A computer implemented method is provided for a virtual training system. A virtual surgical simulation associated with a type of surgical procedure is accessed. Image data associated with a controller and a workspace is received. Controller data corresponding to a controller interaction is received. A first interaction of the controller within the workspace based on at least one of the image data and the controller data is determined. Using the set of one or more transformation rules, the first interaction of the controller is transformed to a manipulation of a virtualized surgical tool in the virtual surgical simulation. A representation is output of the manipulation of the virtualized surgical tool.

A method includes screening, by a video-clip screening module in a video description model, a plurality of video proposal clips acquired from a video to be analyzed, to acquire a plurality of video clips suitable for description. The plural video proposal clips acquired from the video to be analyzed may be screened by the video-clip screening module to acquire the plural video clips suitable for description; and then, each video clip is described by a video-clip describing module, thus avoiding description of all the video proposal clips, only describing the screened video clips which have strong correlation with the video and are suitable for description, removing the interference of the description of the video clips which are not suitable for description in the description of the video, guaranteeing the accuracy of the final descriptions of the video clips, and improving the quality of the descriptions of the video clips.

Disclosed are a video automatic editing method and system based on machine learning. The video automatic editing system based on machine learning includes at least one processor, and the at least one processor includes a video acquirer configured to acquire input video, a highlight frame extractor configured to extract at least one highlight frame from the input video using a highlight extraction model pre-trained through machine learning, and a highlight video generator configured to generate highlight video from the at least one extracted highlight frame.

System and method for crowdsourcing a video summary for creating an enhanced video summary are disclosed. The method includes receiving videos, analysing the videos, creating the video summary of the videos using a building block model, storing the video summary in a video library database, crowdsourcing the video summary to at least one of the plurality of users, enabling the at least one of the plurality of users to review the video summary and identify at least one new characteristic, enabling the at least one of the plurality of users to share the at least one new characteristic on the platform, comparing at least one existing characteristic of the building block model with the corresponding new characteristic, reconciling the video summary along with at least one inserted new characteristic, creating a new building block model, editing the video summary for creating the enhanced video summary.

A server configured to receive video clips from a mobile device, such as eyewear. The server has an electronic processor enabled to execute computer instructions to process the video clips to identify one or more characteristics in the frames of the video clips. The processor selects the video clips having the identified characteristics in the frames and creates a set of the selected video clips having the identified characteristics in the frames. The processor automatically trims, or allows a user of the mobile device to edit and trim the video clips having the identified characteristics to create trimmed video clip segments. The processor enables a user of the mobile device to view, post, send, and export a selected said video clip segment to another user.

A system for driver identification includes an interface and a processor. The interface is configured to receive a trip; and receive a set of albums, wherein an album of the set of albums includes one or more existing trips. The processor is configured to determine similarities for the trip to all trips in the set of albums; determine a first clustering based at least in part on the similarities; indicate that the trip is a provisionally assigned trip that is provisionally assigned to the album of the set of albums based at least in part on the first clustering; determine a second clustering for a set of provisionally assigned trips and all trips in the set of albums, wherein the set of provisionally assigned trips comprises qualified provisionally assigned trips; and determine updated trip assignments for an updated set of albums.

A method for evaluating a game element is disclosed herein. In one example, the method includes receiving a data set representing the game element and generating a predicted response to the game element by inputting the data set into a machine learning model. In some embodiments, the machine learning model is trained on a plurality of training samples derived from previous gameplay data. In some embodiments, each training sample includes a gameplay event and a player response associated with the gameplay event.

The present invention relates to a system for video processing, wherein the system (10) comprises: an input unit (11), a processing unit (12) and an output unit (13). The input unit (11) inputs a video which includes one or more events defining a boundary of a respective scene within the video. The processing unit (12) processes the video to identify the event and insert a cue point at the boundary. The output unit (13) outputs the processed video. A method (20) for video processing is also disclosed.

In an approach for improving the virtual meeting user experience, a processor detects a user disengaging from a virtual meeting having at least two participants for a pre-set period of time or for a pre-set percentage of a total allotted time of a pre-scheduled virtual meeting. A processor retrieves data from a database. A processor prepares a summary that is tailored to a profile of the user and that covers a portion of the virtual meeting during which the user was disengaged. A processor detects the user reconnecting to the virtual meeting. A processor determines whether the user will review the summary before rejoining the virtual meeting. Responsive to determining the user will review the summary before rejoining the virtual meeting, a processor prompts the user with a set of default user preferences to review the summary. A processor outputs the summary to the user.

A media summary is generated to include portions of media items. The portions of media items identified for inclusion in the media summary is determined based on the length of the media summary and classification of content depicted within the media items. Classification of content depicted within the media items includes number of smiles depicted within the media items.