Video Content Summarization and Class Selection

A method to classify video content based on meta-algorithmic patterns, the method comprising:

• receiving the video content via a processing system;
• summarizing the video content using a plurality of summarization engines to provide a plurality of summaries via the processing system;
• applying a plurality of meta-algorithmic patterns to the plurality of summaries to provide a plurality of meta-summaries, wherein each of the meta-algorithmic patterns is applied to at least two of the summaries to provide, via the processing system, at least one of the meta-summaries;
• identifying, via the processing system, similarity measures of the video content over each given class of a plurality of classes of video content based on the plurality of summaries and the plurality of meta-summaries;
• and
• selecting, via the processing system, a class of the plurality of classes based on the identified similarity measures.

A non-transitory computer readable medium comprising executable instructions to:

• receive video content;
• apply a plurality of combinations of meta-algorithmic patterns and summarization engines, wherein:
• each summarization engine provides a summary of the video content, and each meta-algorithmic pattern is applied to at least two summaries to provide a meta-summary;
• generate a summarization vector based on summarization terms extracted from the meta-summary;
• generate a class vector for each given class of a plurality of classes of video content, the class vector based on class terms extracted from videos in the given class;
• determine similarity measures of the video content over each class of video content of the plurality of classes, each similarity measure indicative of a similarity between the summarization vector and each class vector;
• and
• select a class of the plurality of classes based on the determined similarity measures.