Method and apparatus for smart video skipping

Abstract

Aspects of the subject disclosure may include obtaining a first media content item comprising a plurality of content segments. For each content segment of the plurality of content segments of the first media content item, comparing the content segment and a prior content segment to identify a content transition, analyzing the content segment to identify a content marker in the content segment, determining a viewing characteristic of the content segment according to the content transition and the content marker, determining if the content segment is unnecessary according to the viewing characteristic, and updating a set of skipping instructions associated with the first media content item responsive to the determining the content segment is unnecessary, and presenting the first media content item at a first device according to the set of skipping instructions associated with the first media content item. Other embodiments are disclosed.

What is claimed is: 
     
         1 . A method, comprising:
 determining, by a processing system including a processor, genre information based on historic skipping data;   identifying, by the processing system, a maximum rating to apply to a media content item;   detecting, by the processing system, content transitions in the media content item using a machine learning algorithm that models transitions as differentials between frames;   responsive to the detecting the content transitions, for each content segment of a plurality of content segments of the media content item:
 analyzing, by the processing system, the content segment to identify one or more content markers in the content segment; 
 determining, by the processing system, a plurality of viewing characteristics of the content segment according to the one or more content markers, wherein the plurality of viewing characteristics includes a content rating associated with the content segment and a genre associated with the content segment; 
 determining, by the processing system, if the content segment is unnecessary according to a first comparison of the maximum rating and the content rating associated with the content segment and according to a second comparison of the genre information and the genre associated with the content segment; and 
 responsive to determining that the content segment is unnecessary, modifying, by the processing system, the media content item, resulting in a modified media content item, wherein the modified media content item excludes any content segment of the plurality of content segments that is associated with a content rating that exceeds the maximum rating and also excludes any content segment of the plurality of content segments that is associated with any genre identified in the genre information such that the modified media content item is of a particular genre that is different from an overall intended genre of the media content item; and 
   causing, by the processing system, the modified media content item to be streamed to a first device for presenting by the first device.   
     
     
         2 . The method of  claim 1 , wherein the overall intended genre of the media content item comprises an action genre, and wherein the particular genre of the modified media content item comprises a romance genre. 
     
     
         3 . The method of  claim 1 , wherein the maximum rating comprises a Restricted (R) rating, a parents strongly cautioned (PG-13) rating, a parental guidance suggested (PG) rating, or a general audiences (G) rating. 
     
     
         4 . The method of  claim 1 , wherein the detecting the content transitions involves identifying transitions between frames that have been edited by a video or image editing application and frames that have not been edited by a video or image editing application, transitions between frames that do not include any faces and frames that include a particular face or a group of faces, and transitions between frames associated with speech in a determined conversational tone and frames associated with speech in a determined angry tone. 
     
     
         5 . The method of  claim 1 , wherein the historic skipping data is associated with a first user. 
     
     
         6 . The method of  claim 1 , wherein the historic skipping data is associated with a plurality of users. 
     
     
         7 . The method of  claim 1 , wherein the plurality of content segments comprise video frames, scenes, or any combination thereof. 
     
     
         8 . The method of  claim 1 , wherein one or more of the content transitions includes a transition of a video characteristic including color, sharpness, brightness, or any combination thereof. 
     
     
         9 . The method of  claim 1 , wherein one or more of the content transitions includes a transition of an audio characteristic including sound, music, voice, or any combination thereof. 
     
     
         10 . The method of  claim 1 , wherein the one or more content markers relate to faces, voice tone, mood, forms, scenery, or any combination thereof. 
     
     
         11 . The method of  claim 1 , wherein the machine learning algorithm models transitions based on differences in scenery between frames, differences in brightness between frames, differences in background music between frames, and differences in amounts of merged data between frames. 
     
     
         12 . The method of  claim 1 , further comprising modifying the media content item based on skipping instructions that are derived according to second genre information and a second maximum rating, resulting in a modified second media content item, and causing the modified second media content item to be streamed to a second device for presenting by the second device. 
     
     
         13 . A device, comprising:
 a processing system including a processor; and   a memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations, the operations comprising:   determining genre information based on historic skipping data, and determining a maximum rating to apply to the a media content item;   detecting content transitions in the media content item using one or more machine learning algorithms that model transitions as differentials between frames, wherein the one or more machine learning algorithms model transitions based on differences in scenery between frames;   responsive to the detecting the content transitions, for each content segment of a plurality of content segments of the media content item:
 analyzing the content segment to identify one or more content markers in the content segment; 
 determining a plurality of viewing characteristics of the content segment according to the one or more content markers, wherein the plurality of viewing characteristics includes a content rating associated with the content segment and a genre associated with the content segment; 
 determining if the content segment is unnecessary according to a first comparison of the maximum rating and the content rating associated with the content segment and according to a second comparison of the genre information and the genre associated with the content segment; and 
 responsive to determining that the content segment is unnecessary, modifying the media content item, resulting in a modified media content item, wherein the modified media content item excludes any content segment of the plurality of content segments that is associated with a content rating that exceeds the maximum rating and also excludes any content segment of the plurality of content segments that is associated with any genre identified in the genre information such that the modified media content item is of a particular genre that is different from an overall intended genre of the media content item; and 
   causing the modified media content item to be streamed to a first device associated with a first user for presenting by the first device.   
     
     
         14 . The device of  claim 13 , wherein the overall intended genre of the media content item comprises an action genre, and wherein the particular genre of the modified media content item comprises a romance genre. 
     
     
         15 . The device of  claim 13 , wherein the detecting the content transitions involves identifying transitions between frames that have been edited by a video or image editing application and frames that have not been edited by a video or image editing application, transitions between frames that do not include any faces and frames that include a particular face or a group of faces, and transitions between frames associated with speech in a determined conversational tone and frames associated with speech in a determined angry tone. 
     
     
         16 . The device of  claim 13 , wherein one or more of the content transitions includes a transition of a video characteristic, an audio characteristic, or any combination thereof. 
     
     
         17 . The device of  claim 13 , wherein the maximum rating comprises a Restricted (R) rating, a parents strongly cautioned (PG-13) rating, a parental guidance suggested (PG) rating, or a general audiences (G) rating. 
     
     
         18 . A non-transitory machine-readable medium, comprising executable instructions that, when executed by a processing system including a processor, facilitate performance of operations, the operations comprising:
 determining genre information based on historic skipping data, and determining a maximum rating to apply to a media content item;   detecting content transitions in the media content item using a machine learning algorithm that models transitions as differentials between frames, wherein the machine learning algorithm models transitions based on differences in brightness between frames;   responsive to the detecting the content transitions, for each content segment of a plurality of content segments of the media content item:
 analyzing the content segment to identify one or more content markers in the content segment; 
 determining a plurality of viewing characteristics of the content segment according to the one or more content markers, wherein the plurality of viewing characteristics includes a content rating associated with the content segment and a genre associated with the content segment; 
 determining if the content segment is unnecessary according to a first comparison of the maximum rating and the content rating associated with the content segment and according to a second comparison of the genre information and the genre associated with the content segment; and 
 based on determining that the content segment is unnecessary, modifying the media content item, resulting in a modified media content item, wherein the modified media content item excludes any content segment of the plurality of content segments that is associated with a content rating that exceeds the maximum rating and also excludes any content segment of the plurality of content segments that is associated with any genre identified in the genre information such that the modified media content item is of a particular genre that is different from an overall intended genre of the media content item; and 
   causing the modified media content item to be streamed to a first device for presenting by the first device.   
     
     
         19 . The non-transitory machine-readable medium of  claim 18 , wherein the overall intended genre of the media content item comprises an action genre, and wherein the particular genre of the modified media content item comprises a romance genre. 
     
     
         20 . The non-transitory machine-readable medium of  claim 18 , wherein the maximum rating comprises a Restricted (R) rating, a parents strongly cautioned (PG-13) rating, a parental guidance suggested (PG) rating, or a general audiences (G) rating.