948 results about "Live video" patented technology

The invention provides a live broadcast room content identification and intelligent distribution method and system based on multi-modal fusion, and relates to the technical field of machine learning, and the method comprises the steps: collecting video, audio and bullet screen data of a live broadcast room, and carrying out the feature extraction; performing cross-modal interaction, feature alignment and feature reconstruction on the multi-modal features by using the multi-modal feature fusion model to generate cross-modal fusion features; and carrying out content identification based on a pre-trained content classification model to obtain a category label and a time sequence feature. Furthermore, a live broadcast room content portrait and an association network are constructed, and a live broadcast room real-time score is generated and a live broadcast room display weight and a push strategy are dynamically adjusted in combination with user historical watching behavior data and a deep reinforcement learning model. Through multi-modal data fusion and deep reinforcement learning, accurate identification and personalized recommendation of the live broadcast room content are realized, and the user experience and the platform operation efficiency are effectively improved.

The embodiment of the invention provides a live broadcast data processing method and device and a storage medium, and the live broadcast data processing method comprises the steps: determining multi-modal live broadcast data of a target game, carrying out the data analysis of the multi-modal live broadcast data, and obtaining the initial features of a plurality of modals, the multi-modal live broadcast data comprises target game data, a game live broadcast video and live broadcast interaction data associated with the game live broadcast video; performing feature analysis on the initial features of the multiple modes to obtain target features of the multiple modes; performing fragment detection on the target features of the multiple modes by using a fragment detection model to obtain target video fragment parameters; generating a target live video clip corresponding to the target game based on the target video clip parameter and the game live video; the problems that the efficiency of a manual screening mode is low, and the requirements of actual popularization and publicity cannot be met are solved.

The present disclosure generally relates to user interfaces for multi-user communication sessions. In some examples, a device initiates a live stream in a communication session. In some examples, a device transitions between streaming live audio and live video. In some examples, a device enables synchronizing media playback during a live stream. In some examples, a device displays synchronized media playback and plays a reaction from a first participant of the communication session.

Techniques for optimizing a bitrate ladder for live streaming are described herein. A method for optimizing a bitrate ladder for live streaming includes receiving client-side input and an origin-side input during a first interval in a timeslot, the client-side input comprising CDN logs, the origin-side input comprising a quality measure, extracting from the CDN logs frequency of requests for each bitrate in a bitrate ladder in the timeslot and the duration of recent stall events for client video players. During a second interval in the timeslot, an optimized bitrate ladder comprising an optimal set of bitrates (OSB) is selected using an optimization function, the optimization function taking as input quality measures and a coefficient value determined using stall information. The optimized bitrate ladder is sent to the origin server for live encoding follow-on segments.

A mobile software application implementing “live events,” via which a host of the event may sequentially offer one, two, three, four or more items to a plurality of guests in the event (e.g., via auction, via direct purchase, or via a giveaway). The host's device may obtain and transmit a real-time video stream, which is in turn provided to each guest's device in conjunction with real-time information about the item(s) being offered. Particular techniques further assist the host in sequencing two or more items to be offered in the same live event, thereby avoiding delays and cumbersome user interface interactions that might otherwise be involved in initiating the offering of a next item upon concluding an offering of a previous item.

In various examples, a video effect is displayed in a live video stream in response to determining a portion of an audio stream of the live video stream that corresponds to a text segment of a script associated with the video effect. For example, during presentation of the script, the audio stream is obtained to determine if a portion of the audio stream corresponds to the text segment.

A touch screen controlled light emitting pet toy that has a light emitting device equipped to direct a point of light on a surface to provide entertainment to a pet and includes movement about multiple axis and is operated by a touch screen computer based device communicably connected to a controller of the toy. The toy is equipped to receive user input from an application with a touch-screen directly or indirectly via a camera that provides live video data to the application and relays user input to the toy further allowingdikect control and pre-recorded pattern control of the light emitting device through low latency touch screen interactions.

Systems and methods for a media content user interface. A media content provider includes storage for storing and serving video content to subscribers. The media content provider records and or otherwise stores video content from around the world. Subscribers are provided a user interface to the system that includes a channel bar. The channel bar is dynamically scoped responsive to interactions of a viewer with the system. Selectable elements within the channel bar provide direct access to related content regarding video content, such as television series information and cast information. In addition, the channel bar is operable in multiple modes. An EPG mode displays live video for multiple channels simultaneously. Themed modes permit channel bars that display content according to various themes which may be defined by a viewer, the provider, or both.

The invention relates to the technical field of video decoding, in particular to a fast decoding transmission method and system for a video live broadcast image. The method comprises the following steps: acquiring a video live broadcast picture stream; performing image group division on the video live broadcast image flow to generate image group images; analyzing an inter-frame relationship of the picture grouping images, defining priorities of the picture grouping images according to the inter-frame relationship, and generating decoding priority mark data; entropy data fragmentation is carried out on the picture grouping images, and a picture basic entropy slice and a picture increment entropy slice are generated; stage picture transmission is carried out on the picture grouping images based on the picture basic entropy slice and the picture increment entropy slice, and an image streaming preloading strategy is generated; and performing terminal transmission feedback on the picture grouping images by using an image stream type preloading strategy to obtain terminal transmission feedback data. According to the invention, through optimization of video picture grouping, priority scheduling, bandwidth management, decoding acceleration and fault-tolerant reconstruction, the rapid decoding transmission performance of the video live broadcast image is improved.

Techniques are described for performing actions (e.g., streaming video content, such as advertising content) based on visual markers detected within a live video feed being streamed to one or more computing devices. First video content is streamed to the one or more computing devices. A presence of a content item within the first video content is detected at a first point in time during streaming of the first video content. An action associated with the content item is performed at a second point in time in response to detection of the presence of the content item in the first video content.

The invention relates to the technical field of director and picture synthesis methods, in particular to an intelligent director and picture synthesis method of a panoramic live broadcast system, which comprises the following steps: acquiring panoramic video data shot by a panoramic camera; obtaining user feedback data; based on the panoramic video data, generating a shot selection strategy by using a deep reinforcement learning algorithm; detecting a live broadcast key event in real time by using a target detection and tracking algorithm based on the panoramic video data; generating a picture shooting plan sequence according to the shot selection strategy and the live broadcast key event; performing intelligent editing and synthesis on the panoramic video data based on the picture shooting plan sequence; and outputting the synthesized live video. And updating parameters of the deep reinforcement learning algorithm based on the user feedback data, thereby realizing full automation of the program directing process, greatly improving the efficiency, and enabling the system to continuously learn from live broadcast experience through the deep reinforcement learning algorithm and gradually improve the decision-making ability of the system.

A live broadcast method is provided by present disclosure. The method includes obtaining a live broadcast text and generating a live audio based on the live broadcast text, and determining a first live video that is time-aligned with the live audio and obtaining a second live video; playing the second live video in a live broadcast room; pausing the second live video in response that an audience in the live broadcast room asking a question, and playing a first response video that replies to the question; and continuing to play the second live broadcast video in response that all questions from the audience in the live broadcast room have been answered.

Media, methods, and systems are provided for screen sharing. A user may initiate a video recording. A recording preview interface may be displayed for the user to preview the video recording before beginning the recording. The recording preview interface may comprise a live video preview of the user and of a window or application being shared. When the user selects a window or application for previewing that may cause an infinity mirror effect to occur, a screenshot of the window or application may be generated. The screenshot may be rendered over the live video preview of the window or application to obscure the infinity mirror effect. When the user initiates recording, the screenshot may be removed to expose the live video. The screenshot may be cached and retrieved if the user navigates away and then returns to the preview of the window or application causing the infinity mirror effect.

Disclosed are methods, systems, and computer-readable medium to perform operations including: receiving a plurality of three-dimensional (3D) models of a plurality of assembly parts of a physical object; displaying, on a display device and over a live video of the plurality of assembly parts, an augmented reality (AR) overlay including the plurality 3D models; providing the plurality 3D models to a remote device for display on the remote device; receiving, from the remote device, data indicative of instructions for assembling the plurality of assembly parts into the physical object; and modifying, based on the received data, the AR overlay displayed on the display device to provide the instructions for assembling the plurality of assembly parts into the physical object.

The invention relates to the technical field of live broadcast behavior monitoring, in particular to a live broadcast behavior tracking system based on deep learning, which obtains high-quality multi-source information and improves the accuracy of feature analysis by synchronously extracting image and audio data from a live broadcast video stream and combining frame extraction, image enhancement and voice recognition. According to the method, image features are extracted through a pre-trained convolutional neural network, audio features are extracted through a deep learning model, voice transliteration texts are fused, the weight of each modal feature is dynamically adjusted based on an attention mechanism, precise recognition of complex scenes and hidden violation behaviors is achieved, and image camouflage and latent language expression risks are effectively coped with. And the illegal type and confidence are output in real time, once suspected illegal behaviors are detected, alarm, interruption or shielding operation is triggered immediately, and related evidences are uploaded to an auditing database. And efficient, accurate and full-process management and control of the live broadcast violation behaviors are realized.

The present disclosure generally relates to user interfaces for multi-user communication sessions. In some examples, a device initiates a live stream in a communication session. In some examples, a device transitions between streaming live audio and live video. In some examples, a device enables synchronizing media playback during a live stream. In some examples, a device displays synchronized media playback and plays a reaction from a first participant of the communication session.

A connected streetlamp has live video feed zooming capabilities, Fifth Generation (5G) cellular wireless functionality, and traffic analytics capabilities using artificial intelligence (AI) and computer vision image recognition functionality built in to the monitoring device operably attached to or otherwise integrated with the streetlamp head. In other embodiments, the monitoring device may be located on or integrated with other parts of the streetlamp, or located on or integrated with a telephone pole, post, fence, building or other structure located alongside or near a street or road. A vehicle traffic monitoring system may include a plurality of multi-access edge computing (MEC) vehicle traffic monitoring devices each integrated in a respective connected streetlamp.

In various examples, a video effect is displayed in a live video stream in response to determining a portion of an audio stream of the live video stream corresponds to a text segment of a script associated with the video effect and detecting performance of a gesture. For example, during presentation of the script, the audio stream is obtained to determine if a portion of the audio stream corresponds to the text segment. In response to the portion of the audio stream corresponding to the text segment, detecting performance of a gestures and causing the video effect to be displayed.

Mixed reality instructional technology is enhanced. Comparison of a guide mixed reality data stream to a candidate mixed reality data stream detects a deviation, e.g., different hand movement, different tool placement, or different sensor telemetry. Experiencing a feedback stream of output that is based on the deviation facilitates device control and helps candidates improve their skills. Some feedback output emphasizes deviation size, e.g., by varying colors, sounds, or haptic output proportionally to the deviation size. Some feedback output renders a translucent or skeletal guide overlaid on a live video of current candidate activity. Some embodiments support searches whose results show, e.g., how a certain expert performed a task differently than the candidate, or examples of a certain task such as widget replacement in the field. Stream optimization, summarization, synchronization, and other stream derivation functionality is provided.

The present invention provides a graphical tool to create custom multimedia workflows. The graphics tool is marketed as Experience Builder (EB). One implementation of EB is implemented as software as a service (SAAS) services featuring software for real-time collaboration on shared documents, data capturing, live video communications to support remote equipment and product repair, replacement, and maintenance services, and IT support services for products, services, and operations. Using EB enables authors to create their own visual instructions for customers and technicians. EB is a no-code workflow creation tool to develop process flows, such as, self-service guides, training guides, service bulletins, warranty process steps, and checklists. Optional generative AI is also available.

The invention discloses an AR glasses blogger live video anti-shake processing method and processing system, and the method specifically comprises the steps: carrying out the calculation based on an original video stream and equipment motion data, and generating a preliminary stable frame sequence; based on the preliminary stable frame sequence, marking a key semantic region as a strong stability demand region, and segmenting a foreground main body and a background region; performing fine stabilization on the strong stability demand area and the foreground main body by applying non-rigid transformation, performing stabilization on the background area by applying rigid transformation and retaining the depth of the scene, and obtaining a frame sequence after partition correction; predicting a future multi-frame equipment motion track based on the frame sequence after partition correction, the equipment motion data and the segmentation information of the foreground main body / background region; and calculating and executing prospective canvas motion compensation in advance based on the future multi-frame equipment motion trail and the segmentation information of the foreground main body / background region. According to the invention, efficient anti-shake processing of the live video of the AR glasses is realized, and the stability of the live picture and the user experience are effectively improved.

The invention discloses an emotion attention method for AI online education, which is applied among student ends, a teacher end and a server, and the server sends a live video stream of the teacher end to each student end for playing. According to the emotion attention method for AI online education, the average understanding degree value is calculated according to the learning expressions of the students, the understanding and attention degree of the students to the current course listening are evaluated, the playing speed of each student terminal is dynamically and intelligently adjusted, personalized learning experience is provided for each student, and therefore the learning efficiency is improved; the reminding information of the overall understanding condition of the students is sent to the teacher end, so that the teacher can better interact with the students and adjust the teaching method and content in time; according to the embodiment of the invention, the student end starting the camera sends the speed regulation state information to all other student ends and the server, the server does not need to carry out message interaction with each student end, the processing pressure of the server can be reduced, and the server adjusts the code stream of the live video stream by calculating each playing proportion.

Embodiments are disclosed for real-time event detection using edge and cloud AI. An event monitoring system can receive live video data from one or more video capture devices at a surveillance location. A first machine learning model identifies a first portion of the live video data as depicting an event. The first portion of the live video data is provided to a second machine learning model. The second machine learning model identifies the first portion of the live video data as depicting the event. An event notification corresponding to the event is then sent to a user device.

The present disclosure generally relates to user interfaces related to sources of video data. User interfaces enable users to configure and interact with the sources of video data, such as for displaying a live video feed and a recorded video from an external source of video data. In some embodiments, a device provides user interfaces for displaying video from a video source and controlling external devices related to the source.

The invention discloses a video playing control method and device, electronic equipment and a computer readable storage medium. The method comprises the steps that real-time network performance parameters of a video playing end are acquired; the average code rate corresponding to the video stream currently played by the video playing end and the average network performance parameter of the video playing end are determined, and the video played by the video playing end corresponds to the video stream with a plurality of code rate gears; based on the average code rate, the real-time network performance parameter and the average network performance parameter, a video stream of a target code rate gear is determined from the video streams of the multiple code rate gears, and the video stream of the target code rate gear is used for adjusting a video stream played by a video playing end. By using the scheme provided by the invention, the live video with the optimal image quality conforming to the network state can be more accurately provided for the user, so that the comprehensive effect of the image quality and the fluency of the video playing end is better, and the watching experience of the user is improved.

The invention provides a video coding method and device, electronic equipment and a storage medium, relates to the technical field of image processing, in particular to the field of video coding and the like, and can be applied to application scenes such as video live broadcast and the like. The specific implementation scheme is as follows: acquiring a reference frame which is adjacent to a current frame and has established initial ROI hierarchical division; multiplexing a motion vector generated by the reference frame in a motion compensation time domain filtering process, and determining an ROI position predicted value of the current frame; extracting feature points of the five sense organs of the current frame, and correcting an ROI position predicted value based on a feature point spatial topological relation in the initial ROI; respectively configuring differential quantization parameters for the corrected main face region, the corrected secondary face region and the corrected background region; dynamically allocating a three-layer area code rate according to a real-time network bandwidth; and outputting the coded frame of the current frame and the associated ROI level metadata. According to the scheme, the coding efficiency and quality can be improved.

The invention discloses an e-commerce live broadcast violation detection method, device and equipment, a medium and a product. The method comprises the steps that real-time live broadcast data is acquired, the real-time live broadcast data is obtained by performing voice recognition on an acquired real-time live broadcast video, and the data type of the real-time live broadcast data is text data; marking the real-time live broadcast data by using a preset model to obtain a corresponding text vector; inputting the text vector corresponding to the real-time live broadcast data into a pre-trained first-stage classification model to obtain a first violation detection result indicating whether the real-time live broadcast data is compliant or not; and under the condition that the first violation detection result is non-compliant, inputting a text vector corresponding to the real-time live broadcast data into a pre-trained two-stage classification model to obtain a second violation detection result, the second violation detection result comprising suspected violation or serious violation. According to the embodiment of the invention, the model detection efficiency can be improved, and the detection accuracy can be improved.

The invention relates to the technical field of network communication and video processing, in particular to an intelligent global cloud live broadcast system based on AI and multi-operator and multi-cloud optimization, and the system comprises a data collection module which is used for collecting live broadcast video streams; the video compression module adopts H.265 coding; the content review module is used for performing multi-modal review; the RPMTS packaging module is used for accessing three operator cloud private line POP nodes through a public network after packaging; the decoding module is used for decoding POP nodes in the middle area; the translation module is used for generating multi-language subtitles or dubbing; the multi-operator and multi-cloud adaptability matrix module calculates an optimal path in combination with an AI algorithm and a multi-cloud cost adaptability matrix; the multi-branch access module is used for realizing branch node cooperative forwarding; and the multi-language distribution module is used for generating multi-language subtitles and dubbles and pushing the multi-language subtitles and dubbles to each global live broadcast platform, so that synchronous distribution is realized, and the system can reduce global live broadcast delay, improve multi-language coverage capability and realize high reliability and cost optimization.

User authentication, spoofing and replay attack prevention, liveness detection, and user-and-document verification using a live video stream with spatial challenges. A camera of an electronic device captures and transmit a live selfie user-facing video, as part of a user registration process. The user is instructed to spatially move his body or face, such that his face would appear within a first particular on-screen shape; and to also, concurrently or simultaneously, spatially hold in his hand or move a particular an identification document such that it would appear within a second on-screen shape. Optionally, the on-screen shape moves on the screen, and the user is required to spatially move the relevant item to keep it within the boundaries of the moving on-screen shape. The system then analyzes the video via computerized vision, to determine whether the user complied with the spatial manipulation challenges.