A system and method for identifying media segments using audio augmented image cross-comparison is disclosed, in which a media segment identifying system analyses both audio and video content, producing a unique identifier to compare with previously identified media segments in a media segment database. The characteristic landmark-linked-image-comparisons are constructed by first identifying an audio landmark. The audio landmark is an audio peak that exceeds a predetermined threshold. Two digital images are then obtained, one associated directly with the audio landmark, and one obtained a predetermined landmark time removed from the first image. The two images are then used to provide a characteristic landmark-linked-image-comparison. The pair of images are reduced in pixel size and converted to gray scale. Corresponding pixels are compared to form a numeric comparison. One image is mirrored before comparison to reduce the possibility of null comparisons.

A method for providing captured video to a subsequent user device, via a video host, including at least some of allowing a user to designate, via a mobile device, at least one video host; allowing the subsequent user, via the subsequent user device, to be associated with the at least one video host; allowing the user to capture video, via the mobile device, and upload or stream the captured video to the video host device(s), wherein the captured video includes at least one categorization for the captured video, as designated by the user prior to capturing the video; and allowing the subsequent user to access, via the subsequent user device, the captured video, via the video host device associated with the at least one video host, wherein the captured video is accessed, based on the at least one categorization for the captured video.

A method and system for identifying social trends are provided. The method includes collecting multimedia content from a plurality of data sources; gathering environmental variables related to the collected multimedia content; extracting visual elements from the collected multimedia content; generating at least one signature for each extracted visual element; generating at least one cluster of visual elements by clustering at least similar signatures generated for the extracted visual elements; correlating environmental variables related to visual elements in the at least one cluster; determining at least one social trend by associating the correlated environmental variables with the at least one cluster.

A method for automatic metadata tag identification for videos is described. Content features are extracted from a video into respective data structures. The extracted content features are from at least two different feature modalities. The respective data structures are encoded into a common data structure using an encoder of a recurrent neural network (RNN) model. The common data structure is decoded using a decoder of the RNN model to identify content platform metadata tags to be associated with the video on a social content platform. Decoding is based on group tag data for users of the social content platform that identifies groups of the users and corresponding group metadata tags of interest for the groups of users.

Methods and processes for manufacture of an image product from a digital image. An object in the digital image is detected and recognized. Object metadata is assigned to the object, the object metadata linking sound to the object in the digital image which produced the sound. At least one cryptographic hash of the object metadata is generated, and the hash is written to a node of a transaction processing network.

In one aspect, an example method to be performed by a computing device includes (a) receiving a request to use a camera of the computing device; (b) in response to receiving the request, (i) using a microphone of the computing device to capture audio content and (ii) using the camera of the computing device to capture an image; (c) identifying reference audio content that has at least a threshold extent of similarity with the captured audio content; and (d) outputting an indication of the identified reference audio content while displaying the captured image.

Systems and methods of performing video analysis related to a video of an electronic terminal. In one exemplary embodiment, a method is performed by an electronic device that includes processing circuitry. The method may include causing a display to play a video that shows an electronic terminal, automatically detecting a captured event related to the electronic terminal in the video, capturing first time stamp information corresponding to a time point in the video that the captured event occurs in the video, and predicting a future event associated with the captured event related to the electronic terminal in the video. The method may also include capturing and outputting second time stamp information corresponding to a time point in the video that the predicted future event is detected to have occurred in the video.

An electronic device may include a touchscreen display, and a processor, wherein the processor may be configured to receive a first input to select a plurality of videos generated from at least two difference sources, perform video synchronization so that timelines of the plurality of selected videos coincide, extract segmental clips selected in each section from the respective videos, based on a main subject selected by analyzing the plurality of videos, adjust different segmental clips so that subjects included in the different segmental clips are synchronized based on a segmental clip in a first section, automatically generate a cross-edited video by joining segmental clips of respective sections in which the subjects are synchronized, and display the cross-edited video on the touchscreen display

The present disclosure discloses a method and apparatus for extracting a video clip, relates to the field of artificial intelligence technology such as video processing, audio processing, and cloud computing. The method includes: acquiring a video, and extracting an audio stream in the video; determining a confidence that audio data in each preset period in the audio stream comprises a preset feature; and extracting a target video clip corresponding to a location of a target audio clip in the video; wherein the target audio clip is an audio clip within a continuous preset period, and has a confidence that the audio data includes the preset feature, which is larger than a preset confidence threshold. This method may improve the accuracy of extracting a video clip.

Methods and processes for manufacture of an image product from a digital image. An object in the digital image is detected and recognized. Object metadata is assigned to the object, the object metadata linking sound to the object in the digital image which produced the sound. At least one cryptographic hash of the object metadata is generated, and the hash is written to a node of a transaction processing network.