Abstract: A method and an apparatus for generating a video digest, and a readable storage medium are provided. The method is applied to a video acquisition device that includes a hardware unit configured to obtain movement information in real time, the movement information includes speed information and direction information of the video acquisition device. The method includes: starting acquisition of a video signal in response to an acquisition start instruction, and recording movement information corresponding to each frame during the acquisition of the video signal; determining a frequency for key frame extraction according to the movement information corresponding to each frame; determining a key frame from the acquired video signal according to the frequency for key frame extraction; and in response to an acquisition end instruction, generating a video digest according to the key frame.

Abstract: Systems and methods for searching, identifying, scoring, and providing access to companion media assets for a primary media asset are disclosed. In response to a request for companion content, metadata within a predefined time period of a play position when the request was made, is downloaded. A dynamic search template that contains search parameters based on the downloaded metadata is generated. In response to the search conducted using the search template, a plurality of companion media assets are identified and then verified. A trust score for the companion media asset is accessed. The trust score may be analyzed and modified based on its contextual relationship to the play position of the primary media asset. If the trust score is within a rating range, then a link to access the companion media asset, or a specific segment or play position within the companion media asset, is provided.

Abstract: Systems and methods are disclosed preventing accidents by altering user interfaces of self-driving vehicles based on movements of passengers in the self-driving vehicles. The system and methods generate for display media content on a user interface for a self-driving vehicle and determine whether a value of movement from a wearable user device of a user within the self-driving vehicle exceeds a threshold value (indicating the maximum value at which the self-driving vehicle removes the media content on the user interface). Responsive to a determination that the value of the movement from the wearable user device exceeds the threshold value, the system and methods remove the media content on the user interface for the self-driving vehicle.

Abstract: This application provides an audio processing method and an electronic device. A position of a face or a mouth of a person who makes a sound in a video picture is determined, and a range in which sound pickup needs to be enhanced is determined based on the position of the face or the mouth of the person who makes a sound, to implement directional voice enhancement. The method includes: in a process of collecting a video picture and first audio, recognizing a target image of a sound-making object in the video picture; determining, based on the target image, a first sound pickup range corresponding to the sound-making object; and determining second audio based on the first audio and the first sound pickup range. In the second audio, audio volume in the first sound pickup range is greater than audio volume outside the first sound pickup range.

Abstract: Systems, methods, and computer-readable media are disclosed for systems and methods for automated video summary generation using textual quotes. Example methods may include determining first text representing a phrase spoken in video content, determining that the first text is present in first subtitle data of first video content, determining a first timestamp and a second timestamp associated with the first text in the first subtitle data, determining a first video segment of the first video content corresponding to the first timestamp and the second timestamp, and generating a first video summary for the first video content, the first video summary comprising the first video segment.

Abstract: A first graph which is a flow graph is converted into a second graph using a first algorithm. The second graph, combined with a second algorithm using a dynamic programming recursion, is compared with a video and a best matching thread, with respect to the video, is found through the second graph. The best matching thread may then be used for a user-assistance function. The dynamic programming recursion reduces computational effort needed by the computer performing the matching.

Abstract: A video generation method may be applied to the field of image processing and video generation in the field of artificial intelligence. The method includes: receiving a video generation instruction, and obtaining text information and image information in response to the video generation instruction, where the text information includes one or more keywords, and the image information includes N images; obtaining, based on the one or more keywords, one or more image features that is in each of the N images and corresponds to the one or more keywords; and inputting the one or more keywords and the one or more image features of the N images into a target generator network to generate a target video, where the target video includes M images, and the M images are generated based on the one or more image features of the N images and correspond to the one or more keywords.

Abstract: Described, herein, relates to a system and method of accurately and efficiently detecting a tone of a batch of text that achieves both high performance and interpretability by leveraging a multi-head self-attention architecture. The presence of a tone in a batch of text provides a challenge to the performance of a sentiment analysis, since there is an inherent ambiguity in sarcastic expressions that makes sarcasm detection difficult through purely text-based interactions. As such, the multi-head self-attention architecture includes distinct components of routing data through modules comprising data pre-processing, multi-head self-attention, gated recurrent units, and classification, resulting in a modeling system with improved interpretability and accuracy.

Abstract: A system or process may generate a summarization of multimedia content by determining one or more salient moments therefrom. Multimedia content may be received and a plurality of frames and audio, visual, and metadata elements associated therewith are extracted from the multimedia content. A plurality of importance sub-scores may be generated for each frame of the multimedia content, each of the plurality of sub-scores being associated with a particular analytical modality. For each frame, the plurality of importance sub-scores associated therewith may be aggregated into an importance score. The frames may be ranked by importance and a plurality of top-ranked frames are identified and determined to satisfy an importance threshold. The plurality of top-ranked frames are sequentially arranged and merged into a plurality of moment candidates that are ranked for importance. A subset of top-ranked moment candidates are merged into a final summarization of the multimedia content.

Abstract: A video localization system localizes actions in videos based on a classification model and an actionness model. The classification model is trained to make predictions of which segments of a video depict an action and to classify the actions in the segments. The actionness model predicts whether any action is occurring in each segment, rather than predicting a particular type of action. This reduces the likelihood that the video localization system over-relies on contextual information in localizing actions in video. Furthermore, the classification model and the actionness model are trained based on weakly-labeled data, thereby reducing the cost and time required to generate training data for the video localization system.

Abstract: A method includes: ingesting a video; initializing a timed command stream synchronized to the video; emulating transcoding of the video to derive a sequence of video characteristics of the video; populating the timed command stream with the sequence of video characteristics; segmenting the video into a series of mezzanine segments.

Abstract: Methods and apparatus provide for: receiving video game data generated during the playing of a video game, the video game including at least a video and corresponding audio signal; and inputting each signal in the received video game data into a respective machine learning model and determining based on the output of each model, whether a highlight event has occurred during the playing of the video game. At least some of the frames in the video and or audio signal are then selected for inclusion in a recording of the video game gameplay, based on a determination that a highlight event has occurred and a recording is generated that includes the selected video and or audio frames. A method for training the models is also provided, along with systems for training and executing the trained models.

Abstract: Disclosed herein are system, apparatus, article of manufacture, method, and/or computer program product embodiments for a crowd sourced indexing and/or searching of content. An embodiment operates by receiving one or more requests for content from one or more media devices, each request comprising content identifier information that identifies the content, determining whether crowd sourced content index information has been generated for the content, transmitting a response to the one or more media devices of the one or more media devices, in response to the one or more requests, the response comprising content location information and a content indexing request, and receiving content index information for the content identified by the content identifier information from the one or more media devices.

Abstract: Disclosed are a multimedia data generating method, apparatus, electronic device, medium, and program product, applied to the field of multimedia data processing technologies. The method includes: receiving text information inputted by a user; displaying, in response to a recording trigger operation for the text information, the text information and acquiring a first reading speech of the text information; and generating a first multimedia data based on the text information and the first reading speech and displaying the first multimedia data; the first multimedia data includes the first reading speech and a video image matched with the text information; the first multimedia data includes a plurality of first multimedia segments; the plurality of first multimedia segments correspond to a plurality of text segments included in the text information, respectively. The disclose may improve quality of multimedia data generation.

Abstract: In a cloud-based system for encoding high dynamic range (HDR) video, each node receives a video segment and bumper frames. Each segment is subdivided into primary scenes and secondary scenes to derive scene-based forward reshaping functions that minimize the amount of reshaping-related metadata when coding the video segment, while maintaining temporal continuity among scenes processed by multiple nodes. Methods to generate scene-based forward and backward reshaping functions to optimize video coding and improve the coding efficiency of reshaping-related metadata are also examined.

Abstract: Techniques implementable by a computer system are provided. The techniques include receiving, by a server device, a request to stream media, the request including a media content and a streaming start point in the media content. The techniques also include determining a first time length based at least in part on time to receive permissioning. The techniques also include determining a silence point in the media content based at least in part on the streaming start point, the first time length, and identified silence points in the media content. The techniques also include determining a second time length based at least in part on the silence point and the streaming start point, the second time length defining a clear portion. The techniques also include generating a media stream comprising the clear portion and a remaining portion, the clear portion having a time length of the second time length.

Abstract: The present disclosure relates to a method of creating an original video into a short-time summary video. According to the present invention, a summary video is made by focusing on a dynamic object appearing in an original video, but a plurality of objects appearing in the same time period in the original video are made to appear together in the same time period in the summary video. Accordingly, when an event occurs, there is an advantage in that the relevance between objects in the event may be easily identified.

Abstract: A method includes receiving training images representing a portion of a drilling rig over a first period of time, associating individual training images of the training images with times at which the individual training images were captured, determining a rig state at each of the times, classifying the individual training images based on the rig state at each of the times, training a machine learning model to identify rig state based on the classified training images, receiving additional images representing the portion of the drilling rig over a second period of time, and determining one or more rig states of the drilling rig during the second period of time using the machine learning model based on the additional images.

Abstract: This disclosure relates to a system, method, and computer program for automatically generating audio tracks for a video based on a current state of the video. The system provides a novel way to produce one or more audio tracks for a video. The system enables a user to enter a request for an audio track. In response to receiving the request, the system identifies the current state of a video, including the assets, scenes, and timelines in the video. Attributes of the current state of the video are then used to guide the output of machine-learning audio-generation models, which generate one or more audio clips for the video. In this way, visual assets added to a video can be used to guide the output of machine learning models that generate audio for the video. The sound clips produced by the machine-learning modules are then mixed to produce an audio track for the video.

Abstract: Methods and systems are described for providing optimal representations of content. A user interface may present content based on one or more images representing the content. User interactions associated with the content may be tracked based on which of the one or more images was used to represent the content. Statistical information may be tracked to determine which groups of users respond to particular images used to represent content. The statistical information may be used to select which images are used to represent the content for additional users.

Abstract: Systems and methods are provided for detecting a content type of content within a media stream. A computing device may receive a media stream and define a set of media segments that each represent a portion of the media stream. The computing device may identify a first media segment that includes a first boundary and a second media segment that includes a second boundary. The computing device may predict whether the subset of media segments that are positioned between the first media segment and the second media segment include content of a particular content type. The computing device may then transmit an indication of the prediction.

Abstract: Encoded content is accessed. The encoded content includes an encoded first centrally located tile corresponding to a first centrally located tile of a first image, an encoded first peripherally located tile of the first image, and an encoded second peripherally located tile of a second image. The encoded first peripherally located tile is decoded to obtain a decoded first peripherally located tile. The encoded second peripherally located tile is decoded to obtain a decoded second peripherally located tile. The decoded first peripherally located tile and the decoded second peripherally located tile are stitched to obtain a stitched image portion. The stitched image portion is encoded to obtain an encoded stitched image portion. An encoded stitched image of the first image and the second image is obtained by combining the encoded first centrally located tile, and the encoded stitched image portion.

Abstract: A video processing method, an electronic device and a storage medium are provided, and relate to the field of artificial intelligence, and particularly relates to the fields of deep learning, model training, knowledge mapping, video processing and the like. The method includes: acquiring a plurality of first video frames, and performing fine-grained splitting on the plurality of first video frames to obtain a plurality of second video frames; performing feature encoding on the plurality of second video frames according to multi-mode information related to the plurality of second video frames, to obtain feature fusion information for characterizing fusion of the multi-mode information; and performing similarity matching on the plurality of second video frames according to the feature fusion information, and obtaining a target video according to a result of the similarity matching.

Abstract: Embodiments described herein provide an intelligent method to select instances, by utilizing unsupervised tracking for videos. Using this freely available form of supervision, a temporal constraint is adopted for selecting instances that ensures that different instances contain the same object while sampling the temporal augmentation from the video. In addition, using the information on the spatial extent of the tracked object, spatial constraints are applied to ensure that sampled instances overlap meaningfully with the tracked object. Taken together, these spatiotemporal constraints result in better supervisory signal for contrastive learning from videos.

Abstract: Embodiments of a video codec may include technology to derive a conformance point for a sub-region of coded pictures in a coded video sequence in the video data, group any combination of sub-pictures that form a rectangular region into a sub-picture set, and/or derive a level indicator corresponding to a sub-picture based on a level of the coded video sequence and a relative size of the coded picture and the sub-picture set. Other embodiments are disclosed and claimed.

Abstract: Embodiments of the disclosure provide a data processing method and apparatus, a device, and a medium. The method includes: performing video analysis on video data of a target video to obtain a plurality of video segments; determining a video template associated with a target user from a video template database based on a user portrait of the target user, and obtaining at least one predetermined template segment and a template tag sequence in the video template; screening at least one video segment matching the template attribute tag of the at least one template segment; splicing the at least one matched video segment according to a position of a template attribute tag of each template segment in the template tag sequence as a video material segment of the target video; and pushing the video data and the video material segment to an application client corresponding to the target user.

Abstract: A digital watermark is applied to a video to be distributed without re-encoding. A content distribution device 1 receives a content acquisition request to request video content, distributes the video content based on the content acquisition request, generates and distributes a watermark video with a watermark ID embedded, and causes watermark-video-related information including the watermark ID to be recorded, and a content playback device 2 transmits the content acquisition request, receives the video content and the watermark video, plays back and displays the video content, and superimposes the watermark video on the video content for playback and display.

Abstract: Systems and methods are provided herein for generating optimized video segments. A derivative video segment (e.g., a scene) can be identified from derivative video content (e.g., a movie trailer). The segment may be used a query to search video content (e.g., the movie) for the segment. Once found, an optimized video segment may be generated from the video content. The optimized video segment may have a different start time and/or end time than those corresponding to the original segment. Once optimized, the video segment may be presented to a user or stored for subsequent content recommendations.

Abstract: A computer implemented network for executing a self-supervised scene change detection method in which image pairs (T0, T1) from different time instances are subjected to random photometric transformations to obtain two pairs of augmented images (T0?T0?, T0?; T1?T1?, T1?), which augmented images are passed into an encoder (f?) and a projection head (g?) to provide corresponding feature representations.

Abstract: A content distribution platform is disclosed. The content distribution platform enables content creators to upload video based content onto the platform. Users can then view the videos or shortened versions of the videos. The videos may be classified/categorized based on the contents of the video. Based on the categorization/classifications, specific product and service recommendations may be made to users. Recommendations can also be made based on tracking user behavior across the platform.

Abstract: Systems and methods are provided for determining whether to extend a recording of a media asset based on analyzing user data. A media guidance application may determine that a media asset is recording during a scheduled time slot that has a start time and an end time. The media guidance application may determine that the media asset will be transmitted outside of the scheduled time slot based on inputs from a plurality of users. In response to determining that the media asset will be transmitted outside of the scheduled time, the media guidance application may extend the recording of the media asset beyond the scheduled time slot by a predetermined amount of time.

Abstract: A method provides concurrent transmission of a virtual action center with a primary segment cropped from a video image, enabling remote participant control of aspects of the primary segment. The method includes identifying a primary region of interest (ROI) within a video image and delineating the video image into a primary segment encompassing the primary ROI and a secondary segment. The method includes associating a virtual action center within a location of the secondary segment and assigning control features of the virtual action center to the second device connected via a video communication session. The method includes transmitting the primary segment and concurrently transmitting the features/functions of the virtual action center to the second device, enabling the second device to concurrently present, on its display, the primary segment and the virtual action center as portions of a received video stream, providing second device control of content within the primary segment.

Abstract: A system (1) for handling data captured by a body worn camera (2) is disclosed. The system (1) comprises a body worn camera (2), a docking station (3), and a recorder (4). The camera (2) comprises a local storage device (6). The docking station (3) comprises a data interface (7) for connecting the local storage device (6) to the docking station (3), and a first network interface (8) for connecting the docking station (3) to the recorder (4). The docking station is physically separate from the recorder. The recorder (4) comprises a second network interface (9) for connecting the recorder (4) to the docking station (3), and a recorder storage device (10). The recorder (4) is arranged to retrieve the captured data from the camera (2) and store it in the recorder storage device (10), and comprises a third network interface (11) for transfer of stored data to a data management system (5). A method for handling data captured by a body worn camera (2) is also disclosed.

Abstract: This disclosure generally relates to systems and methods that facilitate employing a server based content recording component for recording content remotely for a client content video recording device that has limited storage and limited number of content streams to which it can access concurrently, while satisfying content rules for broadcast and re-transmission.

Abstract: Video content screening using a trained video screening model trained using self-supervised training includes automatically generating a training dataset by obtaining predicate screening data indicating a predicate temporal segment within a training video and a corresponding reference temporal segment within the reference video, obtaining candidate screening data for an extended temporal segment from the training video, wherein the extended temporal segment includes the predicate temporal segment and at least one frame from the training video adjacent to the predicate temporal segment, wherein the candidate screening data indicates a similarity between a screening frame from the reference video and a spatial portion of a candidate frame from the extended temporal segment, and, in response to a determination that a determined similarity between the candidate subframe including, in the automatically generated training dataset, training example data indicating the similarity between the candidate subframe and th

Abstract: Systems and methods describe presenting media to a user at a user device, determining a location relevant to the media, determining whether the user has visited a vicinity of the location by searching through information related to the user, and based on to determining that the user has visited the vicinity of the location searching through the user's personal collection of media in a time window corresponding to the user's visit to retrieve personal media related to the location, and generating for display, based on the searching, a list of personal media related to the location relevant to the media being presented at the user device.

Abstract: A method includes collecting user activity data for a first online media item. The user activity data can be data for a user consuming the first online media item. The method further includes segmenting a second online media item into a plurality of segments, and identifying one or more of the plurality of segments with user activity data satisfying one or more criteria. The identified segments comprise a set of frames of the plurality of frames of the second online media item. The method further includes selecting a frame from the set of frames from the second online media item. The method further includes sending a recommendation of the selected frame as a thumbnail recommendation for the second online media item to a client device.

Abstract: Disclosed is a master electronic device configured to create a content capture session executable by a plurality of electronic devices comprising at least one client electronic device. The master electronic device may comprise: a user interface module configured to receive at least one session parameter; a processor configured to create at least one content capture session based on the at least one session parameter; and a communication means configured to communicate data between the master electronic device and at least one client electronic device, wherein the communication comprises transmission of at least one session parameter, wherein the at least one client electronic device is configured to participate in the at least one content capture session according to the at least one session parameter.

Abstract: The present disclosure provides computing systems and methods for cataloging, retrieving, and/or organizing user-generated content associated with objects. Aspects of the disclosure are directed to a systems and methods which utilize computers to enable users to interact with libraries of user-generated content associated with cataloged objects. For example, a user can capture one or more images of a real-world object, label or otherwise annotate the object with various types of user-generated content and organize the object and its associated content into one or more libraries. The user-generated content can then be provided to other users upon the receipt of images of the same object or an object displaying similar features.

Abstract: Technologies and techniques for optimizing a patient overview in a user interface (UI), utilizing at least one processor. An optimize request is received including an optimization level from a user via the UI, selecting predetermined patient information associated with the received optimization level, and displaying an optimized patient overview containing the selected certain patient information to the user.

Abstract: Systems and methods to reconfigure a scene based on timing and scene content are disclosed. Exemplary implementations may: obtain scene information defines a scene in which an event transpires; analyze the scene information that defines the event to identify effectual content and ineffectual content related to the event within the unedited event duration; and generate, based on the scene information and the analysis, a draft scene that includes an edited event comprising the effectual content from an edited event beginning to an edited event end in accordance with the prospective event duration.

Abstract: An apparatus for encoding an image block includes a processor that presents, to a machine-learning model, the image block, obtains the partition decision for encoding the image block from the model, and encodes the image block using the partition decision. The model is trained to output a partition decision for encoding the image block by using training data for a plurality of training blocks as input, the training data including for a training block, partition decisions for encoding the training block, and, for each partition decision, a rate-distortion value resulting from encoding the training block using the partition decision. The model is trained using a loss function combining a partition loss function based upon a relationship between the partition decisions and respective predicted partitions, and a rate-distortion cost loss function based upon a relationship between the rate-distortion values and respective predicted rate-distortion values.

Abstract: A method and a system for virtual reality, augmented reality, mixed reality, or 360-degree Video environment is disclosed. The system receives Video Streams associated to audio and video scenes to be reproduced and Audio Streams associated to audio and video scenes to be reproduced. There are provided a Video decoder which decodes signal from the Video Stream for the representation of the audio and video scene; an Audio decoder which decodes signal from the Audio Stream for the representation of the audio and video scene to the user; and a region of interest processor deciding, based e.g. on the user's viewport, head orientation, movement data, or metadata, whether an Audio information message is to be reproduced. At the decision, the reproduction of the Audio information message is caused.

Abstract: An example device for requesting a reduced resolution for video data includes a memory configured to store video data; and one or more processors implemented in circuitry and configured to: decode a first sequence of pictures of a bitstream, the first sequence of pictures having a first resolution; in response to determining that the device is to enter a power saving mode, send a message requesting a reduced resolution relative to the first resolution for a second sequence of pictures, the second sequence of pictures being subsequent to the first sequence of pictures in coding order; and decode the second sequence of pictures of the video data of the bitstream, the second sequence of pictures having the reduced resolution. The reduced resolution may be reduced spatial resolution, reduced temporal resolution (frame rate), or both.

Abstract: Systems and methods are provided for generating for display, with a media asset, one or more preview images. If a preview image corresponding to an advanced play position, relative to a current play position, provides a spoiler, an alternative preview image is generated for display. The alternative image may be a modified version of the original image in which at least a portion is removed or masked, or a replacement image, e.g., an image from another play position, a promotional image, or an indication that the preview image is not displayed. A different alternative image or modification may be used when a subsequent play position has been reached if the unmodified preview image contains a different spoiler, and/or a previous modification is no longer required, e.g., if, at the subsequent play position, the original image is no longer a spoiler, the original image may be used as a preview image.

Abstract: Data storage operations, including content-indexing, containerized deduplication, and policy-driven storage, are performed within a cloud environment. The systems support a variety of clients and cloud storage sites that may connect to the system in a cloud environment that requires data transfer over wide area networks, such as the Internet, which may have appreciable latency and/or packet loss, using various network protocols, including HTTP and FTP. Methods are disclosed for content indexing data stored within a cloud environment to facilitate later searching, including collaborative searching. Methods are also disclosed for performing containerized deduplication to reduce the strain on a system namespace, effectuate cost savings, etc. Methods are disclosed for identifying suitable storage locations, including suitable cloud storage sites, for data files subject to a storage policy.

Abstract: Aspects of the disclosure relate to annotated video content. A computing platform may train a model using video content, which may configure the model to classify topics and identify speakers of future video content using STT and NLP. The computing platform may input new video content into the model, which may output an annotated version of the new video content. The model may be configured to generate the annotated version of the new video content by: 1) using one or more STT techniques to produce STT results, 2) classifying topics based on the STT results, 3) identifying speakers based on analysis of voice information, and 4) generating an index indicating a speaker and/or a topic corresponding to time segments. The computing platform may store the annotated version of the new video content, which may be navigable by a user using the visual index.

Abstract: A method, apparatus, and electronic device for processing a video, a medium and a product are presented. An implementation of the method includes: acquiring a target video; selecting, from at least one preset model, a preset model as a target model; determining output data of the target model based on the target video and the target model; reselecting, in response to determining that the output data does not meet a condition corresponding to the target model, another preset model as the target model from the at least one preset model until the output data of the target model meets the condition corresponding to the target model; and determining, based on the output data, a dynamic cover from the target video.

Abstract: The present technology relates to a file generation device, a file generation method, a file reproduction device, a file reproduction method, and a program capable of associating an image stored is a file with external data outside the file. A file control unit generates an association-type high efficiency image file format (HEIF) file in which an image in an HEIF file compliant with HEIF and specific information that specifies external data outside the HEIF file, the external data to be associated with the image, are stored in association with each other. Furthermore, the file control unit reproduces the association-type HEIF file. The present technology can be applied to a case where an HEIF file is generated or a case where the HEIF file is reproduced.

Abstract: A controlling method of an electronic apparatus may include: obtaining image data and metadata regarding the image data, the image data comprising a first image frame and a second image frame that is subsequent to the first image frame; obtaining information regarding a region of interest of the first image frame by inputting the first image frame to a first neural network model; obtaining a similarity between the first image frame and the second image frame based on motion vector information included in the metadata; and detecting whether there is a manipulated area in the second image frame based on the similarity.