51 results about "Visual expression" patented technology

The invention relates to an intelligent shooting method for scene understanding and script analysis driven by a large science and technology movie and television model, and belongs to the technical field of machine vision. The method comprises the steps that script text features are extracted and decomposed to obtain plot development, emotional fluctuation and artistic style information, a reference film and television work with the maximum overall matching score is selected based on a decomposition result, and an optimal shooting strategy vector is extracted; analyzing the shot scene to generate visual features; fusing the text features and the visual features to obtain a multi-modal semantic representation, and generating a dynamic scene-task knowledge graph according to the optimized multi-modal semantic representation so as to generate a shot scheduling strategy; the shooting process is tracked, the shooting sequence and the lens application mode are monitored in real time, and when it is detected that the shooting sequence deviates, lens connection deviates or visual expression does not conform to expectation, an intelligent optimization mechanism is triggered; and when the deviation exceeds a set threshold value, a manual intervention prompt is given out. The shooting cost can be reduced, and the manufacturing efficiency can be improved.

The invention discloses an AI intelligent image-text situation content accurate layout full-marketing generation method, and particularly relates to the technical field of image-text recognition. The method comprises the following steps: performing semantic analysis on a text input by a user, extracting a deliberate graph item, reverse semantics, an auxiliary emotion item and a tonality keyword, and constructing a multi-semantic field group; the field groups are injected into a collaborative generation engine composed of an image generation sub-model and a semantic prediction sub-model, and the semantic prediction sub-model predicts graph attribute tags and guides the image generation sub-model to conduct regional attention intervention; after the image is generated, the matching degree of the image content and the field group structure is evaluated through a structure-level semantic consistency judgment mechanism, and regeneration is triggered if the image content and the field group structure are inconsistent; finally, the image content with the aligned structure is output and subjected to image-text combination typesetting with the original text, and image-text situation content meeting the multi-platform marketing application requirement is generated. According to the method, the semantic accuracy, the structural consistency and the visual expression quality are remarkably improved while the generation efficiency is ensured.

This disclosure relates to techniques for generating and utilizing custom stickers in a digital communication environment. A technique involves receiving a text-based message input during a chat session and using a generative language model (e.g., a Large Language Model, or LLM) to create a text prompt. This prompt is then used by a generative image model to produce a custom sticker. The generated sticker is sent to a client device where it is displayed in a sticker tray alongside other selectable stickers. Users can select and send these stickers directly within their chat interface, enriching communication with visually expressive and contextually relevant imagery.

The invention relates to the technical field of data acquisition, in particular to a tidal play material acquisition method and system based on big data, and the method comprises the following steps: obtaining an augmented reality creation data stream uploaded by a user terminal through an authorization API interface; performing cross-device feature alignment on the creation data stream to generate a standardized culture gene unit, the culture gene unit comprising a visual expression vector, an interactive semantic tag and a group contribution coefficient; the connection strength between the network nodes of the dynamic culture topology network is jointly determined by the collaborative editing association degree of the user and the culture propagation entropy; and according to node betweenness centrality distribution of the dynamic culture topology network, activating the high-potential culture gene unit and generating a decentralized material acquisition queue. According to the method and the device, the timeliness of material acquisition and the system scheduling efficiency are improved, and the problems of response lag, resource waste, content redundancy and the like in a traditional material acquisition scheme are solved.

The invention relates to the field of video generation, in particular to a new media video automatic generation method and system based on artificial intelligence. The method comprises the following steps: identifying user input information; performing deep semantic analysis on the user input information, and constructing a time sequence demand curve; performing role behavior analysis according to the time sequence demand curve, and constructing a role behavior data packet; performing visual expression demand analysis according to user input information, and constructing a multi-level 3D scene; performing dynamic behavior scene fusion on a multi-level 3D scene by using the role behavior data packet, and outputting a video frame sequence; and performing intelligent compression and dynamic code rate optimization on the video frame sequence, and outputting a finished video. According to the invention, full-process automatic, high-quality and high-efficiency generation of the new media video from content conception to finished product output is realized.

The invention discloses a three-dimensional acoustic visualization rendering method and system based on sound field modeling. The method comprises the following steps: arranging a microphone array to collect a multi-channel time domain audio signal, and carrying out short-time Fourier transform to obtain frequency domain complex sound pressure data; performing inversion based on a beam forming algorithm to obtain complex sound pressure of each voxel point in a three-dimensional space, and constructing a four-dimensional acoustic voxel matrix; further utilizing a volume ray projection algorithm to map the volume element data into color and transparency, and realizing three-dimensional rendering and visual expression of the sound field; the system supports frequency screening, time evolution playback, transparency adjustment and three-dimensional visual angle control, and the visual analysis capability of the sound field is improved; and meanwhile, a structured data output interface is provided and can be linked with an AI algorithm, so that intelligent functions such as acoustic anomaly detection and tuning optimization are realized. The method has the capabilities of high-precision modeling, deep rendering expression and intelligent expansion, and is suitable for various acoustic application scenes such as intelligent sound boxes, vehicle-mounted sound boxes, conference systems and the like.

An emotional intelligence method, system, and apparatus is trained on a multi-modal basis to infer emotional states of users from visual, language-based, and / or tactile-based cues. The inferred emotional states then inform the system's interactions with users, which may take the form of language-based expressions in textual or audio form and / or visual-based expressions in the form of images such as within video and / or in the form of physical contact. The system automatically learns multi-modally from its interactions with users, which may be performed by applying a reinforcement learning process, updates its emotional state inferencing models, and adapts its subsequent interactions with users accordingly.

A display system (10) for a vehicle operable by a user, comprising: input safety critical data (D) indicative of one or more operating parameters of the vehicle; i ) and obtain the input safety important data (D i ) based on the intermediate video frame (VF i a graphics generator (20) configured to generate an intermediate video frame signal representative of said intermediate video frame (VF i ) is the monitoring safety critical data (D m ), the first frame area (40) being a visual representation of the monitoring safety critical data (D m ) encoding markers (43, 62) uniquely associated with said monitoring safety critical data (D m ) and the input safety critical data (D i ) correspond to each other under normal operation of the graphics generator (20) and do not correspond to each other under abnormal operation of the graphics generator (20); a graphics generator (20); a device coupled to the graphics generator (20) for receiving the intermediate video frame signal and encoding the monitoring safety critical data (D) according to the encoding markers (43, 62); m a display control unit (22) coupled to said display control unit (22) and configured to determine said input safety critical data (D i ) and the monitoring safety critical data (D m ) and receives both the input safety-critical data (D i ) and the Monitoring Safety Critical Data (D m ) with each other, and based on said comparison, generate a command signal (S c ) and a display monitoring unit (26) configured to generate the command signal (S c ) is the input safety important data (D i ) and the Monitoring Safety Critical Data (D ma display monitoring unit (26) for indicating correspondence or lack of correspondence with the command signal (S); c ) and the command signal (S c ) and the intermediate video frame (VF i ) based on the input safety critical data (D i ) and the Monitoring Safety Critical Data (D m ) corresponds to the monitoring safety-critical data (D m ) is a visual representation of the verified video frame (VF c a display system (10) configured to generate a verified video frame signal indicative of the

The invention discloses an open vocabulary point supervision time sequence action positioning method based on a progressive optimization network, and belongs to the field of video understanding. Firstly, visual features are preliminarily screened through semantic guidance early enhancement, so that background noise interference is inhibited, and the expression ability of category-related features is improved. And then, semantic association of modeling actions in different time periods is further established by utilizing context-semantic post-enhancement, the category identification degree of visual expression is enhanced, and the model is promoted to mine more unconstrained new category suggestions. And finally, the action boundary is optimized in combination with pseudo-label constraint, fine modeling of the boundary position is realized, and the generalization ability of the model is enhanced while the detection precision is improved. According to the method, a progressive optimization modeling strategy is combined, visual and semantic features are fused to construct a unified progressive optimization network, and the method aims at improving the action positioning performance while reducing mark dependence. The method has a wide application prospect in tasks such as intelligent monitoring, abnormal behavior detection and video question and answer.

A computer-implemented therapy method for training conversation and dialogue interaction skills as well as pragmatic language skills in children with ASD is provided. The method includes: obtaining a robot having a non-humanoid, non-animal-like shape, the robot including at least one processor and memory coupled to the processor for controlling one or more actions of the robot; and configuring the processor to control the robot: (i) to monitor audible and visual expressions of a child with Autism Spectrum Disorder in proximity of the robot; and (ii) to audibly generate sentences pronounced by the robot in order to elicit a verbal response from the child and to trigger a conversation, the sentences being automatically generated as a function of the audible and visual expressions of the child to thereby initiate and maintain a conversation with the child.

The present disclosure provides an intelligent generation method based on layered recognition of painting intention, which comprises: obtaining a painting description text input by a user, and pre-processing the painting description text to extract layered semantic features. A geometric constraint expression model is constructed according to the layered semantic features, and geometric state parameters are generated through the geometric constraint expression model. The state transition stage is determined according to the geometric state parameters, and a spatial state evolution model of Markov chain is constructed based on the state transition stage. The optimal geometric state is determined through the spatial state evolution model, and a layered generation model driven by spatial state constraint is constructed according to the optimal geometric state, so as to generate an initial target image through the layered generation model. The initial target image is subjected to consistency test and optimization, and the optimized target image is output after the test is passed. The present application improves the consistency of the generated image in visual expression and engineering implementation by introducing geometric constraints into the state transition process.

The invention provides a data visualization method for stream detection, a medium and a system, and belongs to the technical field of data visualization for stream detection.The method comprises the steps that firstly, the length of a data stream collection time slice is formulated, a cache queue is established, and multi-dimensional data streams are collected from the queue and subjected to feature extraction; performing parallel computing processing on the multi-dimensional feature data, dividing the multi-dimensional feature data into a plurality of data blocks, and performing parallel dimension reduction by using a graphics processor; constructing a visual mapping rule for the feature data after dimension reduction, establishing a rendering buffer area, and performing batch processing by adopting a resource allocation equation set; establishing a data updating queue in the memory partition and performing real-time dimension reduction processing; calculating visual expression accuracy based on the feature data after dimension reduction and optimizing a visual mapping rule; and finally, the rendering parameters are updated by adopting the optimized rule, and real-time visual rendering of the data stream is completed in the graphics processor, so that the problem that massive streaming data are difficult to process in real time and are difficult to display visually in the prior art is solved.

A system and method for enhancing the visual expression of a visual object in a seamless and vivid manner, the visual object having a different overlay visual image therewith, comprising means for providing information about the position and movement of each movable part of the object; image acquisition means for acquiring images and videos of the object; processing means for calculating the three-dimensional distance and position of the movable parts and the object; image processing means for generating an overlay image at the location of the object; means for displaying the overlay image. The system itself is housed in a smartphone-based virtual reality headset.

This disclosure relates to techniques for generating and utilizing custom stickers in a digital communication environment. A technique involves receiving a text-based message input during a chat session and using a generative language model (e.g., a Large Language Model, or LLM) to create a text prompt. This prompt is then used by a generative image model to produce a custom sticker. The generated sticker is sent to a client device where it is displayed in a sticker tray alongside other selectable stickers. Users can select and send these stickers directly within their chat interface, enriching communication with visually expressive and contextually relevant imagery.

The invention relates to the technical field of electrical digital data processing, and discloses an art teaching material cloud space resource management system based on AI, which comprises the following steps of: converting original art materials into parameterized seed data containing vector contours, color primitives and gray-scale guide maps through a material potential conversion module, and associating a lightweight rendering rule set; the instant response engine calls a rendering rule set based on the interaction parameters to carry out graphic operation on the seed data so as to generate a visual image in real time; according to the system and the method, paradigm conversion of art teaching materials from static storage to dynamic response is realized, a single basic material can derive diversified visual expressions in real time according to teaching requirements, meanwhile, data stability under non-ideal acquisition conditions is ensured through a gradient compensation mechanism, and the system and the method are suitable for popularization and application. And flexible and reliable digital support is provided for heuristic teaching.

The present invention belongs to the field of data identification technology, and discloses a conversion optimization processing method, system, device and medium for a large passenger station model. The processing method includes: in UE4, using a development resource replacement program to obtain the ID code in the component name, and searching the corresponding ID row in the data table, obtaining the spatial data of the row, calculating the relationship with the spatial data of the shared resource component, and changing the spatial parameters of the component instance object to realize the conversion of multiple component instance objects into instance objects of shared resources; rotating the instance objects of shared resources at an angle to be consistent with the orientation of the original component. The present invention converts a one-to-one resource instantiation component into a one-to-many instantiation component, and programmatically sets the LOD of shared resources in batches, thereby maximizing the optimization of resource occupancy and optimizing the efficiency of the development program; and solving the visual expression of referenced objects through the UV setting of shared resources, thereby improving the efficiency of system development.

The present invention discloses an AI intelligent graphic and text contextual content precise layout full marketing generation method, which specifically relates to the field of graphic and text recognition technology; performs semantic analysis on the text input by the user, extracts the main image items, reverse semantics, auxiliary emotional items and tonality keywords, and constructs a multi-semantic field group; injects the field groups into a collaborative generation engine composed of an image generation sub-model and a semantic prediction sub-model, and the semantic prediction sub-model predicts the graphic attribute labels to guide the image generation sub-model to perform regional attention intervention; after the image is generated, the degree of matching between the image content and the field group structure is evaluated through a structural-level semantic consistency judgment mechanism, and regeneration is triggered if there is inconsistency; finally, the structurally aligned image content is output and combined with the original text for graphic and text layout to generate graphic and text contextual content that meets the requirements of multi-platform marketing applications; the present invention significantly improves semantic accuracy, structural consistency and visual expression quality while ensuring generation efficiency.

During a process called live design, a computing system may receive, from a repository, an instance of a first component comprising a first set of one or more metaobjects that provides a binary representation of the instance of the first component. In turn, the computing system may render the instance of the first component as an icon and a first set of one or more underlying panes that provide a visual expression of the instance of the first component. The computing system may then receive, via the first set of one or more underlying panes, a user modification to the instance of the first component. Thereafter, the computing device and / or the repository may determine whether the user modification to the instance of the first component is valid, and may process the user modification in accordance with the determining.

Disclosed is a system and associated methods for generating an autonomous bot that replicates speech characteristics, visual expressions, and actions of a professional in order to further relationships established by the professional in meetings that the professional is unavailable for. The system monitors meetings involving the professional at different stages of a workflow, and classifies the workflow stage associated with each meeting. The system models content, speech characteristics, and visual expressions expressed by the professional at each workflow stage based on commonality that is detected in a different set of meetings classified to a corresponding workflow stage. The modeling is used to generate an autonomous bot as a surrogate for the professional in a meeting that the professional is unavailable for. The autonomous bot interacts with other meeting participants by replicating the content, speech characteristics, and visual expressions of the professional throughout the meeting based on the modeling.

This invention discloses a dynamic simulation method for the flowing light effect in a wind farm digital twin system, relating to the technical field of wind farm simulation. The method includes: collecting the operational sequence state data of wind farm equipment in the wind farm digital twin system and constructing a time-series dynamic rate vector; calculating the dynamic activity index of each wind farm device; constructing multiple visual state modules corresponding to multiple dynamic activity intervals, with each visual state module including a set of independent flowing light effect processing parameter mapping rules; performing visual parameter simulation on each wind farm device and outputting the flowing light effect simulation results. This method solves the technical problem in existing technologies where there is a lack of layered processing capability for the visual representation of wind farm equipment with different dynamic activity levels, resulting in insufficient visual differentiation and low information recognition between high-activity and low-activity devices. It achieves the technical effect of improving the visual expression hierarchy and dynamic response sensitivity of equipment status information in the wind farm digital twin system.

The invention discloses a temperature control method and system configured with multi-gear sensible temperature marks. The core innovation of the method comprises the steps that (1) a refrigeration / heating mode key is canceled, gear configuration is flexible, dynamic setting of 5-7 gears is supported, and manufacturers can select the number of the gears and define the names of the gears in a personalized mode; (2) diversified visual expressions directly associated with the sensible temperature of people: snowflake and sun icons support multi-dimensional design of size, quantity and color, and a half-snowflake and half-sun pattern is innovatively adopted for a comfortable grade; and (3) full-scene adaptation: automatically resetting in a hotel mode, and carrying out personalized setting on gear icons in a school mode. Visualization and individuation of temperature setting are achieved, the method is suitable for an air conditioner panel, intelligent home equipment and a mobile terminal application program, the operability and comfortable use experience of a user in using the air conditioner are improved, energy conservation and carbon reduction of the air conditioner are facilitated, and technical support is provided for digitization and virtualization of the space environment.

This invention discloses a live streaming content compliance risk control method and system based on screening rules, relating to the field of streaming media content risk control technology. The proposed solution includes acquiring a real-time live stream, performing temporal slicing on the live stream, and performing visual object recognition and visual expression recognition on the video frames in the current slice to obtain object feature fragments, expression feature fragments, and their temporal position information. This application changes the existing approach of treating subsequent information as merely supplementary information by first associating and clustering object feature fragments and expression feature fragments appearing in stages across time units into matching fragment groups, and then concatenating them according to temporal position information to form a risk chain to be closed. This solves the technical defect that risk information cannot be closed and identified for a long time when it appears in stages across time units, and achieves continuous closed tracking of the same live streaming display chain, thereby reducing continuous missed judgments due to insufficient evidence in a single time unit.

The invention relates to a multi-mode user emotion recognition method, device and equipment and a medium, the method is applied to sound equipment, and the method comprises the steps that physiological data, voice data and image data of a target user are acquired; extracting physiological features from the physiological data; extracting voice features and semantic features from the voice data; extracting facial features from the image data; and determining the emotion of the target user according to the physiological features, the voice features, the semantic features and the facial features. Therefore, according to the technical scheme of the invention, the accurate judgment of the emotion of the target user is realized by integrating the four types of modal data of the physiological features, the voice features, the semantic features and the facial features. The four types of features respectively map the emotional state of the user from four dimensions of physiological reaction, acoustic expression, semantic connotation and visual expression to form a multi-dimensional complementary emotion recognition system. The mechanism can recommend appropriate music content to the user, the auditory demands of the user under different emotions are met, and the use experience of the user is remarkably improved.

The invention relates to the technical field of rendering optimization, in particular to a C + + rendering method and system for city-level 3D Gaussian splashing, and the method comprises the following steps: obtaining a building boundary and a height grid, calculating an included angle between a building and a visual angle, superposing a height difference and a shielding rate to obtain an interference graph, screening a sphere with a low fusion value, generating a visual unit table, and judging an idle level through a mapping thread. And ranking the rendering sequence, and generating a rendering parameter set by combining a terrain gradient set radius. The visual interference degree of each area is accurately evaluated, three factors of shielding, delay and cache failure are subjected to normalization fusion evaluation, redundant sphere units influencing the visual effect and performance are effectively filtered, a spatial index position is matched according to the thread idle capability level in the rendering thread scheduling process, the thread utilization efficiency is improved, and the rendering thread scheduling efficiency is improved. The Gaussian sphere radius is adjusted through the contour line gradient, the visual expression consistency of different terrain complexity areas in the scene is enhanced, and dynamic optimization rendering distribution of Gaussian splashing in the city-level three-dimensional scene is achieved.

This invention relates to the field of human-computer interaction and interface optimization, and discloses a method for optimizing the visual hierarchy of an interface based on eye tracking. The method includes: acquiring a set of interface elements of the interface to be optimized, and constructing a target visual hierarchy map based on a preset interaction task flow, the functional type of each interface element, and its information priority; collecting eye tracking data during the user's execution of a preset interaction task, the eye tracking data including first fixation time, cumulative fixation duration, number of regressions, and saccade shift relationships; determining the perception priority parameters of each interface element based on the eye tracking data, and constructing an actual perception hierarchy map; comparing the actual perception hierarchy map with the target visual hierarchy map to identify hierarchy deviation element groups and their corresponding deviation types; and calling the corresponding visual expression parameter reconstruction rules according to the deviation type to locally reconstruct the hierarchy deviation element groups while maintaining the preset interface structure constraints.

The present specification relates to the technical field of image processing, and particularly relates to a UI stylization method and device based on extended reality, the method comprising: acquiring a scene in a user's field of view and a UI element to be stylized; generating a stylization description instruction for the UI element to be stylized according to the scene and the UI element to be stylized, the stylization description instruction being used to integrate the UI element to be stylized into a visual expression of an extended reality scene; determining each single target UI element in the stylization description instruction according to the stylization description instruction; and rearranging each single target UI element to generate a stylized UI component. According to the present scheme, the visual performance of the UI to be stylized is adjusted in real time according to the specific style of the XR scene, without interrupting the user's experience in the immersive scene. Through machine learning and deep learning technology, the model is trained to recognize and adapt to different scene styles, so that the UI can be naturally integrated into the user's immersive environment.

The present invention relates to the technical field of electronic digital data processing, and discloses an AI-based cloud space resource management system for art teaching materials, comprising: converting original art materials into parameterized seed data containing vector outlines, color primitives and grayscale guide maps through a material potential conversion module, and associating a lightweight rendering rule set; an instant response engine calls the rendering rule set based on interactive parameters to perform graphics operations on the seed data to generate visual images in real time; and a teaching interactive interface provides interactive parameter input controls. The present invention realizes a paradigm shift from static storage to dynamic response of art teaching materials, enabling a single basic material to derive diversified visual expressions in real time according to teaching needs. At the same time, a gradient compensation mechanism is used to ensure data stability under non-ideal acquisition conditions, providing flexible and reliable digital support for heuristic teaching.

The application discloses a picture-text marketing content generation method and system based on a multi-modal model, and is applied to the technical field of multi-modal models; sample effectiveness screening is performed according to a time offset value between a feedback occurrence time of historical interaction feedback data and a picture-text content display time, sample data with picture-text corresponding relationships, entry attribution relationships and feedback time sequence relationships are generated; correlation weights between image visual expressions, text semantic expressions and feedback behavior expressions are extracted to obtain embedded features, picture-text generation constraint vectors are generated, and picture-text marketing content is generated based on the picture-text generation constraint vectors, which helps to solve the problem that, when picture-text marketing content is generated for a specific traffic entry or a target user group, there is insufficient correlation representation among image visual expression emphasis, text marketing semantic emphasis and traffic feedback characteristics in the multi-modal generation process, so that the generated content is insufficient in adaptability to click interest and conversion intention.