Abstract: A method for calibrating a position of a laser beam in an apparatus comprising at least one optical unit for directing the laser beam is provided. The at least one optical unit comprises a plurality of optical elements.

Abstract: According to some aspects, methods and systems may include receiving, by a computing device, metadata identifying an event occurring in a video program, and determining an expected motion of objects in the identified event. The methods and systems may further include analyzing motion energy in the video program to identify video frames in which the event occurs, and storing information identifying the video frames in which the event occurs.

Abstract: Methods and apparatus for generating personalized menus and a media content interface are provided. In one example, different device specific media asset lists are generated at different user devices for the same user based on the media consumption history at each device. In another example, media asset listings are displayed for multicast and on-demand media assets determined to be of interest to the user. An on-demand media asset is listed at a time when no other multicast media assets are listed. In another example, media asset listings for successive episodes of a media series are displayed in sequential order in response to an input to view successive episodes of a media series. In another example, a text search for media content is performed in which the search priority of media provider results is decreased relative to the search priority of media asset results as additional characters are added to a search string.

Abstract: Methods and apparatus for generating personalized menus and a media content interface are provided. In one example, different device specific media asset lists are generated at different user devices for the same user based on the media consumption history at each device. In another example, media asset listings are displayed for multicast and on-demand media assets determined to be of interest to the user. An on-demand media asset is listed at a time when no other multicast media assets are listed. In another example, media asset listings for successive episodes of a media series are displayed in sequential order in response to an input to view successive episodes of a media series. In another example, a text search for media content is performed in which the search priority of media provider results is decreased relative to the search priority of media asset results as additional characters are added to a search string.

Abstract: Systems, apparatuses, and methods are described for determining boundaries within a content asset. A server may collect user interaction data for one or more content assets. Using the user interaction data, the server may determine commercial breaks or scene changes for the content asset. The server may apply best fit curves to the user interaction data, and determine commercial breaks or scene changes based on the best fit curves.

Abstract: Systems, apparatuses, and methods are described for determining boundaries within a content asset. A server may collect user interaction data for one or more content assets. Using the user interaction data, the server may determine commercial breaks or scene changes for the content asset. The server may apply best fit curves to the user interaction data, and determine commercial breaks or scene changes based on the best fit curves.

Abstract: Methods and apparatus for generating personalized menus and a media content interface are provided. In one example, different device specific media asset lists are generated at different user devices for the same user based on the media consumption history at each device. In another example, media asset listings are displayed for multicast and on-demand media assets determined to be of interest to the user. An on-demand media asset is listed at a time when no other multicast media assets are listed. In another example, media asset listings for successive episodes of a media series are displayed in sequential order in response to an input to view successive episodes of a media series. In another example, a text search for media content is performed in which the search priority of media provider results is decreased relative to the search priority of media asset results as additional characters are added to a search string.

Abstract: According to some aspects, methods and systems may include receiving, by a computing device, metadata identifying an event occurring in a video program, and determining an expected motion of objects in the identified event. The methods and systems may further include analyzing motion energy in the video program to identify video frames in which the event occurs, and storing information identifying the video frames in which the event occurs.

Abstract: Various implementations described herein are directed to determining variations or changes to a predetermined programming schedule. In accordance with one method, a predicted end time of video content may be determined to be later than a scheduled end time of the video content. Also, it may be determined that video content scheduled to be displayed on a first stream or channel has been moved to a second stream or channel. A scheduled recording or transmission time of video content may be altered based on detected changes to the predetermined programming schedule. A program listing such as an electronic program guide may be revised based on detected changes to the predetermined programming schedule.

Abstract: According to some aspects, methods and systems may include receiving, by a computing device, metadata identifying an event occurring in a video program, and determining an expected motion of objects in the identified event. The methods and systems may further include analyzing motion energy in the video program to identify video frames in which the event occurs, and storing information identifying the video frames in which the event occurs.

Abstract: According to some aspects described herein, content and service providers in a media delivery network may provide improved recommendations and/or personalize a user's experience based on the real-time activity of that user as well as other users. In this way, ever increasing amounts of content may be optimally managed in a way that provides users with the improved and/or personalized experience.

Abstract: Systems, apparatuses, and methods are described for determining boundaries within a content asset. A server may collect user interaction data for one or more content assets. Using the user interaction data, the server may determine commercial breaks or scene changes for the content asset. The server may apply best fit curves to the user interaction data, and determine commercial breaks or scene changes based on the best fit curves.

Abstract: According to some aspects described herein, content and service providers in a media delivery network may provide improved recommendations and/or personalize a user's experience based on the real-time activity of that user as well as other users. In this way, ever increasing amounts of content may be optimally managed in a way that provides users with the improved and/or personalized experience.

Abstract: Methods, systems, and apparatuses are described for identifying highlights of a content item. A media clip may be obtained from a content sharing service. The media clip may correspond to a media content. A portion of the media content that is included in the media clip may be determined, and a popularity value of the media clip may be obtained from the content sharing service. A popularity metric for the portion of the media content may be determined and displayed.

Abstract: Systems, apparatuses, and methods are described for determining boundaries within a content asset. A server may collect user interaction data for one or more content assets. Using the user interaction data, the server may determine commercial breaks or scene changes for the content asset. The server may apply best fit curves to the user interaction data, and determine commercial breaks or scene changes based on the best fit curves.

Abstract: Various implementations described herein are directed to determining variations or changes to a predetermined programming schedule. In accordance with one method, a predicted end time of video content may be determined to be later than a scheduled end time of the video content. Also, it may be determined that video content scheduled to be displayed on a first stream or channel has been moved to a second stream or channel. A scheduled recording or transmission time of video content may be altered based on detected changes to the predetermined programming schedule. A program listing such as an electronic program guide may be revised based on detected changes to the predetermined programming schedule.

Abstract: Methods, systems, and apparatuses are described for identifying highlights of a content item, and identifying times, within the content item, to indicate as a beginning of a chapter within the content item. A second content item that corresponds to a portion of the first content item may be identified. The portion of the first content item may be determined to be a highlight of the first content item. Shot boundaries of the content item may be determined, and chapter information corresponding to a different version of the content item may be mapped to the content item.

Abstract: A display and/or control element, that includes a layer stack having a TFT layer, a liquid crystal cell and a color filter glass, wherein the color filter glass may be arranged on an outer surface of the layer stack. In some configurations, the color filter glass may project laterally from the layer stack.

Abstract: Methods and apparatus for generating personalized menus and a media content interface are provided. In one example, different device specific media asset lists are generated at different user devices for the same user based on the media consumption history at each device. In another example, media asset listings are displayed for multicast and on-demand media assets determined to be of interest to the user. An on-demand media asset is listed at a time when no other multicast media assets are listed. In another example, media asset listings for successive episodes of a media series are displayed in sequential order in response to an input to view successive episodes of a media series. In another example, a text search for media content is performed in which the search priority of media provider results is decreased relative to the search priority of media asset results as additional characters are added to a search string.

Abstract: Methods and apparatus for generating personalized menus and a media content interface are provided. In one example, different device specific media asset lists are generated at different user devices for the same user based on the media consumption history at each device. In another example, media asset listings are displayed for multicast and on-demand media assets determined to be of interest to the user. An on-demand media asset is listed at a time when no other multicast media assets are listed. In another example, media asset listings for successive episodes of a media series are displayed in sequential order in response to an input to view successive episodes of a media series. In another example, a text search for media content is performed in which the search priority of media provider results is decreased relative to the search priority of media asset results as additional characters are added to a search string.