72 results about "Human interaction" patented technology

The present invention facilitates communication between sign language users and machines by translating sign language and text using AI models, deep learning computer vision, and word embeddings. Users interact via sign language, captured and processed through deep learning and NLP modules. The system converts sign language videos into text, constructs coherent sentences, and generates contextually appropriate responses using a Retrieve and Generate (RAG) model. Responses are translated back into sign language videos, spelling out words not found in the dictionary. If requested, a human agent can respond. Key features include high-accuracy recognition, context-aware response generation, dynamic vocabulary updates, and optional human interaction. The method ensures efficient processing with LLM, embedding techniques, and deep learning, optimizing translation accuracy and user experience. The system adapts to multiple languages and dialects by training on specific sign languages, making it applicable globally.

The invention relates to the technical field of computer vision, and discloses a figure interaction detection method based on spatial fine-grained context interaction feature fusion, which comprises the following steps of: firstly, performing target detection on an input image to obtain a target detection result set and a person-object pairing feature; performing gridding projection on the image to obtain image global features, and inputting the image global features into a spatial fine-grained feature learning module to obtain spatial fine-grained features; inputting the spatial fine-grained features and the human-object pairing features into a spatial context interaction feature fusion module to obtain spatial context interaction features, and inputting the spatial context interaction features and the spatial fine-grained features into a visual encoder to obtain enhanced human-object pairing features; obtaining an interaction category score according to the feature and a text embedding feature of a character interaction category; and iteratively optimizing the character interaction detection model until convergence. According to the method, the description of local details of a visual space is enhanced, the context relationship between a person and an object is enhanced, and the accuracy of person interaction detection is improved.

The invention provides a virtual human interaction action generation method for unmarked augmented reality equipment, and the method comprises the steps: obtaining a head posture, a hand posture and a first-person visual angle image sequence of a user through a built-in sensor of an augmented reality helmet, and jointly reconstructing a whole-body posture of the user on the basis; generating an interaction action of a virtual human according to the reconstructed user posture; according to the method, the interactive action of the virtual human can be more natural and real and is kept consistent with the actual behavior of the user; in the field of man-machine interaction, the prior art depends on user control and needs additional hardware equipment and manual participation to maintain an interaction process; or depending on predefined conditions, generalization and practicability are poor; compared with the prior art, additional manual intervention and predefined design are not needed, interaction with the natural response virtual human can be achieved only through the lightweight augmented reality helmet, hardware dependence and labor cost are reduced, automation and usability of the method are promoted, and interaction convenience and immersion are improved.

Machines, devices, and other objects are configured to use authorization tokens to verify object identities without human input. In examples, the object uses a password to validate the object's identity to an authorization server to obtain an access token for use in multiple applications. In another example, the object uses a certificate to validate the object's identity to an authorization server to obtain an access token. In other examples, any other suitable identifying data may be used to validate the object's identity to an authorization server to obtain an access token. The process of using passwords, certificates, or other validation processes to obtain tokens or other authorization mechanisms allows the object to authenticate themselves without human interaction and to use a single identity to access services from multiple service providers that trust a central authorization server.

The invention relates to a social subject memory simulation system and method based on a large language model, and belongs to the technical field of computers. According to the method, online and offline multi-source information fusion is realized, and behavior and situation characteristics of social subjects can be comprehensively described; a large language model semantic comprehension capability is introduced, so that the intelligent level of memory retrieval and information fusion is improved; dynamic dump and index retrieval of long-term memory are supported, so that subjects can keep semantic coherence and behavior consistency in multiple rounds of interaction; the authenticity of information spreading and interaction between social subjects is enhanced, and technical support is provided for an intelligent social system, virtual human interaction and social simulation.

1. The name of the design product: service type single-arm robot. 2. The use of the design product: used as a service type single-arm robot, used for personal care, health physiotherapy, rehabilitation assistance, or related services in the context of human interaction in commercial service scenarios. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective view 1.

This application provides a video annotation method, electronic device, and storage medium. The method includes: acquiring the original video and user-annotated information for the first frame of the original video; generating an initial contour mask based on the SAM3 model and the first frame and its annotation information; determining whether the number of frames in the original video exceeds a preset frame count threshold; if so, dividing the original video into multiple sub-videos; performing temporal propagation annotation on each sub-video sequentially based on the initial contour mask to obtain the initial contour mask for each frame in the original video; and generating the annotation result of the original video based on the original video and the initial contour masks for each frame in the original video. This application generates the initial contour mask based on the SAM3 model, requiring only minimal human interaction to automatically locate the target and identify its state, significantly reducing the workload of manual frame-by-frame annotation and lowering labor costs.

The disclosure provides systems / methods of predicting future actions from a video. The disclosed systems and methods can use a video of human interactions with an object as input to predict future human actions. The disclosed systems and methods jointly detect the gaze of the human in the video and the action (or human-object interactions (HOI)) of the human in the video to predict a future gaze. The detected gaze and action, as well as the predicted future gaze, can be used to predict future actions (or HOIs) of the human in the video.

The present application relates to a kind of high-efficiency adaptive picture character interaction detection method and system.The system contains two kinds of operating modes: training-free mode: system utilizes pre-trained target detector and multimodal model, constructs the concept guide of multi-branch character interaction memory module, to simultaneously store specific domain visual knowledge and universal domain semantic knowledge, complete character interaction detection;Fine-tuning mode: utilize lightweight adapter based on attention mechanism, for the visual encoder in model is incorporated into instance-level priori knowledge, while updating the knowledge stored in character interaction memory module, obtain better character coding features.The model under training-free in the present application can complete character interaction detection task and obtain competitive performance in the case of only a small amount of samples, the model under fine-tuning mode can obtain more spatially sensitive pair relationship features, so that character interaction relationship detection is more accurate.

A computer-implemented system facilitates controlled social interactions in public venues without exposing users outside those venues. A server receives location signals from user devices, confirms presence within a venue geofence using stored boundary data and short-range checks, and issues venue-bound session tokens. The server computes a venue “vibe” profile by fusing audio features, occupancy estimates, and explicit user feedback, and returns the profile to devices. Messaging between devices is authorized only while both present valid tokens; authorization is revoked and venue-scoped identifiers and message metadata are purged when a device leaves or a token expires. Optional features include Live-Peak time-gated live view with credit-based extensions, administrative boundary refinement, and tokenized payments to venue merchants upon acceptance of offers. The system supports interactions beyond dating, including friendship, group coordination, and professional networking.

Human interaction with products and services can be difficult to measure or quantify. As an example solution, a computer-implemented method is provided. The method includes receiving human perception data in response to an external stimulus over a period of time. The human perception data includes a plurality of time periods. The method further includes determining an emotional response based on the human perception data. The method further includes assigning a numerical value to the emotional response. The method further includes calculating a change in the emotional response over the plurality of time periods over the period of time.

AI has been evolving to be able to learn various information regarding an individual and to better express the personality and features of the individual. In addition, attempts have been made to make use of such AI to facilitate human-to-human communication. The present invention solves the problem of there being no effective method for making use of AI for smooth communication and human-to-human interaction.　A "personalized AI" is made to speak as a proxy for an individual. By proceeding with speaking, a conversational flow is created. The AI is useful for smooth communication and human-to-human interaction because the individual sees and hears the conversational flow and can trade off with the AI in the middle of the conversation or newly join the conversation as a guest, whereby the conversation can be structured more easily than when constructing a conversation from the beginning.

A system includes a mobile unit with one or more sensors and a mechanical arm, and a stationary unit that includes a first customizable identifier. The one or more sensors are configured to detect a first customizable identifier of the first stationary unit. The one or more sensors collect location data corresponding to the first customizable identifier of the first stationary unit. The mobile unit is configured to align the mechanical arm of the mobile unit with the first stationary unit, based at least in part on the location data corresponding to the first customizable identifier of the first stationary unit.

The application belongs to the technical field of human-computer interaction, and discloses a kind of based on explainable machine learning human-computer interaction method, system, medium and equipment, the predicted psychological help question and answer are based on ChatGPT, and the psychological health question and answer human consultant and ChatGPT are compared and analyzed based on average; The key language clues of the perceived helpfulness of the psychological health question and answer are determined, and the influence of the key language clues on the perceived helpfulness; The prompt strategy for ChatGPT is designed, and the performance of ChatGPT in the psychological health question and answer is improved through targeted prompting.The answer of ChatGPT to the real psychological health problem has language similarity with the high-quality answer provided by the human consultant; how to design and optimize the prompt engineering to improve the performance of ChatGPT in the psychological health question and answer, and whether the targeted prompt engineering can improve the response quality of ChatGPT.

The invention discloses a virtual human interaction method and device based on dynamic strategy adjustment, and the method comprises the steps: collecting multi-modal input data of a user, extracting an emotion tone index, and recognizing an interaction intention; querying according to the interaction intention and optimizing a communication strategy in combination with a scene knowledge base to obtain an optimization strategy framework; candidate responses are generated based on the optimization strategy framework, and the matching degree of the candidate responses and the user state is evaluated to determine final output; and when the matching degree is lower than a preset threshold value, switching to a standby interaction mode to generate a response. According to the method, the user intention is accurately recognized through multi-modal fusion analysis, the scene knowledge base is combined to dynamically optimize the strategy, and a closed-loop evaluation and correction mechanism is established, so that the adaptability, intelligence and pertinence of virtual human interaction are remarkably improved, and the user experience is improved.

This application provides a method, apparatus, and electronic device for generating training data based on psychological process modeling. The method includes: acquiring a set of target text segments; inputting the set of target text segments into a trained binary classification model to obtain a classification result for each text segment in the set; selecting at least one target text segment from the set whose classification result indicates it contains cognitive linkage information; inputting the at least one target text segment into a trained sequence labeling model to obtain at least one linkage data group corresponding to each target text segment; inputting the at least one linkage data group and preset constraint rule information into a trained causal language model to obtain psychological link information corresponding to each linkage data group; and constructing training data based on each linkage data group and its corresponding psychological link information. This solution enables explicit modeling of the psychological motivations behind human interaction behavior, improving the quality of training data.

1. Name of the product in this design: Ground Interactive Motion All-in-One Machine. 2. Purpose of this design: It is used for ground projection human interaction, mainly for people to interact with the projected image by stepping on it. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: a 3D model.

Differentiating between human interaction and computer interaction using a natural perception of human eyes to identify human users. One or more images may be displayed within one or more test fields on a web page. The one or more images themselves, or a duration for which they are presented, may cause a human eye to not see something that is in the images or to see something that is not in the images. Input may be received from the user identifying all images that are perceived by the user. A determination may be made that the user is a human user based on what the user identifies. Access to another web page may be granted to users who are determined to be human and denied to users that are not determined to be human.

The application discloses a dynamic cover generation method and device and electronic equipment. Frame extraction is performed on a target video to obtain a video picture set; human body key point detection is performed on each frame of video picture in the video picture set; for each frame of video picture in the video picture set, a picture score of the video picture is determined based on a key point detection result of the video picture; a plurality of candidate picture sets are constructed based on the video picture set, a comprehensive score of each candidate picture set is determined, and a first number of target picture sets are selected from the plurality of candidate picture sets at least according to a principle of high priority of the comprehensive score; and a dynamic cover of the target video is generated based on the first number of target picture sets. The technical scheme disclosed by the application automatically generates a dynamic cover for a target video without human participation, has high efficiency, consumes very short time, does not miss wonderful segments, and the generated dynamic cover contains more human interaction pictures, which is conducive to attracting the attention of users.

The application discloses a kind of human-vehicle interaction communication systems based on vehicle network security, including data acquisition module, communication module, security module, central control unit and display and interactive terminal.The system ensures the communication security in the process of human-vehicle interaction by data encryption, decryption and security protocol management.The system uses artificial intelligence algorithm to optimize interaction logic, supports multiple communication modes, has touch screen and voice recognition function, and improves the safety and user experience of human-vehicle interaction.

A computer-implemented method is disclosed for detecting advertisement fraud in real-time using a multi-modal analysis framework. The method involves receiving user data and user action data from a media device, including demographic information and sensor-based interaction metrics such as accelerometer, gyroscope, and touch sensor data. These inputs are processed by an advertisement fraud detection system equipped with a processor and hardware-run algorithms, including a multi-modal machine learning model that distinguishes human from non-human interactions. Fraudulent actions are identified by detecting deviations from predefined behavioral baselines enriched with campaign-level intelligence. The system further analyzes historical ad performance to identify downtime periods characterized by low human activity and high fraud probability. During these periods, fake advertisements are adaptively inserted based on contextual mismatches to confirm fraudulent behavior. Upon detection, notifications are dispatched to advertisers via multiple communication mediums.

1. The name of the design product: desktop multifunctional self-service terminal. 2. The use of the design product: multifunctional self-service terminal for human interaction. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective view 1.

The application belongs to the technical field of image processing, and provides a single image three-dimensional figure interaction generation method based on multi-modal deep learning, comprising: performing instance detection and segmentation processing on a single image to be processed to obtain two-dimensional region information; performing figure interaction reasoning by using a multi-modal large language model according to the single image to be processed and the two-dimensional region information, and generating a conditional vector through encoding; determining figure two-dimensional image features according to the two-dimensional region information, and constructing three-dimensional geometry and spatial relationship based on the figure two-dimensional image features and the conditional vector to obtain three-dimensional human body grid and object point cloud data; and obtaining three-dimensional figure interaction results through three-dimensional space optimization and interaction probability distribution prediction according to the three-dimensional human body grid, the object point cloud data and the conditional vector. The scheme realizes integrated modeling of semantic conditions and three-dimensional geometry under single image input, and the final output three-dimensional figure interaction results have good three-dimensional consistency.

A medical infusion fluid handling system, such as an automated peritoneal dialysis system, may be arranged to de-cap and connect one or more lines (such as solution lines) with one or more spikes or other connection ports on a fluid handling cassette. This feature may reduce a likelihood of contamination since no human interaction is required to de-cap and connect the one or more lines and the one or more spikes. For example, the automated peritoneal dialysis system may include a carriage arranged to receive the one or more lines each having a connector end and a cap. The carriage may move along a first direction so as to move the connector ends of the one or more lines along the first direction, and a cap stripper may be arranged to engage with the caps on the one or more lines on the carriage. The cap stripper may move in a second direction transverse to the first direction, as well as to move with the carriage along the first direction.

Apparatus and methods to verify human interaction through an encrypted channel are provided. A human verification program may create an encrypted channel between two or more devices when a communication between users of the devices is started. Data may be transferred over the encrypted channel when a user performs a verifiably human action. The data may be analyzed to determine whether the user is more likely than not a bot. The channel may be collapsed when a pre-determined condition is satisfied.

The application discloses a kind of restaurant scene under the identification method and safety monitoring system of character interactive behavior, belong to video analysis technical field, the method includes: determine each video monitoring collection area picture, data pre-processing etc.;Establish restaurant staff face and human target, customer human body, restaurant common article label library;Establish the label library of the body related action behavior of interaction with restaurant common article and the interaction between people, judge the safety / unsafe of its behavior and establish label;Build double-task double-flow parallel learning network, extract the feature information of target identification and the feature information of character interactive action behavior;Process the feature information extracted by fusion model network, build a network model for restaurant customer safety monitoring and employee service work content understanding, and judge whether there is unsafe employee and customer behavior, establish a kind of intelligent monitoring system, and have certain help effect to the automation level of video intelligent monitoring system.

This invention provides a virtual human intelligent interaction system and method based on a large-scale model workflow. The interaction system includes: a virtual human interaction module, used to convert collected user interaction information into query requests; and to generate response content based on standard format requests received from an interface interface module, and present it to the user; an interface interface module, used to convert query requests received from the virtual human interaction module into proprietary format requests specific to the workflow tool module; and to convert processing results returned by the workflow tool module into standard format requests required by the virtual human interaction module; and a workflow tool module, used to process the proprietary format requests received from the interface interface module to obtain processing results. This invention solves the problems in existing technologies such as the disconnect between workflow tools and virtual human technology, the limited interaction methods, and the weak data processing and management capabilities caused by the over-reliance of virtual humans on language models.

A modular autonomous robotic device assembly for transporting shipped items is described. The assembly includes a modular mobility base having propulsion, steering, sensors for collision avoidance, and suspension actuators; a modular auxiliary power module having a power source and a cargo door; a modular cargo storage system having a foldable structural wall and a latching system; and a modular mobile autonomous module covering the cargo storage system and providing a human interaction interface, external sensors, a wireless interface, and an autonomous controller having interface circuitry coupled to the human interaction interface and sensors of the mobile autonomous module. The assembly has a power and data transport bus providing a communication and power conduit across the different modular components. A method for assembling such a robotic device on demand is further described, having steps for authenticating the different modular components during assembly.

A medical infusion fluid handling system, such as an automated peritoneal dialysis system, may be arranged to de-cap and connect one or more lines (such as solution lines) with one or more spikes or other connection ports on a fluid handling cassette. This feature may reduce a likelihood of contamination since no human interaction is required to de-cap and connect the one or more lines and the one or more spikes. For example, the automated peritoneal dialysis system may include a carriage arranged to receive the one or more lines each having a connector end and a cap. The carriage may move along a first direction so as to move the connector ends of the one or more lines along the first direction, and a cap stripper may be arranged to engage with the caps on the solution lines on the carriage. The cap stripper may move in a second direction transverse to the first direction, as well as to move with the carriage along the first direction.

The invention belongs to the technical field of man-machine interaction in artificial intelligence, and particularly relates to a man-machine interaction degree evaluation method based on bidirectional information value, which comprises the following steps: calculating the man-machine interaction degree of a single man to a machine; calculating the man-machine interaction degree of a single machine to a person; calculating man-machine interaction degree parameters; and calculating and outputting the total human-computer interaction degree, and evaluating the efficiency and effect of human-computer interaction. According to the method, the problems of incomplete man-machine interaction degree calculation and lack of objective quantitative standards in existing unmanned aerial vehicle autonomy evaluation are solved. A two-way information value concept is introduced for the first time, and an interaction scene is fully covered; subjective expert experience is quantified through an analytic hierarchy process, and evaluation objectivity is improved; and in combination with time dynamics and content effectiveness, the model engineering applicability is enhanced. The accuracy and credibility of unmanned aerial vehicle autonomy evaluation can be remarkably improved, and a scientific basis is provided for command decision making.