Abstract: A method includes grouping media items associated with a user into segments based on a timestamp associated with each media item and a total number of media items. The method also includes selecting target media from the media items for each of the segments based on media attributes associated with the media item. The method also includes generating a video that includes the target media for each of the segments by generating a first animation that illustrates a first transition from a first item from the target media to a second item from the target media with movement of the first item from an onscreen location to an offscreen location, wherein the first item is adjacent to the second item in the first animation and determining whether the target media includes one or more additional items. The method also includes adding a song to the video.

Abstract: A method includes grouping media items associated with a user into segments based on a timestamp associated with each media item and a total number of media items. The method also includes selecting target media from the media items for each of the segments based on media attributes associated with the media item. The method also includes generating a video that includes the target media for each of the segments by generating a first animation that illustrates a first transition from a first item from the target media to a second item from the target media with movement of the first item from an onscreen location to an offscreen location, wherein the first item is adjacent to the second item in the first animation and determining whether the target media includes one or more additional items. The method also includes adding a song to the video.

Abstract: A method includes grouping media items associated with a user into segments based on a timestamp associated with each media item and a total number of media items. The method also includes selecting target media from the media items for each of the segments based on media attributes associated with the media item. The method also includes generating a video that includes the target media for each of the segments by generating a first animation that illustrates a first transition from a first item from the target media to a second item from the target media with movement of the first item from an onscreen location to an offscreen location, wherein the first item is adjacent to the second item in the first animation and determining whether the target media includes one or more additional items. The method also includes adding a song to the video.

Abstract: A method includes grouping media items associated with a user into segments based on a timestamp associated with each media item and a total number of media items. The method also includes selecting target media from the media items for each of the segments based on media attributes associated with the media item. The method also includes generating a video that includes the target media for each of the segments by generating a first animation that illustrates a first transition from a first item from the target media to a second item from the target media with movement of the first item from an onscreen location to an offscreen location, wherein the first item is adjacent to the second item in the first animation and determining whether the target media includes one or more additional items. The method also includes adding a song to the video.

Abstract: A system and method for identifying one or more notable moments from video data are disclosed. In one embodiment, the system includes a video receiving module, an identification criteria module, a moment identification module and a presentation module. The video receiving module receives video data. The identification criteria module determines one or more criteria for identifying a notable moment. The one or more criteria are based at least in part on one or more of an audio indicator and a facial indicator. The moment identification module automatically identifies at least one notable moment in the video data based at least in part on the one or more criteria. The at least one notable moment is based on a subset of the video data. The presentation module sends the identified at least one notable moment for presentation to at least one user.

Abstract: A method includes grouping media items associated with a user into segments based on a timestamp associated with each media item and a total number of media items. The method also includes selecting target media from the media items for each of the segments based on media attributes associated with the media item. The method also includes generating a video that includes the target media for each of the segments by generating a first animation that illustrates a first transition from a first item from the target media to a second item from the target media with movement of the first item from an onscreen location to an offscreen location, wherein the first item is adjacent to the second item in the first animation and determining whether the target media includes one or more additional items. The method also includes adding a song to the video.

Abstract: A method includes grouping media items associated with a user into segments based on a timestamp associated with each media item and a total number of media items. The method also includes selecting target media from the media items for each of the segments based on media attributes associated with the media item. The method also includes generating a video that includes the target media for each of the segments by generating a first animation that illustrates a first transition from a first item from the target media to a second item from the target media with movement of the first item from an onscreen location to an offscreen location, wherein the first item is adjacent to the second item in the first animation and determining whether the target media includes one or more additional items. The method also includes adding a song to the video.

Abstract: Implementations generally relate to enhancing a video. In some implementations, a method includes classifying one or more objects in one or more frames of the video. The method further includes determining one or more filter parameters of one or more filters based on the classifying of the one or more objects. The method further includes smoothing one or more of the determined filter parameters based on the classifying of the one or more objects. The method further includes applying one or more of the filters with corresponding smoothed filter parameters to one or more frames of the video.

Abstract: Implementations generally relate to enhancing a video. In some implementations, a method includes classifying one or more objects in one or more frames of the video. The method further includes determining one or more filter parameters of one or more filters based on the classifying of the one or more objects. The method further includes smoothing one or more of the determined filter parameters based on the classifying of the one or more objects. The method further includes applying one or more of the filters with corresponding smoothed filter parameters to one or more frames of the video.

Abstract: A computer-implemented method, computer program product, and computing system is provided for interacting with images having similar content. In an embodiment, a method may include identifying one or more event attributes associated with an ongoing event. The method may also include determining one or more statistical characteristics associated with the one or more of the event attributes. The method may further include generating a prompt to an event participant to take a photograph during the ongoing event based on, at least in part, the one or more statistical characteristics.

Abstract: A system and method for identifying one or more notable moments from video data are disclosed. In one embodiment, the system includes a video receiving module, an identification criteria module, a moment identification module and a presentation module. The video receiving module receives video data. The identification criteria module determines one or more criteria for identifying a notable moment. The one or more criteria are based at least in part on one or more of an audio indicator and a facial indicator. The moment identification module automatically identifies at least one notable moment in the video data based at least in part on the one or more criteria. The at least one notable moment is based on a subset of the video data. The presentation module sends the identified at least one notable moment for presentation to at least one user.

Abstract: A computer-implemented method, computer program product, and computing system is provided for interacting with images having similar content. In an embodiment, a method may include identifying one or more event attributes associated with an ongoing event. The method may also include determining one or more statistical characteristics associated with the one or more of the event attributes. The method may further include generating a prompt to an event participant to take a photograph during the ongoing event based on, at least in part, the one or more statistical characteristics.