive force and diversity are enhanced, and rich and real scene experience is provided for the field of virtual reality.

The invention provides a CT guided liver puncture training method and system based on virtual reality, and relates to the technical field of virtual reality. A deformable liver model and a virtual CT reconstruction engine under respiration driving are constructed, needle body posture mapping and image fusion display are achieved by fusing an inertia-electromagnetic dual-mode sensor, path interaction control, tissue dynamic response and score feedback are supported, the scene difficulty is automatically adjusted based on a training result, and the accuracy and the reliability of the system are improved. Progressive puncture skill training of static breath-holding, shallow breath and free breath scenes is achieved, the sense of reality of training, operation feedback and teaching efficiency are improved, and the system is suitable for development and clinical teaching application of an interventional therapy training system under the guidance of medical images.

The invention relates to the technical field of risk management, and discloses an asset and risk management-oriented dynamic risk visual management method, which comprises the following steps of: automatically scanning to obtain asset information in a network, and classifying assets; based on the asset information, determining a connection relationship between assets, and constructing a network topology structure diagram; based on a vulnerability database, vulnerabilities existing in the assets are analyzed, an attack graph is generated, and a preset attack path is determined; analyzing a preset attack path to determine an attack path in combination with the network flow data and an attack technique; evaluating the security defense system in the attack path by using a simulated attack technology, and determining the defense efficiency; based on augmented reality and virtual reality technologies, vulnerabilities, attack paths and defense efficiency of each asset are dynamically displayed on a network topology structure diagram. The invention provides an efficient, intuitive and dynamic risk visualization management method by combining various technologies, and the asset management and risk response capabilities can be remarkably improved.

The invention discloses an interactive virtual reality generation method, and belongs to the technical field of virtual reality, and the method comprises the steps: collecting the spatial position and motion data of a user through a pose sensor and a somatosensory sensor, carrying out the three-dimensional point cloud reconstruction and interaction plane parameter extraction through an edge calculation processor, and calling a matched virtual object model to generate an initial scene. A dynamic prediction model is loaded to predict influence parameters of user actions on a scene, scene evolution is calculated in real time in combination with a digital twin engine, and a result is transmitted to a multi-mode feedback module to generate visual, tactile and auditory feedback instructions. And the scene dynamic adjustment module is triggered to adjust the physical attribute parameters by monitoring the bio-electricity signal in real time. According to the method, geometric constraint consistency and semantic reasonable matching of a virtual scene and a real environment are realized through multi-source sensor data fusion and edge calculation, user actions are dynamically responded by combining space-time prediction and a digital twinning technology, scene physical attributes are adaptively adjusted on the basis of bio-electricity signals, and multi-modal feedback cooperation is assisted, so that the user experience is improved. And the reality, immersion and user comfort of virtual reality interaction are obviously improved.

The invention provides an audio processing device and method, an augmented reality device, equipment and a storage medium, and belongs to the technical field of virtual reality display and sensing. The audio processing device comprises a positioning device which is configured to track and position a user in a real space in real time, determine positioning information of the user and send the positioning information to a processor; the processor is configured to determine target positioning information of the user based on pre-established spatial information and the real-time positioning information of the user; determining association relationship information between the user and a virtual sound source in a virtual space based on pre-established space information and real-time target positioning information of the user; obtaining human body parameters of the user, and determining an audio filtering result matched with the user based on the association relationship information, the human body parameters and the audio frequency of the virtual sound source; and reconstructing the audio to be played based on the audio configured for the virtual sound source in advance and the audio filtering result.

Systems and methods are provided for facilitating an interactive artificial-reality activity. A method includes, after a user of a head-wearable device has opted-in to using an artificial-reality application to facilitate connecting with other participating users, determining, based on user-specific suggestion criteria, that a suggested user is located in an approved common space with the user and has opted-in to use the artificial-reality application. The method includes causing the head-wearable device to present an user interface (UI) element for linking the suggested user and the user. Upon the user selecting the UI element for linking the suggested user with the user, the method includes automatically causing the head-wearable device to provide visual-guidance UI elements to navigate the user to an interactive-activity location where the user and the suggested user will perform an artificial-reality activity while also displaying information about the artificial-reality activity to be performed.

The invention discloses a single-view large-scale outdoor scene three-dimensional reconstruction method based on three-dimensional Gaussian splashing, and the method comprises the steps: collecting a pseudo aerial image, and constructing a panoramic multi-mode supervision end-to-end single-view three-dimensional reconstruction model; meanwhile, panoramic consistency supervision, semantic constraint depth regularization and a radial weighted luminosity loss and Gaussian cutting mechanism are introduced, so that the defect of insufficient geometric constraint of traditional single-view three-dimensional reconstruction is effectively overcome, and high-efficiency and high-fidelity three-dimensional modeling of a large-scale outdoor scene under single image input is realized; the method is suitable for various actual scenes such as smart city construction, automatic driving simulation, virtual reality / augmented reality, digital twinning and the like.

The invention discloses an intelligent water conservancy three-dimensional twinborn scene construction method and system, and relates to the technical field of intelligent water conservancy, and the method comprises the steps: collecting scene data in real time through a multi-source sensor disposed at a water conservancy facility site, including hydrological parameters, facility structure data, environment image data and ecological monitoring data; performing space-time alignment and deviation correction on the scene data by using a deep learning driven multi-modal feature fusion algorithm to generate a three-dimensional water conservancy grid model of a unified coordinate system; according to the real-time data updating frequency and the environment change trend, a local or global updating strategy of the three-dimensional water conservancy grid model is adaptively adjusted, the optimized three-dimensional water conservancy grid model and a virtual reality engine are integrated, and a twin scene supporting gesture interaction is constructed; an ecological simulation module is embedded in the twinborn scene to dynamically evaluate the influence of water conservancy activities on water quality and biological habitats.

The invention provides an immersive concert experience system based on virtual reality, and belongs to the technical field of virtual reality, and the system comprises a dynamic adjustment module which is used for predicting the preference of a user for stage arrangement, light effects and music types through a machine learning model according to the historical preference data of the user, and outputting the preference to the stage arrangement, light effects and music types; dynamically adjusting visual elements and sound field parameters of the virtual scene and a refresh rate and a field angle of the virtual scene in combination with the user physiological indexes and the user head motion trail which are acquired in real time; the action capture and feedback module is used for capturing an interaction instruction sent to the dynamically adjusted virtual scene by the limb action of the user in real time; and the interaction feedback module is used for enabling the virtual performer to respond to the interaction instruction of the user in real time based on the expression recognition and voice synthesis technology, and generating personalized interaction feedback content. A user constructs an immersive music interaction field domain, and experience logic of a virtual music meeting is completely reconstructed.