93 results about "Video eeg" patented technology

The embodiment of the invention provides a video clustering method and device and a storage medium. The method comprises the steps of obtaining all to-be-classified videos of any user from a video library; adopting a preset feature extraction model for each to-be-classified video in all the to-be-classified videos to extract features used for judging the context relationship between the videos; judging whether any two to-be-classified videos have a context relationship or not according to the features of each to-be-classified video and a preset video context judgment model; and clustering and sorting the to-be-classified videos with the context relationship to obtain at least one video group. The to-be-classified videos with the context relation are automatically clustered and sorted based on the preset model, operations such as labeling, classifying and sorting of the to-be-classified videos by a user are not needed, the clustering and sorting efficiency of the to-be-classified videos is improved, the cost is reduced, and the user experience is improved. And clustering and sorting of the to-be-classified videos provide convenience for video viewers to continuously watch the videos, and the video watching experience is improved.

The invention provides a model training method and device, a video recommendation method and device, equipment and a storage medium, and relates to the field of artificial intelligence, in particular to the fields of deep learning, data processing, recommendation algorithms and the like. The model training method comprises the following steps: acquiring a training sample comprising user features of a sample user, video features of historically watched videos of the sample user and reference playing durations corresponding to the historically watched videos; extracting historical sequence features according to the user features and the video features to obtain a first feature vector; performing feature importance learning based on the first feature vector to obtain a second feature vector; the second feature vector is input into a tree-shaped playing time length full-connection network for progressive playing time length learning, the predicted playing time length corresponding to the historically watched video is obtained, and the tree-shaped playing time length full-connection network is obtained by adopting a tree-shaped structure to conduct modeling on the playing time length; and adjusting parameters of the playing time length prediction model based on the predicted playing time length and the reference playing time length.

The invention provides a subtitle processing method and device. In a scene in which the electronic equipment plays the video, scene parameters of the scene are obtained, and the scene parameters comprise at least one of personalized data of a user watching the video, equipment data of the electronic equipment and content data of content in the video. And according to the parameter combination acquisition model, acquiring a parameter combination of the subtitles suitable for the scene parameters, the parameter combination comprising at least one of the following: the subtitle style, the position of the subtitles in the video playing interface and the continuous display duration of the subtitles. And displaying the subtitles to be displayed on the video playing interface based on the parameter combination. According to the method and the device, the requirement of a user on the personalized watching effect of the subtitles can be met, the personalized watching habits and experience preferences of the user on the subtitles can be met, the method and the device can adapt to the specification of a screen of hardware equipment of a currently played video, and better and more personalized subtitle watching experience is provided for the user.

Provides is a method for detecting a complex target in pedestrian re-identification video streams based on an event-related potential (ERP). According to the method, video streams of a complex target in different scenarios are collected, and are made into experimental paradigms, and electroencephalogram (EEG) data of a subject during watching of a video content is collected. Then brain electrical activity mapping (BEAM) is analyzed, and ERP features are marked, including P300 and P300-D, which correspond to target emergence and target disappearance respectively. Positive and negative sample pairs are constructed, and essential features between classes are obtained based on a method of contrastive representation learning and a method of spatial-temporal feature attention extraction, so as to solve the extreme class imbalance problem of samples and the problem of how to distinguish between two similar classes in a video paradigm.

Technology is disclosed for programmatically generating interactive content cards (ICCs) for enhancing digital video content. In one implementation, an ICC overlays video content without altering the underlying video, providing viewers with additional, contextually relevant information as the video is viewed. The ICCs may be dynamically presented based on predefined presentation criteria, such as temporal markers, detected events, or recognized objects within the video that correspond to the information in the cards. Upon detecting a viewer's interaction with an ICC, a content window providing supplemental information about the video is presented. The supplemental information is generated using a query to a knowledge base, which may include a search engine or a language model, ensuring that the information is current and relevant.

The application discloses an ADHD multi-feature extraction and fusion classification method based on original videos, and comprises the following steps: S1, a network camera is used to collect video records of a subject watching videos, the videos are preprocessed, and preprocessed image frames are obtained; S2, the preprocessed image frames are analyzed to obtain behavior modes including facial actions, eye movements and head movements; S3, feature components of the behavior modes are extracted and fused; and S4, a deep learning network is constructed to classify the fused features. The application further discloses an ADHD multi-feature extraction and fusion classification system based on original videos. The application classifies ADHD patients based on video sequences, avoids invasive influence, reduces cost and is easy to popularize. Through multi-modal feature fusion, the limitation of single modal data is reduced, better accuracy and effectiveness are achieved, and in addition, the application can also be used for classifying autism cases.

1. The name of the design product: the graphical user interface of the electronic device for inviting people to watch video. 2. The use of the design product: the design product is used for electronic device. 3. The design points of the design product: the graphical user interface in the electronic device is requested to protect the part, wherein the gray single color block is the video content picture. 4. The picture or photo that can best show the design points: the front view. 5. The electronic device is the usual design, and the rear view, the left view, the right view, the top view and the bottom view are omitted. 6. The use of the graphical user interface: the design product is used for inviting nearby people to watch video together in watching video. 7. The human-computer interaction mode of the graphical user interface: clicking the first icon from the left in the upper right corner of the front view can enter the interface change state figure 1 to search for nearby people to watch video, after waiting for the search to end in the interface change state figure 1, the interface change state figure 2 can be entered, and in the interface change state figure 2, selecting "+" on the right side of any person to watch video can enter the interface change state figure 3.

The invention discloses a video recommendation method and device based on multi-modal feature recognition, a storage medium and computer equipment. The method comprises the following steps: collecting and analyzing facial images and physiological signal data of a user respectively collected by a camera device and intelligent monitoring equipment when a target user browses a video on a video platform, and recording watching information of the user at the same time; extracting facial features, physiological features and viewing features from the collected data; emotion recognition is carried out in combination with the multi-modal features, and emotion information of the user on the video is determined; and determining emotional preferences of the user according to an emotional recognition result, and recommending personalized video contents to the user based on the preferences. Through multi-modal feature recognition, the scheme can more comprehensively capture emotional changes and interest points of the user in the video watching process, so that the preferences and preferences of the user are more accurately judged, and the recommendation accuracy is improved.

The application discloses a kind of based on data-driven digital person high-quality video generation method and system, it is related to data analysis technical field, including: obtaining historical digital person video, and current target video, extract the feature video in digital person video;Obtain the viewing user of viewing feature video, obtain target user according to the interactive behavior and viewing duration between viewing user and feature video;The behavior of target user is analyzed when watching feature video, and the audience user corresponding to target video is extracted;According to the adjustment record of the parameter value of the interactive parameter in the video changed by audience user, the early warning degree of target video is calculated, and intelligent prompt is carried out.The application obtains the audience user of digital person video by feature video and adjustment record, and the actual characteristics of audience user are intelligently analyzed, effectively generate high-quality, strong attractive video content, improve the viewing experience and satisfaction of user group watching video.

This invention discloses a method for studying visual attention mechanisms based on EEG microstates, comprising: collecting EEG signals from subjects while watching videos and preprocessing them; extracting saliency maps from the videos, and extracting statistical features from the perspectives of spatial saliency information in the local temporal domain and spatiotemporal saliency information changes in the global time series, respectively, to obtain sIQR features and tsIQR features; converting the preprocessed EEG signals into EEG topology map sequences and performing spatial clustering to extract EEG microstate templates, determining the number of templates and selecting the final microstate templates, and then backfitting them to the EEG signals to obtain microstate sequences; extracting microstate features and depth features from the microstate sequences, examining the statistical differences between microstate features and sIQR and tsIQR features, constructing decoding models based on microstate features or depth features, and using the decoding models to decode segments and videos respectively to obtain segment labels and video labels.

Embodiments of the present disclosure provide a video clustering method, a device, and a storage medium. The method comprises: obtaining all videos to be classified of any user from a video library; for each video to be classified among all of the videos to be classified, using a preset feature extraction model to extract a feature for determining an inter-video context relationship; on the basis of the feature of each video to be classified and a preset video context discrimination model, determining whether a context relationship exists between any two videos to be classified; and clustering and sorting videos to be classified having a context relationship, to obtain at least one video group. According to the embodiments of the present disclosure, clustering and sorting videos to be classified having a context relationship are automatically implemented on the basis of a preset model, without requiring a user to perform operations such as manually annotating labels for, classifying, or sorting the videos to be classified, so that the clustering and sorting efficiency of the videos to be classified is increased and the costs are reduced. In addition, the clustering and sorting of the videos to be classified provide convenience for video viewers to watch videos continuously, so that the video watching experience is improved.

The embodiments of the present disclosure relate to a push processing method and apparatus, and a device and a medium. The method comprises: if candidate push objects associated with the current live broadcast video include a second push object, which matches a first push object, displaying push information in a live broadcast interface of the current live broadcast video, wherein the push information is used for prompting that the current live broadcast video includes the second push object associated with the first push object, and the first push object is determined according to historical viewed videos; and if the push information meets a preset trigger condition, displaying, in the live broadcast interface, a push page for the second push object.

Embodiments of the present disclosure provide a video-based interaction method, apparatus, device, and storage medium. The method includes: displaying a plurality of user identifiers for identifying associated users on a video playback page of a target video having a plurality of associated users; in response to a trigger operation on a target user identifier among the plurality of user identifiers, displaying a predetermined panel on the video playback page, and displaying predetermined media content information of a target associated user corresponding to the target user identifier in a first display area within the predetermined panel. As can be seen, embodiments of the present disclosure can display predetermined media content information of an associated user of a target video on the video playback page of the target video, enabling a user watching the video to quickly know the associated users of the target video, thus enriching the video-based interaction function and improving the user experience.

The invention relates to a video restoration method and device based on bullet screen feedback, equipment and a medium, and the method comprises the steps: collecting bullet screen data in a video playing process, and recognizing feedback data used for feeding back a video quality problem from the bullet screen data, the feedback data comprising a bullet screen text and bullet screen time; determining a problem type and a problem severity degree of a video quality problem according to the bullet screen text, and determining a problem region of the video quality problem according to the bullet screen text and the bullet screen time; and determining a repair strategy according to the question type and the question severity, and performing video repair on the question region according to the repair strategy. Through a bullet screen semantic recognition mechanism, subjective feedback information of a user on image quality in a video watching process is converted into quantifiable quality problem description, information mapping from subjective perception to objective restoration is realized, and the problem that faults exist between subjective quality feedback of the user and an objective video restoration technology during video restoration is solved.

The invention discloses a digital human live broadcast attention assessment system based on multi-modal physiological feature fusion, and the system comprises a multi-modal physiological feature fusion model construction module which is used for constructing a deep learning model based on a Transform architecture based on a historical digital human live broadcast video and electroencephalogram data and eye movement data when a user watches the video; the digital human live broadcast audience attention evaluation module is used for inputting a digital human live broadcast video into the multi-modal physiological feature fusion model, outputting the attention distribution change when audiences watch the video in real time, and evaluating the attention overlapping degree and focusing degree of the audiences according to the attention distribution change; and the visual angle of the virtual camera is adjusted to optimize digital human live broadcast. According to the digital human live broadcast attention assessment system based on multi-modal physiological feature fusion, the attention of digital human live broadcast audiences is accurately assessed, the live broadcast content is dynamically optimized, the user experience and the live broadcast effect are remarkably improved, and wide application of the digital human technology is promoted.

The present invention relates to a method for screening mobile terminal visual attention abnormalities in children based on multimodal data learning. A calibration video and a testing video are set up, and a head-face video of children while watching the calibration video and the testing video on smartphones is recorded, respectively. An eye-tracking estimation model is constructed to predict the fixation point location from the head-face video corresponding to the testing video frame by frame and to extract the eye-tracking features. Facial expression features and head posture features are extracted. A Long Short-Term Memory (LSTM) network is used to fuse different modal features and realize the mapping from multimodal features to category labels. In the testing stage, the head-face video of children to be classified while watching the videos on smartphones is recorded, and the features are extracted and input into the post-training model to determine whether they are abnormal.

The invention relates to a language learning system, which comprises a learning system, a video player and a foreign language video material, and is characterized in that the output end of the learning system is electrically connected with the video player, and the foreign language video material is in data connection with the learning system and the video player through a data memory. By adopting the translation algorithm module and the subtitle display module, an English learning program is highly simplified, English learning becomes closer to a native language learning process, information of a foreign language video material is decomposed, extracted, translated and combined, a learner can comprehensively and accurately learn the foreign language video material, and meanwhile, the learning efficiency is improved. The translated subtitle information is transmitted to the video player in real time to be displayed, so that a learner can view the translated subtitle information while watching the video, and the learning efficiency and effect are improved.

The embodiment of the invention discloses a video playing method, a video generating method and related devices, and the video playing method comprises the steps: responding to an interaction participation operation triggered for a target video, and playing the target video comprising interaction elements; the target video is a video recorded by a video production user based on an interactive video template, the interactive video template is used for indicating a display style of an interactive element in the video and a trigger action corresponding to the interactive element, and the interactive element is a virtual element configured with an erasable event; in the process of playing the target video, in response to an effective elimination operation triggered for the interactive element displayed in the target video, displaying an elimination effect corresponding to the interactive element; the effective elimination operation means that the touch position of the playing interface of the target video is located in an elimination area corresponding to the interactive element. According to the method, a strong sense of participation can be generated in the video watching process of the user, and the video watching experience of the user is improved.

The invention discloses an electroencephalogram signal enhanced intelligent video abstraction method and system, relates to the technical field of video content understanding and electroencephalogram emotion analysis, and aims to solve the technical problems that in the prior art, video abstraction cannot reflect subjective emotion experience of viewers, electroencephalogram and video time axes are difficult to align, and heterogeneous data are difficult to fuse. Acquiring an electroencephalogram signal of a viewer in a video watching process, synchronizing the electroencephalogram signal with a video clip, and extracting and generating a structured video abstract based on multi-modal content; frequency domain features, time domain features, time frequency features and spatial correlation features are obtained according to the electroencephalogram signals, and electroencephalogram feature visual representation is generated; and fusing the video content abstract, the video key event timestamp and the electroencephalogram feature visual representation, deducing the emotional state and aligning the emotional state with the video event, and outputting a personalized video abstract reflecting the real emotional experience of a viewer. The method can be used for application scenes such as intelligent video abstraction, video platform recommendation, immersive content understanding and emotion calculation.

The utility model discloses a fire safety four-ability training demonstration device, which relates to the technical field of fire training and comprises a mounting plate, a transverse moving assembly, a display screen, a controller and a plurality of sensors, the transverse moving assembly and the controller are arranged on the back of the mounting plate, the display screen is detachably arranged on the transverse moving assembly, and the sensors are arranged on the display screen. The multiple sensors are arranged on the back face of the mounting plate at intervals and located on one side of the transverse moving assembly, and the transverse moving assembly, the display screen and the multiple sensors are all electrically connected with the controller. According to the utility model, the display screen is driven by the transverse moving assembly to carry out segmented fixed-point demonstration on four capabilities of fire safety, basic contents of the four capabilities of fire safety are briefly displayed in a video mode, the form is novel, the eyeballs of employees can be attracted, the watching interest is improved, the memory is deepened in the video watching process, and the visual effect is improved. And the mastering degree of four capabilities of fire safety is enhanced.

The invention relates to a digital human interaction method, device and system based on a video stream and electronic equipment. The method comprises the following steps: performing visual feature analysis processing on continuous video frames of a video stream, and determining a target spatial position of a digital human embedded in the video stream; performing time domain feature analysis and / or scene switching detection on the continuous video frames, and determining a target time point of the digital human embedded in the video stream; generating a to-be-embedded digital human based on the action detection result and the scene classification result of the continuous video frames, and embedding the to-be-embedded digital human into the video stream based on the target spatial position and the target time point; acquiring a video frame associated with the user behavior data from the video stream; and based on the user behavior data and the video frame associated with the user behavior data, generating corresponding digital human interaction content and transmitting the digital human interaction content to the digital human embedded in the video stream, and executing an interaction operation by the digital human. According to the invention, real-time interaction between the digital person and the audience can be realized, so that the audience can instantly interact with the digital person while watching the video.

The present invention provides an EEG emotion recognition method based on an attention-based spatiotemporal network, comprising the following steps: S1, obtaining EEG data and label data of a subject watching a video clip; S2, data preprocessing, including downsampling, removing baseline signals, removing eye contact signals and physiological artifacts of blinking, and bandpass filtering to retain EEG signals between 4.0 and 45.0 Hz to divide the data; S3, constructing a spatiotemporal convolutional neural network model based on kernel attention; S4, training the neural network model, adjusting parameters, and obtaining classification results for EEG emotion recognition; S5, using a set evaluation index, taking the SVM model as the baseline, and comparing it with multiple deep neural network models to verify the effectiveness of the kernel attention-based spatiotemporal network model. The present invention has a high recognition accuracy, can enable machines to effectively recognize and understand human emotions, and makes human-computer interaction more user-friendly, and has strong application value in the field of human-computer interaction.

The present invention discloses a human-machine collaborative video summarization method based on pupil size. Based on the theory that there is a close connection between the spontaneous non-verbal reactions of viewers and their real-time attention changes when watching videos, a perception-driven video dataset is made by utilizing the characteristics that the pupillary light response can be used to indicate the more attractive parts in the video and the data is easy to obtain, providing a basis for the video summarization model to learn the real-time and dynamic attention mechanism of viewers. The present invention uses a human-machine collaborative video summarization framework composed of an encoder-decoder module, an attention mechanism module, and a key frame selection module, which can supervisedly learn the relationship between video features and the attention of viewers to the video, and finally obtain an attention-driven video summarization model that can automatically generate a summary according to the original video.

The application discloses a content generation method, device, storage medium and program product. First, in response to a video playing instruction of target video content, a historical viewing breakpoint moment of the target video content is determined, and viewed video content before the historical viewing breakpoint moment in the target video content is determined. Then, semantic information including a plot script and / or a key frame of the viewed video content is extracted. Finally, a plot abstract of the viewed video content is generated according to the semantic information. Thus, the plot abstract of the viewed video content is generated by using the semantic information of the viewed video content before the historical viewing breakpoint moment in the target video content, so that the user can quickly review the historical video content that has been played and viewed according to the plot abstract at a current viewing starting moment, thereby making it easier for the user to connect the plot of a long video, improving the possibility of breakpoint continuation playing of the long video, and finally improving the completion rate of the long video.

The present invention relates to the field of video service technology, and discloses a video billing control system based on blockchain, comprising a regional analysis module, a quality detection module, a user classification module, a billing pricing module, and a data packaging and transmission module, which can instantly obtain regional information, video quality information, and user portrait information of a target user. The regional information can reflect the geographical location of the target user, and the user's video viewing habits will have a certain impact on people around him. Therefore, the regional information can be included in pricing considerations, and the pricing of the region where the video is watched using the video platform related to the present invention can be reduced, thereby increasing customer stickiness; similarly, video quality and user portrait information reflecting the user's video viewing habits can also be included in pricing consideration standards, thereby adjusting the billing of the video, and sending the generated billing details table to a blockchain storage platform by the data packaging and transmission module for storage, thereby ensuring the security of pricing and billing related data.

Vision analysis system for the production of customized multifocal lenses (100), adapted to be used for the design of a multifocal lens (1) tailored to the needs and physical conformation of a wearer (10), characterized in that it comprises: at least an acquisition device (110) adapted to analyze the behavior of a wearer (10) during the viewing of videos and images, also analyzing the reactions of the eyes to the stimuli; at least a digital apparatus (200) adapted to allow programming the inputs to be provided through said acquisition device (110), and for processing the data obtained, and for leading the design of the multifocal lens (1).

To solve a problem of lack of teachers in school education.SOLUTION: A system for providing a teacher alternative service for school education includes: means for creating an education program in a video based on a target of each school from ministry of education text data; means provided with an interactive function for a student to view the video; and means for automatically producing a test based on a set target.SELECTED DRAWING: Figure 1

[Problem] To improve user experience by generating a stronger sense of presence in the appreciation of a video or sound. [Solution] The present invention includes a vibration part 44 capable of generating vibration corresponding to an audio signal. The audio signal has directivity of sound. The vibration part can generate vibration according to the directivity of sound, and the vibration generated in the vibration part is applied to a user A.

1. Name of the product of this design: Main body of a portable display. 2. Purpose of the product of this design: The portable display is mounted on a mounting component worn on the head (for example, a glasses frame) or a handle, etc., for watching videos. The main body is the main part of the portable display. 3. The key design point of this design product lies in the shape of the part shown by the solid line. 4. The picture or photo that best illustrates the design points: Stereoscopic diagram 1. 5. Other circumstances that require explanation: This design is a partial design, and the part requiring protection is represented by a solid line of the article.

The invention provides a subtitle generation method and device, electronic equipment and a storage medium, and relates to the technical field of computers, in particular to the technical fields of artificial intelligence, natural language processing, signal processing, software engineering, interactive design and the like. The specific implementation scheme comprises the steps of determining a target video; segmenting the audio data of the target video to obtain a plurality of target audio clips; according to a concurrent processing mechanism, performing voice recognition on the plurality of target audio segments to obtain a plurality of text segments; wherein the plurality of text segments are in one-to-one correspondence with the plurality of target audio segments; and translating the plurality of text segments to obtain a target subtitle text. By adopting the method and the device, human resources can be saved, and the generation period of the target subtitle text can be shortened, so that the requirement of acquiring subtitles in real time when a user watches a video in real time is met.