48 results about "Video Library" patented technology

The invention provides an interactive digital human presentation method based on a backplane video and a related device, and relates to the technical field of artificial intelligence such as human-computer interaction, digital human, end-cloud integration and large models. The method comprises the following steps: extracting a real-time inquiry from a real-time interaction request initiated by a user for a digital human offline video in a playing state, and sending the real-time inquiry and historical interaction content to a cloud server; the cloud server is controlled to generate reply voice according to the real-time inquiry and historical interaction content and select a target digital person bottom plate video matched with the reply voice from a digital person bottom plate video library, and different digital person bottom plate videos correspond to digital persons showing different actions respectively; controlling the cloud server to generate a digital person online video for answering the real-time inquiry according to the target digital person bottom plate video and the reply voice; and linking and playing the digital human online video stream-pushed by the cloud server in the digital human offline video in the playing state in a manner of inserting the waiting transition video.

The invention discloses a video-based omni-directional remote rehabilitation training system, a video-based omni-directional remote rehabilitation training method and a medium, which are characterized in that a digital standardized training video library classified according to four stages of PT physical therapy is established, and more than 700 digital standardized training videos such as joint activity, balance training, gait correction and the like are covered; it is ensured that the training content is scientific and covers the whole period and all directions of rehabilitation training; rehabilitators generate personalized training schemes in combination with rehabilitation scene types (hospitalization / home / community / old-age care institutions) and clinical data and in combination with remote video evaluation of the rehabilitators, and training requirements in different environments are met. By capturing actions of limb joint angles, joint point motion trails and muscle force changes, a training action deviation rate is calculated and is fed back and output to a rehabilitation teacher in a grading manner, so that the training standardability is remarkably improved; rehabilitators can manage multiple patients online at the same time, remotely check training percentage data, adjust schemes and generate rehabilitation notes, and efficient, accurate and personalized rehabilitation guidance services are provided for the patients.

The application discloses a video search method and device and a computer readable storage medium. The method comprises the following steps: obtaining a video search text, and performing text feature extraction on the video search text to obtain first text features; mapping the first text features to a video feature space corresponding to video information to obtain second text features; performing video feature extraction on each candidate video in a candidate video library to obtain first video features of each candidate video; mapping the first video features to a text feature space corresponding to text information to obtain second video features of each candidate video; and searching for a target candidate video corresponding to the video search text in the candidate video library based on a first similarity relationship between the first text features and the second video features and a second similarity relationship between the first video features and the second text features. The method can greatly improve the accuracy of searching for videos based on text.

The invention discloses a video retrieval method and device, electronic equipment and a storage medium, and belongs to the technical field of retrieval. The method comprises the steps of obtaining at least one type of query statement feature based on a target query statement; for each candidate video in the video library, obtaining a dynamic visual feature and at least one type of static visual feature of the candidate video; the number of the dynamic visual features is at least one; on the basis of at least one type of query statement feature, the dynamic visual feature and at least one type of static visual feature, obtaining a comprehensive similarity score of a candidate video; and based on the comprehensive similarity score of each candidate video, determining a retrieval result of the target query statement. According to the video retrieval method disclosed by the invention, the problem that the accuracy of a video retrieval result is not high is solved.

The application discloses a video retrieval method and device, electronic equipment and storage medium, and belongs to the technical field of retrieval. The method comprises the following steps: acquiring at least one type of query sentence feature based on a target query sentence; acquiring at least one type of visual feature, a first subtitle feature and a second subtitle feature of each candidate video in a video library; the first subtitle feature is an overall subtitle feature of the candidate video, the second subtitle feature is a subtitle feature of each frame in the candidate video, and the number of the second subtitle feature is at least 1; acquiring a comprehensive similarity score of the candidate video based on the query sentence feature, the visual feature, the first subtitle feature and the second subtitle feature; and determining a retrieval result of the target query sentence based on the comprehensive similarity score of each candidate video. The video retrieval method disclosed by the application solves the problem that the accuracy of the video retrieval result is not high.

The present invention relates to the technical field of digital humans. Disclosed is a large-model-driven method for real-time interaction with a digital human, comprising the following steps: S1, inputting a question text by means of a human-machine dialog frontend and sending the question text to a large model backend; S2, the large model backend performing large model inference on the basis of the question text and a knowledge base to generate an answer summary and a full answer and respectively sending the answer summary and the full answer to a digital human backend and the human-machine dialog frontend for display; S3, a classifier generating a plurality of classification labels on the basis of the answer summary, and the digital human backend performing retrieval and matching on a preset video library on the basis of the classification labels to obtain a target preset video and sending the target preset video to the human-machine dialog frontend; and S4, a digital human processing engine generating a digital human summary video on the basis of the answer summary and pushing the digital human summary video to a player, and the player sequentially playing the target preset video and the digital human summary video. Smoother experience of real-time question-and-answer interaction with a digital human is finally achieved, thereby reducing loss of realism in the experience.

The invention provides a street view and satellite image matching method and equipment. The method comprises the following steps: acquiring a street view image, a satellite image and an unmanned aerial vehicle video library; extracting a first visual feature of the satellite image and a second visual feature of the unmanned aerial vehicle video key frame; calculating a first similarity score between the satellite image and the unmanned aerial vehicle video key frame by using the first visual feature and the second visual feature; performing visual feature comparison and semantic description association on the streetscape image and the unmanned aerial vehicle video key frame, and calculating a second similarity score between the streetscape image and the unmanned aerial vehicle video; and based on the first similarity score and the second similarity score, bridging calculation is carried out by using the unmanned aerial vehicle video as transfer to obtain an indirect matching score of the streetscape image and the satellite image, and a cross-view matching result is obtained in combination with the direct visual feature matching score. Based on the method, the invention also provides a street view and satellite image matching device. According to the method, the accuracy and practicability of cross-view image retrieval are remarkably improved.

This application discloses a video generation method, apparatus, electronic device, and medium, belonging to the field of artificial intelligence technology. The video generation method includes: extracting behavioral descriptive words and visual descriptive words from a first text; determining target video segments matching the behavioral descriptive words from N first videos, and determining target video frames matching the visual descriptive words from the N first videos; generating a target video based on the target video segments and the target video frames; wherein the N first videos are N videos in a video library similar to the first text; and N is an integer greater than 1.

The application discloses a kind of family audio-video imprint automatic aggregation and personal biography film generation method and system based on genealogy figure. First, structured family knowledge base including family member node, blood relationship edge and associated multimedia data is constructed. In response to biography generation request, start multi-modal figure imprint aggregation: fusion face recognition and blood relationship auxiliary matching, automatically identify and extract all image fragments of target figure appearance from audio-video library, form cross-modal material set. Further, blood narrative guided intelligent editing is carried out: based on age estimation, material time sequence segmentation is carried out, narrative structure is automatically generated in combination with blood event node, and material enhancement technology is used to output into film. The system automatically generates the "family imprint" column in personal data card, and aggregates and displays related audio-video materials. Through integrated path, scattered family memories are gathered into personal image biography, which greatly reduces the production threshold, realizes the automatic aggregation and generation of family memories.

The application discloses a kind of based on man-machine cooperation's mass video complex target retrieval method.Currently, the generalization ability of intelligent system based on machine vision is weak, when environment changes, target exists shielding or presents camouflage state, still need a lot of manpower intervention in mass video retrieval target, time-consuming and laborious.The application first according to the coarse-grained feature of target uses retrieval model in video library and carries out pre-screening, and the target candidate set obtained by screening is made into brain-eye cooperation RSVP paradigm and presented to subject.Subject determines target, and its specific features are input into retrieval model, so as to realize the fast positioning and tracking of target in mass video.The application combines the generalization reasoning ability of human and the rapid retrieval ability of machine, can effectively improve the efficiency and accuracy of video investigation, has strong scientific significance and social significance.

The invention discloses a video retrieval method based on video-text dual alignment and an ETVA model, and the method comprises the steps: constructing and training the ETVA model, capturing local text features and global text features described by a text input by a user, retrieving a video matched with the global text feature description from a massive video library based on the global text features, and carrying out video retrieval based on the video-text dual alignment. And retrieving a video matched with the local text feature description from the videos matched with the global text feature description based on the local text feature. According to the method, the global features and the fine-grained features are extracted from the video and the text through the ETVA model, and accurate alignment is carried out. By means of the double alignment mode, the model can deeply mine and capture more complex semantic association between the video and the text, interaction between local representation of the video and local representation of the text is enhanced, the model can more accurately understand video content and text description, and then the accuracy and efficiency of video retrieval are remarkably improved.

The invention discloses a construction method of a driver drowsiness detection data set and related equipment, and relates to the technical field of image processing, and the method comprises the steps: responding to a data set construction instruction, extracting continuous multi-frame driver driving images from a driver drowsiness video library, carrying out the automatic pre-labeling of the driver driving images through a preset multi-mode large model, and obtaining a pre-labeled driver driving image; the method comprises the steps of obtaining a pre-annotation result, sending the pre-annotation result to an annotation inspection device for verifying and correcting the pre-annotation result to obtain a target annotation result meeting annotation requirements, and constructing a data set meeting a YOLO model training format based on the target annotation result and a driver driving image, the data set being used for training a YOLO model. The YOLO model is used for real-time driver drowsiness detection. According to the method, based on the synergistic effect between large model pre-annotation and manual verification, the workload of workers is reduced, the accuracy of the annotation result is also improved, and then the driver drowsiness detection data set is efficiently and accurately constructed.

The invention relates to a video recommendation method and device and application thereof. The method comprises the steps that historical behavior information of a user is acquired, the historical behavior information comprises a first image-text label vector corresponding to at least one historical video and a corresponding behavior duration, and the first image-text label vector is used for generating the corresponding historical video; each first image-text tag vector is matched with a video library index, second image-text tag vectors corresponding to the multiple candidate videos are obtained, and the second image-text tag vectors are used for generating the corresponding candidate videos; and screening the candidate videos based on historical behavior information of the user and each second image-text label vector, and obtaining at least one target recommended video for the user to request on demand. According to the scheme provided by the invention, construction and updating of the video library index and recall screening in video recommendation can be realized based on the image-text vector tag generated by the driving video, more accurate watching suggestions are provided for the user, and the user experience is improved.

The invention provides an intelligent rehabilitation training scheme generation system and method and a medium. The intelligent rehabilitation training scheme generation system comprises a digital training video library module, an intelligent evaluation module, a scheme customization module, a training data acquisition module, a multi-source data fusion module, a scheme optimization module, a risk control module and a decision support module. Compared with the prior art, the method has the advantages that the adaptive training video is automatically associated through the multi-dimensional label structured video library in combination with the user capability baseline report generated by intelligent evaluation, so that the individualized scientificity and precision of the scheme are improved; through multi-source data fusion modeling, collected training data are fused, a user digital model is constructed, and real-time accurate deviation correction of actions is achieved; based on real-time feedback of multi-source data fusion, a training scheme is intelligently adjusted, historical training data is analyzed, and a recommended video training scheme is predicted; rehabilitymen can manage multiple patients at the same time, remotely and efficiently adjust schemes, view data parameters and generate rehabilitation reports, and efficient, accurate and personalized rehabilitation services are provided for the patients.

The present application relates to the technical field of vehicle video data analysis, and discloses a vehicle video data analysis method based on traffic responsibility definition. The method first builds a video library containing various traffic scene videos, and each video has an event sequence diagram. Then, the same scene event sequence diagrams are merged into a comprehensive sequence diagram. Next, the responsibility requirements and analysis requirements of the accident are obtained, and the comprehensive sequence diagram is selected and the basic sequence diagram is extracted according to the requirements, and the part to be identified is labeled. Then, a responsibility judgment model is constructed, and after the complete sequence diagram is obtained by analyzing the part to be identified, the key frame nodes are checked, and the nodes with a dispute probability greater than a critical threshold are defined as dispute nodes and a label reminder is generated. In addition, when the video library is built, the video is collected and preprocessed, and the key frame nodes are extracted by the optical flow method or the convolutional neural network model. The method can improve the efficiency and accuracy of traffic responsibility definition.

The application discloses a video synthesis method of a camera device, the camera device and a storage medium. The method comprises the following steps: collecting a recording video stream in the process of collecting a monitoring video stream for video monitoring; the video parameter of the recording video stream is lower than the video parameter of the monitoring video stream; extracting a target video frame containing a target object in the recording video stream to obtain a video library for editing; synthesizing at least part of the target video frame into a target video based on the video library; and sending the target video to a user terminal. In the foregoing manner, the camera device can complete the synthesis of the video, the problem of excessive processing pressure and playing lag caused by the user terminal for video synthesis can be reduced, and the probability of playing lag can be reduced.

The application discloses an automatic data simulation tool and method based on a linear regression model, comprising a simulation video library module, a data conversion module, an instruction management module and a data playback module, wherein the simulation video library module, the data conversion module and the instruction management module are all associated with the data playback module, the simulation video library module comprises a video file unit and a configuration file unit; the data conversion module is a core module of the system, and comprises a data filtering unit, a data conversion unit and a data rewriting unit; the data filtering unit is used for filtering data in a parsed Log file according to an instruction before simulation starts, and target data is obtained through linear regression model conversion; and data used in the simulation process is measured by equipment in an actual road test scene, and the data has reliability, accuracy and effectiveness, and a reproduced scene is equivalent to the actual road test scene.

The application discloses a video recommendation method. The method comprises the following steps: determining whether a user likes a target video according to behavior data of the user in the process of watching the target video; if the user likes the target video, searching for a video group having a logical correlation relationship with the target video from a video library; when a video recommendation instruction is received, acquiring a preference feature vector of the user, a description feature vector of each to-be-recommended video in the video library, and a logical weighting value of all first to-be-recommended videos except the target video in the video group; calculating a preference degree of the user to each to-be-recommended video according to the preference feature vector, the description feature vector of each to-be-recommended video, the logical weighting value, and a preset matching degree algorithm; and selecting to-be-recommended videos meeting a preset condition according to all the calculated preference degrees to form a recommendation list and recommend the recommendation list to the user. The application can improve user experience.

The invention aims to disclose an offline rehabilitation training system based on remote interaction, which comprises a rehabilitation training terminal and a remote interaction terminal, and the rehabilitation training terminal and the remote interaction terminal are connected with each other in a wireless communication mode; the rehabilitation training terminal establishes a digital standardized training video library through a digital standardized training video library unit, so as to ensure that the training content is scientific and covers the whole period and all directions of rehabilitation training; an intelligent evaluation unit and a training scheme generation unit are combined with rehabilitation scene types and clinical data evaluation to generate personalized training schemes, and training requirements in different environments are met; actions of limb joint angles, joint point motion trails and muscle force changes are captured through the training monitoring unit, the training action deviation rate is calculated and fed back in a graded mode, and the training standardability is remarkably improved; a rehabilitation teacher can simultaneously manage multiple patients online through the remote interaction terminal, remotely check training percentage data, adjust a scheme and generate a rehabilitation report, and the purpose of the invention is achieved.

The application provides a rendering method and device for virtual human interactive video, and the method comprises the following steps: obtaining a voice to be broadcast; selecting limb action data matched with the voice to be broadcast in a limb action video library as target limb action data; the target limb action data comprises a limb action video pre-rendered based on a virtual human limb action, lip position information and lip posture information of the limb action video; rendering a lip video according to the lip posture information and the voice to be broadcast; and fusing the lip video and the limb action video based on the lip position information to obtain a virtual human interactive video for outputting the voice to be broadcast. According to the scheme, only the lip video needs to be rendered in real time, the lip video and the pre-rendered limb action video can be combined into a completed virtual human interactive video, and the calculation amount required for rendering the virtual human interactive video in real time is significantly reduced.

The invention provides a video content retrieval method and device.The method comprises the steps that all video streams in a video library are traversed, a first frame sequence of the video streams is obtained based on a first frame rate, and if the pixel difference value between adjacent video frames in the first frame sequence is larger than a first threshold value, the video streams are retrieved; if yes, determining a video clip corresponding to the adjacent video frame as a candidate clip, and obtaining a key frame in the candidate clip based on a second frame rate; determining each granularity video corresponding to the video stream, and determining structured data corresponding to each granularity video according to a pre-trained processing model; and matching the user retrieval information with the structured data corresponding to each granularity video of each video stream in the video library, and determining target video content according to a matching result. According to the method provided by the invention, the accuracy of video retrieval can be improved.

The application discloses a kind of image extraction model construction, image query and video generation method, device, the method includes obtaining all video frame images in video library;Each of all video frame images is carried out encoding processing, and first video frame image encoding sample set is obtained;Each of all video frame images is carried out data enhancement processing, and the image after enhancement is encoded to obtain second video frame image encoding sample set;First video frame image encoding sample set, second video frame image encoding sample set are input into pre-trained image extraction model and are trained, so that image extraction model can accurately extract the feature of video frame, improve the accuracy of video frame image matching.

The present disclosure provides a video search method and device, electronic equipment and storage medium, relates to the technical field of artificial intelligence, in particular to the technical field of natural language processing, computer vision, intelligent search and deep learning. The specific implementation scheme is as follows: determining a search sentence to be processed and a corresponding word segmentation annotation result, wherein the word segmentation annotation result includes at least one word in the search sentence and a corresponding annotation type; determining a sentence dependency tree of the search sentence according to the at least one word and the corresponding annotation type; querying a video library according to the sentence dependency tree to obtain a target video in the video library that matches the sentence dependency tree; and generating a video search result of the search sentence according to the target video, thereby determining a video matching the search sentence through comparison of the dependency trees, avoiding manual annotation of the title of the video, reducing cost, and improving accuracy.

The invention relates to the technical field of hospital intelligent science popularization, in particular to a science popularization content propaganda and education method and system based on intelligent interaction, and the method comprises the steps: constructing an image-text propaganda and education content library and a rehabilitation training video library which cover multiple departments, multiple disease categories and multiple stages, and carrying out the structural processing and labeling modeling of the content, time mapping and node sorting are executed based on the hospitalization cycle of the patient, and a daily personalized propaganda and education task is automatically generated. Furthermore, a propaganda and education plan is executed through the robot, the robot is controlled to go to a ward according to the bed sequence, the identity of the patient is verified through visual recognition and voice confirmation, matched image-text propaganda and education, voice explanation and training videos are automatically played, and the manual propaganda and education workload is effectively reduced. Training actions of the patient are collected through camera equipment, whether action execution is standard or not is judged in real time, training feedback data are generated, standardized supervision of rehabilitation actions is achieved, and the risk that the rehabilitation progress is affected due to improper training is reduced.

The application relates to the technical field of natural language understanding, and particularly discloses a text processing method and related devices. The method comprises the following steps: obtaining a target comment of a target video; the target comment is a comment published by a user on the target video; a word to be corrected in the target comment is detected; the word to be corrected is a word with a low likelihood in the target comment; the likelihood of the word to be corrected is obtained by inputting the word to be corrected into a language model; the language model is trained based on information of a candidate video; and the candidate video comprises a video in a video library that is highly similar to the target video. The method can automatically identify and correct errors in the comment of the current short video by comprehensively utilizing the current short video content and the overall comment, the other multi-source video content and the comment data that are similar to the current short video, thereby improving the identification rate of errors in the comment and the accuracy of correction, and improving the identification and correction efficiency.

The application discloses a video deduplication method and system based on key frame weighted feature fusion and a medium, and relates to the technical field of video content processing. The method comprises the following steps: acquiring a to-be-processed video and performing shot segmentation, and selecting representative key frames in each shot segment; generating a main body core according to the representative key frames and forming a disturbance envelope band outward, identifying a non-main body interference area and determining an interference intrusion state; screening main judgment key frames, extracting local texture features, semantic content features and effective picture global features, and performing weighted fusion to generate video-level candidate recall features; recalling candidate videos, establishing shot matching edges and shot closed chains, and outputting video deduplication results. By distinguishing between main body content and peripheral interference content, combining shot sequence continuous verification, and adopting candidate recall and closed chain verification for processing, the identification accuracy of repeated videos and near-repeated videos is improved, and the screening efficiency and judgment accuracy in a large-scale video library are taken into account.

The embodiment of the invention discloses a video recommendation method and device, electronic equipment and a medium, and relates to the technical field of computers, and one specific implementation mode of the method comprises the steps of obtaining user video watching data in a first preset time period; based on user watching data of a first video in the user video watching data, determining whether the video type of the first video is a hot video; when the video type of the first video is a hot video, sampling and pairing processing is carried out on a watching user set in the user watching data to obtain a watching user pair, and a similarity score between the first video and the second video is determined based on a watching video set of the watching user pair; and based on the similarity score, obtaining candidate recommended videos from a video library, and generating video recommendation information by using the candidate recommended videos. The efficient landing of the recall algorithm under the scene of millions of users and millions of video candidate sets is realized, and the real-time performance and reliability of video recommendation are improved.

The invention provides a resource scheduling method for real-time interactive digital humans and a related device, and relates to the technical field of artificial intelligence such as human-computer interaction, digital humans, end-cloud integration and large models. The method comprises the following steps: receiving real-time interaction requests initiated by different users through different digital human live broadcast room entrances; and for each real-time interaction request, matching and allocating a corresponding backplane video resource from a pre-generated digital human backplane video library to form different digital human backplane videos in the digital human backplane video library to respectively correspond to the digital human showing different actions, the backplane video resources allocated to the at least two different real-time interaction requests are multiplexed from the same digital human backplane video; a corresponding digital human response video is generated based on the backplane video resource allocated for each real-time interaction request. According to the method, the calculation overhead and the resource consumption for independently generating the basic video material for the real-time interaction request initiated by each user are remarkably reduced through cross-request multiplexing of the bottom plate video resources.

The invention provides a digital human generation and interaction method and device and a medium, and relates to the technical field of digital humans, and the method comprises the steps: constructing a universal digital human image and a reference action video library matched with the universal digital human image; generating a personalized action video library corresponding to the target digital human image based on the target digital human image provided by the user and the reference action video segment; responding to voice wake-up information sent by a user, and generating corresponding reply text and reply voice; generating a plurality of reply action video segments based on the reply voice and the personalized action video library; the reply voice, the reply action video segment and the reply text are subjected to time sequence alignment, then the reply text is bound to serve as subtitles, and a synchronous digital human interaction video with real-time synchronization of the voice, the action and the subtitles is obtained; the problems that traditional personalized digital human customization is large in difficulty and high in cost are solved by means of universal action resources, and in the digital human interaction stage, the sense of reality, fluency and real-time response capacity of digital human interaction are remarkably enhanced.

The present disclosure provides a video material generation method and device, electronic equipment and storage medium, and relates to the technical field of video processing. The specific implementation scheme is: performing video quality filtering processing on all original videos collected by users in a video library to obtain a plurality of original videos; grouping the plurality of original videos based on a theme and a picture size to obtain a plurality of video groups; and generating a plurality of video materials corresponding to each video group based on a preset video material generation strategy and each video group. The present disclosure can effectively improve the quality of video materials and further improve the quality of video generation.